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DTSTART;TZID=Europe/Vienna:20260218T160000
DTEND;TZID=Europe/Vienna:20260218T170000
DTSTAMP:20260527T005909
CREATED:20251217T115533Z
LAST-MODIFIED:20260326T113244Z
UID:244288-1771430400-1771434000@graphwise.ai
SUMMARY:Beyond the Prototype: Unpacking Scalable\, Enterprise-Ready GraphRAG at Graphwise
DESCRIPTION:On-Demand WEBINAR \n			\n				\n				\n				\n				\n				Beyond the Prototype: Unpacking Scalable\, Enterprise-Ready GraphRAG at Graphwise\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						February 18\, 2026\n					\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n					\n\n\n\n\n	\n		\n		\n      		\n	            \n                \n                    \n\n                    \n                    \n                                                \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                \n                                                                                                                                \n                                                                                                                            \n                                                                                                                                                                                                                        \n                                                                                                                                                                                                                                    \n                                                                            \n                                                                                                                                                                                    \n                        \n                                            \n                    \n                    \n                \n                            \n        \n      		\n		\n		\n		\n	\n	\n\n				\n			\n				\n				\n				\n				\n				Fill out the form to watch this webinar\n			\n				\n				\n				\n				\n				\n			\n				\n				\n			\n		\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Enterprises keep hitting the same RAG wall: great demos\, fragile reality. Retrieval is shallow\, answers drift\, business logic disappears\, and knowledge stays siloed—leaving teams stuck in PoCs that never reach production. \nGraphRAG changes that. \nDuring this on-demand webinar “Beyond the Prototype\,” we introduce GraphRAG: the intelligence layer of the Graphwise platform. It unites LLMs\, structured knowledge\, and multiple search methods to deliver transparent\, verifiable\, enterprise-ready answers. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				You’ll learn how GraphRAG:\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Uses Knowledge Models to interpret and clarify user questions\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Combines graph\, vector\, and full-text search for higher accuracy\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Grounds answers in real relationships to reduce hallucinations\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Shows the exact provenance of every answer\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Works with any major LLM\, vector store\, or ID provider\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Runs as a modular\, scalable\, orchestrated workflow\n					\n				\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				If you’re tired of brittle RAG pipelines and endless prompt tweaking\, this session shows how GraphRAG turns enterprise knowledge into reliable\, audit-ready intelligence that truly works in production.\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				Watch the webinar\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n                \n                    \n\n                    \n                    \n                                                                                    Speaker\n                                                                            \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                        \n                                                                                                                                                    Gerald Mann is VP of Presales at Graphwise and a veteran sales engineering leader who helps organizations turn complex\, siloed data into actionable insights using graph\, semantic\, and AI-driven architectures. He is known for making advanced data and analytics concepts clear\, practical\, and tied to real business outcomes for both technical and executive audiences.
URL:https://graphwise.ai/event/beyond-the-prototype-unpacking-scalable-enterprise-ready-graphrag-at-graphwise/
CATEGORIES:On-demand Webinar
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/12/Beyond-the-Prototype-Unpacking-Scalable-Enterprise-Ready-GraphRAG-2000x1000-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20260211T160000
DTEND;TZID=Europe/Vienna:20260211T170000
DTSTAMP:20260527T005909
CREATED:20251219T124458Z
LAST-MODIFIED:20260225T090928Z
UID:244346-1770825600-1770829200@graphwise.ai
SUMMARY:From Culinary to IoT: How Tietoevry Delivers Real Semantic AI Impact
DESCRIPTION:On-Demand WEBINAR \n			\n				\n				\n				\n				\n				From Culinary to IoT: How Tietoevry Delivers Real Semantic AI Impact\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						February 11\, 2026 \n					\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n					\n\n\n\n\n	\n		\n		\n      		\n	            \n                \n                    \n\n                    \n                    \n                                                \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                \n                                                                                                                                \n                                                                                                                            \n                                                                                                                                                                                                                        \n                                                                                                                                                                                                                                    \n                                                                            \n                                                                                                                                                                                    \n                        \n                                            \n                    \n                    \n                \n                            \n        \n      		\n		\n		\n		\n	\n	\n\n				\n			\n				\n				\n				\n				\n				Fill out the form to watch this webinar\n			\n				\n				\n				\n				\n				\n			\n				\n				\n			\n		\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Many enterprises are excited about generative AI\, but turning that excitement into scalable results often proves difficult. The challenge is that most enterprise data is complex\, interconnected\, and highly contextual. Traditional large language models can generate fluent text\, but they don’t truly understand the domain. \nWatch a webinar hosted together with our partners at Tietoevry\, where we’ll explore how Knowledge Graph-driven Retrieval-Augmented Generation (RAG) helps AI move from guessing to genuine understanding. \nMohammad Shadab\, Senior Data Architect\, and Sebastian Remnerud\, Senior Solution Consultant at Tietoevry\, will walk through two real customer cases that show how this approach works in practice: \nCase 1: Turning IoT data into meaningful insightsSensor data alone rarely tells the full story. By combining knowledge graphs\, LLMs and enriching IoT data with external sources such as weather\, organizations connect previously unrelated signals and move beyond basic monitoring to enable predictive maintenance and profitability insights.The result: IoT data that finally tells a clear story\, enabling predictive actions and confident decisions. \nCase 2: Smarter recipes with domain-aware AIBy grounding generative AI in structured domain knowledge\, this solution significantly improves content quality\, dietary constraint detection\, and personalized recipe recommendations\, enabling intelligent recipe transformation while preserving nutritional intent and culinary context.The result: Now users can trust AI because it understands the domain\, not just the words on the page. \nWhether you’re working with enterprise data\, AI initiatives\, or IoT systems\, this session will offer practical insights you can apply right away! Along with time to raise your own questions and challenges. \n​ \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				Watch the webinar\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n                \n                    \n\n                    \n                    \n                                                                                    Speaker\n                                                                            \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                        \n                                                                                                                                                    Gerald Mann is VP of Presales at Graphwise and a veteran sales engineering leader who helps organizations turn complex\, siloed data into actionable insights using graph\, semantic\, and AI-driven architectures. He is known for making advanced data and analytics concepts clear\, practical\, and tied to real business outcomes for both technical and executive audiences.
URL:https://graphwise.ai/event/from-culinary-to-iot-how-tietoevry-delivers-real-semantic-ai-impact/
CATEGORIES:On-demand Webinar
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/12/How-Tietoevry-Delivers-Real-Semantic-AI-Impact-scaled.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20260129T160000
DTEND;TZID=Europe/Vienna:20260129T170000
DTSTAMP:20260527T005909
CREATED:20251211T125625Z
LAST-MODIFIED:20260218T112955Z
UID:244205-1769702400-1769706000@graphwise.ai
SUMMARY:From Silos to Shared Intelligence: Inside the Graphwise Knowledge Hub
DESCRIPTION:On-Demand WEBINAR \n			\n				\n				\n				\n				\n				From Silos to Shared Intelligence: Inside the Graphwise Knowledge Hub\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						January 29\, 2026\n					\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n					\n\n\n\n\n	\n		\n		\n      		\n	            \n                \n                    \n\n                    \n                    \n                                                \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                \n                                                                                                                                \n                                                                                                                            \n                                                                                                                                                                                                                        \n                                                                                                                                                                                                                                    \n                                                                            \n                                                                                                                                                                                    \n                        \n                                            \n                    \n                    \n                \n                            \n        \n      		\n		\n		\n		\n	\n	\n\n				\n			\n				\n				\n				\n				\n				Fill out the form to watch this webinar\n			\n				\n				\n				\n				\n				\n			\n				\n				\n			\n		\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				​Most conversations about how to efficiently share knowledge and use it to create value within organizations gets stuck in the technical weeds: information is siloed in multiple systems\, there is no (good) metadata to unify them\, Google Search is often the better alternative to enterprise search. At the moment AI is the big promise to solve that. But the real story isn’t in the AI itself. It is in actionable content and context the enterprise manages to provide the AI system with. \nOver the past year\, we built the Graphwise Knowledge Hub\, an AI-driven platform that brings together information from CRM\, marketing\, product docs\, website content\, market research\, and more. By today the  project evolved into a shared knowledge graph driven intelligence layer for the company. A place where sales teams\, marketers\, product experts\, and new colleagues tap into the same pool of knowledge to get the information they need for their different context \nIn this on-demand webinar you will learn how our Graphwise Knowledge Hub and the knowledge practices and governance around it became the focal point for efficient knowledge sharing and having better input for the AI\, to incorporate all of that into the workflow of knowledge accumulation\, making knowledge actionable. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Helmut Nagy\, VP Sales Enablement and Teodora Petkova\, Knowledge Steward\, will share: \n			\n				\n				\n				\n				\n				\n					\n					\n						\n						What we built and why\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						The lessons learned from real internal use\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						How we evaluated whether the Hub truly accelerates enablement\, communication\, and content creation\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						A public demo of the Knowledge Hub so you can explore it yourself\n					\n				\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Curious to see behind the scenes of the Graphwise Knowledge Hub and learn about the processes and practices that make it work?\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				Watch the webinar\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n                \n                    \n\n                    \n                    \n                                                                                    Speaker\n                                                                            \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                        \n                                                                                                                                                    Gerald Mann is VP of Presales at Graphwise and a veteran sales engineering leader who helps organizations turn complex\, siloed data into actionable insights using graph\, semantic\, and AI-driven architectures. He is known for making advanced data and analytics concepts clear\, practical\, and tied to real business outcomes for both technical and executive audiences.
URL:https://graphwise.ai/event/from-silos-to-shared-intelligence-inside-the-graphwise-knowledge-hub/
CATEGORIES:On-demand Webinar
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/12/From-Silos-to-Shared-Intelligence-Inside-the-Graphwise-Knowledge-Hub.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20260121T170000
DTEND;TZID=Europe/Vienna:20260121T180000
DTSTAMP:20260527T005909
CREATED:20251215T175628Z
LAST-MODIFIED:20260218T113801Z
UID:244273-1769014800-1769018400@graphwise.ai
SUMMARY:The Hidden $130M Tax: Stopping the Search Time Drain in Microsoft 365
DESCRIPTION:On-Demand WEBINAR \n			\n				\n				\n				\n				\n				The Hidden $130M Tax: Stopping the Search Time Drain in Microsoft 365\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						January 21\, 2026 \n					\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n					\n\n\n\n\n	\n		\n		\n      		\n	            \n                \n                    \n\n                    \n                    \n                                                \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                \n                                                                                                                                \n                                                                                                                            \n                                                                                                                                                                                                                        \n                                                                                                                                                                                                                                    \n                                                                            \n                                                                                                                                                                                    \n                        \n                                            \n                    \n                    \n                \n                            \n        \n      		\n		\n		\n		\n	\n	\n\n				\n			\n				\n				\n				\n				\n				Fill out the form to watch this webinar\n			\n				\n				\n				\n				\n				\n			\n				\n				\n			\n		\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Most organizations are losing millions without realizing it. 68% of professionals waste 1-5+ hours every week battling poor M365 search\, duplicate documents\, and chasing colleagues for links. In a 5\,000-employee company\, that hidden inefficiency can reach $130M per year. \nA bit more math: 5 wasted hours/week at $100/hour = $26K per employee annually\, a massive drain on your operating budget. \nWatch a focused on-demand session on how to stop this profit leak and maximize your Microsoft 365 investment. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Todd Blaschka\, Senior Executive\, Ben White\, Product Manager together with our partner Toni Ressaire\, Innovation Director at Altuent will walk you through the strategic solution to the root cause of the chaos: \n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Why M365 search fails: inconsistent or missing metadata that makes it impossible to quickly identify the right\, current version of a file \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						The strategic fix-Semantic AI: automatically applies accurate\, governed labels and connects documents using standardized vocabulary \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						How to reclaim capacity: ensure teams instantly find what they need and redirect time toward high-value work like process optimization \n					\n				\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Invest 45 minutes learning how to turn SharePoint into a governed\, reliable knowledge system\, and immediately reclaim millions in lost productivity. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				Watch the webinar\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n                \n                    \n\n                    \n                    \n                                                                                    Speaker\n                                                                            \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                        \n                                                                                                                                                    Gerald Mann is VP of Presales at Graphwise and a veteran sales engineering leader who helps organizations turn complex\, siloed data into actionable insights using graph\, semantic\, and AI-driven architectures. He is known for making advanced data and analytics concepts clear\, practical\, and tied to real business outcomes for both technical and executive audiences.
URL:https://graphwise.ai/event/the-hidden-130m-tax-stopping-the-search-time-drain-in-microsoft-365/
CATEGORIES:On-demand Webinar
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/12/Stopping-the-Search-Time-Drain-in-Microsoft-365-2000x1000-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20251218T160000
DTEND;TZID=Europe/Vienna:20251218T170000
DTSTAMP:20260527T005909
CREATED:20251117T120623Z
LAST-MODIFIED:20260218T114251Z
UID:243636-1766073600-1766077200@graphwise.ai
SUMMARY:Automate Knowledge. Trust your AI
DESCRIPTION:On-Demand WEBINAR \n			\n				\n				\n				\n				\n				Automate Knowledge. Trust your AI\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						December 18\, 2025 \n					\n				\n			\n				\n				\n				\n				\n				\n					}\n					\n						\n						San Francisco | 7:00 a.m. – 8:00 a.m. PST New York | 10:00 a.m. – 11:00 a.m. EST Vienna | 4:00 p.m. – 5:00 p.m. CET \n					\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n					\n\n\n\n\n	\n		\n		\n      		\n	            \n                \n                    \n\n                    \n                    \n                                                \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                \n                                                                                                                                \n                                                                                                                            \n                                                                                                                                                                                                                        \n                                                                                                                                                                                                                                    \n                                                                            \n                                                                                                                                                                                    \n                        \n                                            \n                    \n                    \n                \n                            \n        \n      		\n		\n		\n		\n	\n	\n\n				\n			\n				\n				\n				\n				\n				Fill out the form to watch this webinar\n			\n				\n				\n				\n				\n				\n			\n				\n				\n			\n		\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				2025 marked the breakout year for Graph AI — the shift from niche innovation to the trusted foundation of reliable generative AI. \nJoin us for an end-of-year session with Atanas Kiryakov and Andreas Blumauer as we explore what shaped the market this year and where it’s heading next. You’ll also see the Graphwise AI Platform in action—live demos showing how to make generative AI verifiable\, scalable\, and ready for real business impact. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				We’ll unpack:\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Precise GraphRAG—how knowledge graphs serve as a semantic layer to cut hallucinations and deliver verifiable answers \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Graph Automation—how to build a domain-specific model from your corpus in about an hour \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						The 5-Star Journey—how our integrated platform gets you from concept to production-ready AI in weeks\, not months \n					\n				\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				If you’re ready to turn your data into a trusted semantic backbone and deploy fact-based\, reliable AI applications\, this webinar is for you.\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				Watch the webinar\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n                \n                    \n\n                    \n                    \n                                                                                    Speaker\n                                                                            \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                        \n                                                                                                                                                    Gerald Mann is VP of Presales at Graphwise and a veteran sales engineering leader who helps organizations turn complex\, siloed data into actionable insights using graph\, semantic\, and AI-driven architectures. He is known for making advanced data and analytics concepts clear\, practical\, and tied to real business outcomes for both technical and executive audiences.
URL:https://graphwise.ai/event/automate-knowledge-trust-your-ai/
CATEGORIES:On-demand Webinar
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/11/Automate-Knowledge.-Trust-your-AI_fi.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20251209T160000
DTEND;TZID=Europe/Vienna:20251209T170000
DTSTAMP:20260527T005909
CREATED:20251117T114611Z
LAST-MODIFIED:20260218T123802Z
UID:243622-1765296000-1765299600@graphwise.ai
SUMMARY:Graph Center of Excellence: Preparing for Next Generation AI
DESCRIPTION:Live WEBINAR \n			\n				\n				\n				\n				\n				Graph Center of Excellence: Preparing for Next Generation AI\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						December 9\, 2025\n					\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n					\n\n\n\n\n	\n		\n		\n      		\n	            \n                \n                    \n\n                    \n                    \n                                                \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                \n                                                                                                                                \n                                                                                                                            \n                                                                                                                                                                                                                        \n                                                                                                                                                                                                                                    \n                                                                            \n                                                                                                                                                                                    \n                        \n                                            \n                    \n                    \n                \n                            \n        \n      		\n		\n		\n		\n	\n	\n\n				\n			\n				\n				\n				\n				\n				Fill out the form to watch this webinar\n			\n				\n				\n				\n				\n				\n			\n				\n				\n			\n		\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				As enterprises race toward AI adoption\, many are hitting the same wall: fragmented systems\, inconsistent governance\, low-quality data\, and AI that can’t be trusted. Without unified\, contextualized data\, AI initiatives stall before they scale. \nGraph technology is rapidly emerging as the backbone of enterprise AI — the missing link that connects data\, meaning\, and governance into a single intelligent framework. It reduces cost\, increases trust\, and turns disconnected information into a powerful semantic foundation for analytics\, automation\, and AI. \nIn this recorded session\, you’ll learn how to strategically adopt graph technologies across your organization by establishing a Graph Center of Excellence (CoE). We’ll break down why a Graph CoE is becoming essential for enterprises navigating the AI era—and how it accelerates your path from experimentation to production-ready\, context-rich AI. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				We’ll explore:\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						The core pillars of a Graph CoE and how to deploy it across your enterprise \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Strategic graph adoption to unify\, govern\, and enrich your data\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Real-world use cases driving measurable business impact\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Why organizations must rethink their data management paradigm\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						How to eliminate the ongoing “Bad Data Tax” draining AI ROI\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						How a Graph CoE powers context engineering for AI solutions\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						How it streamlines the creation of GraphRAG-based and domain-specific AI applications\n					\n				\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Watch now to learn how establishing a Graph Center of Excellence can revolutionize your enterprise. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				Watch Now\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n                \n                    \n\n                    \n                    \n                                                                                    Speaker\n                                                                            \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                        \n                                                                                                                                                    Gerald Mann is VP of Presales at Graphwise and a veteran sales engineering leader who helps organizations turn complex\, siloed data into actionable insights using graph\, semantic\, and AI-driven architectures. He is known for making advanced data and analytics concepts clear\, practical\, and tied to real business outcomes for both technical and executive audiences.
URL:https://graphwise.ai/event/graph-coe-preparing-for-next-generation-ai/
CATEGORIES:On-demand Webinar
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/11/Graph-Technologies-AI-Thought-Leader.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20251120T170000
DTEND;TZID=Europe/Vienna:20251120T180000
DTSTAMP:20260527T005909
CREATED:20251022T094040Z
LAST-MODIFIED:20260218T124414Z
UID:242826-1763658000-1763661600@graphwise.ai
SUMMARY:Accelerating Decision-Making in Finance:  AI & Graphs in Action
DESCRIPTION:On-Demand WEBINAR \n			\n				\n				\n				\n				\n				Accelerating Decision-Making in Finance: AI & Graphs in Action\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						November 20\, 2025\n					\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n					\n\n\n\n\n	\n		\n		\n      		\n	            \n                \n                    \n\n                    \n                    \n                                                \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                \n                                                                                                                                \n                                                                                                                            \n                                                                                                                                                                                                                        \n                                                                                                                                                                                                                                    \n                                                                            \n                                                                                                                                                                                    \n                        \n                                            \n                    \n                    \n                \n                            \n        \n      		\n		\n		\n		\n	\n	\n\n				\n			\n				\n				\n				\n				\n				Fill out the form to watch this webinar\n			\n				\n				\n				\n				\n				\n			\n				\n				\n			\n		\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Watch this insightful webinar where we explore the latest Graphwise case studies from the financial industry\, demonstrating how graph technology and AI are driving decision automation across critical business areas. \nCase studies covered: \n\nOperational Resiliency (DORA) Compliance Automation: demonstrate compliance by automatic fulfillment of regulation requirements.\nCredit Risk Assessment: Enhancing accuracy and efficiency in risk evaluation.\nCompliance Issue Resolution: Automating the detection of risks and resolution of compliance inquiries.\nAutomated Regulatory Reporting: streamlining regulatory reporting from a enterprise semantic layer\nSelf-Service Analytics: Empowering business users with Natural Language Querying (NLQ) over the Semantic Layer for actionable insights.\n\nBusiness Value: \n\nMeasure business value and key performance indicators (KPIs) impacted by these innovations.\n\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Technology Enablers:\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Semantic Graphs vs. Relational baseline: Learn the differentiating advantages of graph-based architectures\, compared to a baseline based on the traditional relational approach.\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Agentic-Assisted Modeling\, Mapping\, and Validation: Accelerate decision automation with AI-driven support for more robust and agile operations.\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						AI Agent Orchestration: Leverage automation platforms for seamless coordination and faster insights across business processes.\n					\n				\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Watch the webinar and learn how these powerful technologies can optimize your financial operations. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				Watch now\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n                \n                    \n\n                    \n                    \n                                                                                    Speaker\n                                                                            \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                        \n                                                                                                                                                    Gerald Mann is VP of Presales at Graphwise and a veteran sales engineering leader who helps organizations turn complex\, siloed data into actionable insights using graph\, semantic\, and AI-driven architectures. He is known for making advanced data and analytics concepts clear\, practical\, and tied to real business outcomes for both technical and executive audiences.
URL:https://graphwise.ai/event/accelerating-decision-making-in-finance-ai-graphs-in-action/
CATEGORIES:On-demand Webinar
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/10/Accelerating-Decision-Making-in-Finance-AI-Graphs-in-Action-featured-image.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251117
DTEND;VALUE=DATE:20251121
DTSTAMP:20260527T005909
CREATED:20250813T165935Z
LAST-MODIFIED:20250813T165937Z
UID:241039-1763337600-1763683199@graphwise.ai
SUMMARY:KMWorld 2025
DESCRIPTION:KMWorld 2025—Enterprise Intelligence: Collaboration & Knowledge Sharing for Success—takes place November 17–20\, 2025\, at the JW Marriott\, Washington\, D.C. This flagship event convenes leaders across knowledge management\, information architecture\, AI\, and enterprise collaboration for a powerhouse of thought leadership\, practical workshops\, and immersive training. \nCo-located alongside KMWorld are four specialty conferences—Taxonomy Boot Camp\, Enterprise Search & Discovery\, Text Analytics Forum\, and Enterprise AI World—creating a dynamic ecosystem for innovation in enterprise solutions. With a Platinum Pass\, attendees unlock access to all five events\, gaining insider access to cutting-edge tools\, techniques\, networking\, and cross-disciplinary insights. \nAt its core\, KMWorld 2025 emphasizes how human ingenuity and AI-driven strategies intersect to foster transformative knowledge sharing—covering topics like search optimization\, taxonomy design\, AI governance\, digital collaboration\, cognitive tools\, and resilience in hybrid work environments. \n			\n				register now
URL:https://graphwise.ai/event/kmworld-2025/
LOCATION:JW Marriott Washington DC\, 1331 Pennsylvania Avenue NW\, Washington\, DC\, 20004\, United States
CATEGORIES:Event
ATTACH;FMTTYPE=image/jpeg:https://graphwise.ai/wp-content/uploads/2025/08/KMW25_OG_1200x630.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20251105T163000
DTEND;TZID=Europe/Vienna:20251105T173000
DTSTAMP:20260527T005909
CREATED:20250930T134657Z
LAST-MODIFIED:20260218T133858Z
UID:242463-1762360200-1762363800@graphwise.ai
SUMMARY:Talk to Your Graph
DESCRIPTION:On-Demand WEBINAR \n			\n				\n				\n				\n				\n				Talk to Your Graph\n			\n				\n				\n				\n				\n				See how leading organizations are using Talk to Your Graph \n			\n				\n				\n				\n				\n				\n					\n					\n						\n						November 5\, 2025 \n					\n				\n			\n				\n				\n				\n				\n				\n					}\n					\n						\n						San Francisco | 7:30 a.m. – 8:30 a.m. PST New York | 10:30 a.m. – 11:30 a.m. EST Vienna | 4:30 p.m. – 5:30 p.m. CET \n					\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n					\n\n\n\n\n	\n		\n		\n      		\n	            \n                \n                    \n\n                    \n                    \n                                                \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                \n                                                                                                                                \n                                                                                                                            \n                                                                                                                                                                                                                        \n                                                                                                                                                                                                                                    \n                                                                            \n                                                                                                                                                                                    \n                        \n                                            \n                    \n                    \n                \n                            \n        \n      		\n		\n		\n		\n	\n	\n\n				\n			\n				\n				\n				\n				\n				Fill out the form to watch this webinar\n			\n				\n				\n				\n				\n				\n			\n				\n				\n			\n		\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Watch a technical showcase of how leading organizations are using Talk to Your Graph (TTYG) to enable natural language interaction with complex\, graph-based data. \nModerated by Andreas Blumauer\, this session features real-world implementations from five companies working with diverse datasets and graph architectures. The focus will be on practical insights\, architectural choices\, and the evolving role of conversational interfaces in enterprise knowledge systems. \nIdeal for data engineers\, knowledge graph architects\, and technical leads exploring applied semantics\, NLP\, and graph technology. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Watch now to be among the first to learn about Talk to Your Graph use cases! \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				Watch Now\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n                \n                    \n\n                    \n                    \n                                                                                    Speaker\n                                                                            \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                        \n                                                                                                                                                    Gerald Mann is VP of Presales at Graphwise and a veteran sales engineering leader who helps organizations turn complex\, siloed data into actionable insights using graph\, semantic\, and AI-driven architectures. He is known for making advanced data and analytics concepts clear\, practical\, and tied to real business outcomes for both technical and executive audiences.
URL:https://graphwise.ai/event/webinar-talk-to-your-graph/
CATEGORIES:On-demand Webinar
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/09/Talk-to-your-Graph-featured-image.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251103
DTEND;VALUE=DATE:20251108
DTSTAMP:20260527T005909
CREATED:20250822T103131Z
LAST-MODIFIED:20250822T103132Z
UID:241272-1762128000-1762559999@graphwise.ai
SUMMARY:TechCon365: MICROSOFT 365\, POWER PLATFORM & COPILOT CONFERENCE
DESCRIPTION:Join us at TechCon 365: MICROSOFT 365\, POWER PLATFORM & COPILOT CONFERENCE in Dallas\, TX! \nThis is the premier in-person conference focused on Microsoft 365\, Power Platform\, Azure\, Copilot\, and AI technologies. The 2025 edition is scheduled for November 3–7\, 2025\, hosted at the Irving Convention Center in Irving\, Texas. \nAttendees can access over 130 sessions across multiple tracks and 25 workshops tailored to varying experience levels—from beginners to advanced professionals.  \nThemes of the conference include:  \n\nMicrosoft 365 & Copilot adoption\, governance\, and deployment\nPower Platform & automation workflows (Power Apps\, Power Automate\, Power BI)\nSharePoint & content/information architecture\nAI & Azure development including Copilot Studio\, Azure OpenAI\, custom agents\nBroader tools: Viva\, Microsoft Fabric\, Dataverse\, Syntex\, OneDrive\, Teams\, Loop\, Search\, and more!\n\nThe success of the 2024 event sets a strong precedent for 2025\, with a robust agenda\, expert speakers\, and rich opportunities to connect and grow. \nWe look forward to connecting with you at our booth! \n			\n				register now
URL:https://graphwise.ai/event/techcon365-dallas-2025/
LOCATION:Irving Convention Center\, 500 W. Las Colinas Blvd\, Irving\, TX\, 75039\, United States
CATEGORIES:Event
ATTACH;FMTTYPE=image/jpeg:https://graphwise.ai/wp-content/uploads/2025/08/techcon365_dallas_2025.jpeg
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251022
DTEND;VALUE=DATE:20251024
DTSTAMP:20260527T005909
CREATED:20250708T135637Z
LAST-MODIFIED:20260226T150958Z
UID:239801-1761091200-1761263999@graphwise.ai
SUMMARY:Graphwise AI Summit 2025
DESCRIPTION:ONline conference \n			\n				\n				\n				\n				\n				Graphwise AI Summit 2025\n			\n				\n				\n				\n				\n				Unlocking Intelligent Applications & Business Impact with Trustworthy AI & Knowledge Graphs \n			\n				\n				\n				\n				\n				\n					\n					\n						\n						October 22nd – 23rd\, 2025 \n					\n				\n			\n				Watch on demand\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Navigating AI’s Landscape: Agentic AI\, GenAI\, RAG & more\n			\n				\n				\n				\n				\n				One year after the strategic merger combining GraphDB and PoolParty technologies\, Graphwise comes for a two-day online event packed with virtual talks\, panels\, and demos with industry leaders\, partners and innovators.\nExplore the strategic impact of semantic technologies and knowledge graphs on cutting-edge AI\, diving into real-world use-cases in Financial Services\, Healthcare & Life Sciences\, and beyond. \n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				 \n				Expert speakers\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				 \n				global attendees\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				 \n				strategic insights\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Learn how to build a GraphRAG solution in a couple of steps and make use of our Graphwise AI Graph Suite latest features \n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Tailor Your Summit Experience\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n					\n					\n						Strategic AI Solutions\n						Wednesday\, 22nd October\nFor AI strategists & decision-makers to explore how to leverage Graphwise for business growth and innovation. \nWhat you will see: \n\nStrategic insights on cutting-edge AI & KGs\nReal-world use cases & industry pain points\nSuccess stories across industries & proven ROI\n\n					\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n					\n					\n						Technical Deep Dive\n						Thursday\, 23rd October\nFor hands-on innovators & technical professionals to dive into Graphwise platform’s advanced capabilities. \nWhat you will see: \n\nGraphwise platform\, integrations and portfolio\nDeep dives into core technologies & new features\nPractical tips for developers on how to best use our platform
URL:https://graphwise.ai/event/graphwise-ai-summit-2025/
LOCATION:Online
CATEGORIES:Online Event
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/07/AI-Summit-2025-fea-Img.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251006
DTEND;VALUE=DATE:20251009
DTSTAMP:20260527T005910
CREATED:20250813T164440Z
LAST-MODIFIED:20251003T075938Z
UID:241031-1759708800-1759967999@graphwise.ai
SUMMARY:BioTechX Europe 2025
DESCRIPTION:BioTechX Europe 2025 (6–8 October) is Europe’s largest biotech congress\, held at Messe Basel\, Switzerland. Expect over 3\,000 attendees\, 400+ speakers\, 150+ exhibitors\, and 50 cutting-edge start-ups tackling diagnostics\, precision medicine\, AI\, and digital transformation across pharma and healthcare. \nThe event blends forward-looking conference sessions with a bustling exhibition floor and extensive networking opportunities. Topics span from AI in drug development and real-world evidence to genomics\, single-cell analysis\, FAIR data\, and cheminformatics—making it a prime destination for industry professionals seeking innovation and collaboration. \n			\n				\n				\n				\n				\n				\nTalk: October 7\nIlian Uzunov and Todor Primov’s talk\, Beyond the Limits of GenAI\, will explore how semantic technology and graph-based AI help life sciences organizations: \n\nBreak down data silos and advance FAIR data practices\nUnlock hidden relationships in data\nBuild scalable and trustworthy AI applications\n\n			\n				register now
URL:https://graphwise.ai/event/biotechx-europe-2025/
LOCATION:Messe Basel
CATEGORIES:Event
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/08/BioTechX_Europe_2025_1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20251001T163000
DTEND;TZID=Europe/Vienna:20251001T173000
DTSTAMP:20260527T005910
CREATED:20250822T105346Z
LAST-MODIFIED:20260218T134236Z
UID:241289-1759336200-1759339800@graphwise.ai
SUMMARY:Maximizing Productivity with GraphRAG
DESCRIPTION:ON-DEMAND WEBINAR \n			\n				\n				\n				\n				\n				Maximizing Productivity with GraphRAG\n			\n				\n				\n				\n				\n				Five Use Cases of Retrieval Augmented Generation \n			\n				\n				\n				\n				\n				\n					\n					\n						\n						October 1\, 2025 \n					\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n					\n\n\n\n\n	\n		\n		\n      		\n	            \n                \n                    \n\n                    \n                    \n                                                \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                \n                                                                                                                                \n                                                                                                                            \n                                                                                                                                                                                                                        \n                                                                                                                                                                                                                                    \n                                                                            \n                                                                                                                                                                                    \n                        \n                                            \n                    \n                    \n                \n                            \n        \n      		\n		\n		\n		\n	\n	\n\n				\n			\n				\n				\n				\n				\n				Fill out the form to watch this webinar\n			\n				\n				\n				\n				\n				\n			\n				\n				\n			\n		\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Bringing Confidence to AI \nAre you struggling to realize the full value of your AI initiatives\, facing challenges with data scalability\, user satisfaction\, or even compliance? This webinar will demonstrate how GraphRAG directly addresses these critical business problems and significantly improves AI performance by leveraging enterprise knowledge graphs and a robust semantic layer. \nJoin us for a highly practical session where we will debate five distinct industry use cases\, showcasing real-world applications and measurable outcomes: \n Global Manufacturing: See how GraphRAG provides precise\, quality-assured answers to complex technical questions about systems like hydraulics\, outperforming VectorRAG and pure LLMs in accuracy and enhancing support engineer efficiency. \n Research Organizations: Discover how GraphRAG built a functioning AI assistant for over multilingual policy documents\, exceeding a 95% correct answer rate and substantially enhancing retrieval accuracy. \n Pharmaceutical/Biopharmaceutical Companies: Learn how GraphRAG accelerates the process of bringing new molecules to market by structuring company-wide data into knowledge graphs\, enabling faster deployment of LLMs\, scalability to millions of records\, and automation of business processes like submissions to authorities. \n Software Vendors: Explore how GraphRAG improves self-service portals by preserving content structures and using domain-specific metadata for precise retrieval\, leading to answers that truly interpret user questions and minimize hallucinations. \n Big Four Consultancies: Understand how GraphRAG facilitates knowledge discovery across disconnected content silos\, leading to enhanced content accessibility\, improved collaboration efficiency\, and increased operational agility for internal stakeholders. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				This webinar will reveal how GraphRAG solutions drive tangible benefits and key performance indicators (KPIs) across your organization::\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						AI Accuracy & Reliability: Boost model accuracy to 90–100% and reduce hallucinations using a GraphRAG model grounded in real-world data. \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Efficiency & Cost: Cut manual tagging by 60%\, speed up search by 40%\, and reduce duplicate work by 50%\, while lowering RAG costs and LLM usage. \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Productivity & Speed: Save 30+ minutes per query\, increase project efficiency by 30%\, and reduce time-to-market by 40%. \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Innovation & Growth: Improve access to information and collaboration\, enabling faster decisions and supporting 25% revenue growth. \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Compliance & Governance: Automatically map content to regulations\, flag risks\, and ensure auditability with consistent metadata. \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						And much more! \n					\n				\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Watch now to learn how GraphRAG transforms disparate data into an “AI-ready data layer” through a multimodal data fabric and a semantic layer\, ensuring comprehensive data utilization and bringing true confidence to your AI initiatives. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				Watch the webinar\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n                \n                    \n\n                    \n                    \n                                                                                    Speaker\n                                                                            \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                        \n                                                                                                                                                    Gerald Mann is VP of Presales at Graphwise and a veteran sales engineering leader who helps organizations turn complex\, siloed data into actionable insights using graph\, semantic\, and AI-driven architectures. He is known for making advanced data and analytics concepts clear\, practical\, and tied to real business outcomes for both technical and executive audiences.
URL:https://graphwise.ai/event/maximizing-productivity-with-graphrag/
CATEGORIES:On-demand Webinar
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/08/October-1-2025-featured-image-web.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251001
DTEND;VALUE=DATE:20251003
DTSTAMP:20260527T005910
CREATED:20250618T145737Z
LAST-MODIFIED:20250923T092804Z
UID:239468-1759276800-1759449599@graphwise.ai
SUMMARY:Big Data & AI Paris
DESCRIPTION:The Origins of BIG DATA & AI PARISThe rapid development of Big Data in France\, fueled by the growth of Cloud Computing and the opening of public data\, created a clear need for structure and collaboration within the emerging ecosystem. It was in this context that Big Data Paris was launched—bringing together experts\, decision-makers\, and innovators from across the sector. \nA few years later\, with the rise of deep learning and the launch of France’s national AI strategy in 2018\, Artificial Intelligence took center stage. To meet this momentum and support the practical application of AI technologies\, AI Paris was born. \nToday\, Big Data and AI are inseparable. AI relies on data to learn\, and Big Data finds its full value through the intelligent systems that interpret it. To reflect this deep interconnection and help professionals seamlessly explore both domains\, Big Data Paris and AI Paris have united into a single strategic event:🎉 BIG DATA & AI PARIS. \nWhether you want to navigate both fields or dive deeper into one\, BIG DATA & AI PARIS is the ultimate meeting point for those shaping the future of data and intelligent technology. \nWe look forward to meeting you in Paris – register now! \n			\n				register now
URL:https://graphwise.ai/event/big-data-and-ai-paris-2025/
LOCATION:Paris Expo Porte de Versailles\, 1 Pl. de la Porte de Versailles\, Paris\, 75015\, France
CATEGORIES:Event
ATTACH;FMTTYPE=image/jpeg:https://graphwise.ai/wp-content/uploads/2025/06/Big-Data-AI-Paris-2025.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251001
DTEND;VALUE=DATE:20251002
DTSTAMP:20260527T005910
CREATED:20250813T162825Z
LAST-MODIFIED:20250813T162827Z
UID:241020-1759276800-1759363199@graphwise.ai
SUMMARY:Semantic Layer Symposium 2025
DESCRIPTION:Semantic Layer Symposium 2025 is the premier in-person forum for professionals exploring the power of semantic technologies in transforming data into meaningful business intelligence. Held on Wednesday\, October 1\, 2025\, at the luxurious Nimb Hotel in Copenhagen\, this one-day event (with an optional pre-conference workshop) brings together data leaders\, knowledge management professionals\, semantic specialists\, and academics to share real-world strategies and insights. \nAttendees will explore practical use cases\, networking opportunities\, and expert-led sessions focused on implementing semantic layers—from bridging data silos and shaping scalable infrastructure to delivering actionable\, context-rich insights in enterprise environments. \n			\n				register now
URL:https://graphwise.ai/event/semantic-layer-symposium-2025/
LOCATION:NIMB HOTEL\, Bernstorffsgade 5\, Copenhagen\, 1577\, Denmark
CATEGORIES:Event
ATTACH;FMTTYPE=image/jpeg:https://graphwise.ai/wp-content/uploads/2025/08/semanticlayersymposium2025.jpeg
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250924
DTEND;VALUE=DATE:20250926
DTSTAMP:20260527T005910
CREATED:20250618T142746Z
LAST-MODIFIED:20250618T142747Z
UID:239455-1758672000-1758844799@graphwise.ai
SUMMARY:Nordic TechKomm 2025
DESCRIPTION:Join us in Copenhagen for NORDIC TechKomm\, where international experts in technical communication come together to explore the latest trends\, challenges\, and innovations in the field. \nThis year’s theme is “Level Up Your Technical Communication”—a call to action for professionals ready to take their skills and strategies to the next level. \nDesigned for those with an advanced understanding of technical communication\, NORDIC TechKomm brings together technical writers\, information developers\, content architects\, and TC managers to share insights\, best practices\, and cutting-edge solutions. \nWhether you’re looking to refine your content strategy\, explore new tools\, or connect with peers from across the industry\, NORDIC TechKomm offers the perfect platform for growth\, networking\, and inspiration. \n📍 Copenhagen awaits—don’t miss this opportunity to elevate your expertise and be part of the conversation shaping the future of technical communication. \n			\n				register now
URL:https://graphwise.ai/event/nordic-techkomm-copenhagen-2025/
LOCATION:Scandic Sydhavnen\, Sydhavns Plads 15\, Copenhagen SV\, 2450\, Denmark
CATEGORIES:Event
ATTACH;FMTTYPE=image/webp:https://graphwise.ai/wp-content/uploads/2025/06/NORDIC-TechKOMM-2025-conference.webp
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20250917T170000
DTEND;TZID=Europe/Vienna:20250917T180000
DTSTAMP:20260527T005910
CREATED:20250612T103516Z
LAST-MODIFIED:20260218T134534Z
UID:239318-1758128400-1758132000@graphwise.ai
SUMMARY:How Knowledge Managers can use Copilot agents to break down content silos in SharePoint
DESCRIPTION:On-Demand WEBINAR \n			\n				\n				\n				\n				\n				How Knowledge Managers can use Copilot agents to break down content silos in SharePoint\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						September 17\, 2025 \n					\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n					\n\n\n\n\n	\n		\n		\n      		\n	            \n                \n                    \n\n                    \n                    \n                                                \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                \n                                                                                                                                \n                                                                                                                            \n                                                                                                                                                                                                                        \n                                                                                                                                                                                                                                    \n                                                                            \n                                                                                                                                                                                    \n                        \n                                            \n                    \n                    \n                \n                            \n        \n      		\n		\n		\n		\n	\n	\n\n				\n			\n				\n				\n				\n				\n				Fill out the form to watch this webinar\n			\n				\n				\n				\n				\n				\n			\n				\n				\n			\n		\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				About our ‘How Knowledge Managers can use Copilot agents’ webinar\nAre you a Knowledge Manager struggling with information overload\, siloed SharePoint sites\, and the constant challenge of ensuring employees can quickly access accurate information? \nDiscover how to leverage Microsoft Copilot agents–enhanced with AI-powered taxonomy management and auto-tagging for SharePoint–to transform your organization’s knowledge landscape. \nWatch Graphwise\, developers of cutting-edge semantic AI software\, and Altuent\, a knowledge management consultancy for this webinar. We’ll provide practical insights on how to make Copilot agents more reliable\, increase traceability\, trust and efficiency. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Discover the unparalleled features of Graphwise for M365:\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						A solution that prevents SharePoint being a siloed\, chaotic mess\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						How to add a semantic layer (with AI automations) to your unstructured content\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						We aim to give you practical insights on how to make Copilot agents in your KM process more reliable\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						How to unleash the power of Copilot agents to retrieve specific information from SharePoint\n					\n				\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				Watch the webinar\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n                \n                    \n\n                    \n                    \n                                                                                    Speaker\n                                                                            \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                        \n                                                                                                                                                    Gerald Mann is VP of Presales at Graphwise and a veteran sales engineering leader who helps organizations turn complex\, siloed data into actionable insights using graph\, semantic\, and AI-driven architectures. He is known for making advanced data and analytics concepts clear\, practical\, and tied to real business outcomes for both technical and executive audiences.
URL:https://graphwise.ai/event/how-knowledge-managers-can-use-copilot-agents-breakdown-silos-sharepoint/
LOCATION:Online
CATEGORIES:On-demand Webinar
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/06/September-17-2025-copilot-agents-sharepoint-webinar-featured-image.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20250910T170000
DTEND;TZID=Europe/Vienna:20250910T170000
DTSTAMP:20260527T005910
CREATED:20250812T180947Z
LAST-MODIFIED:20260218T135012Z
UID:241003-1757523600-1757523600@graphwise.ai
SUMMARY:Introducing Graphwise Sandbox: Explore the Power of GraphDB in Minutes
DESCRIPTION:On-Demand WEBINAR \n			\n				\n				\n				\n				\n				Introducing Graphwise Sandbox\n			\n				\n				\n				\n				\n				Explore the Power of GraphDB in Minutes \n			\n				\n				\n				\n				\n				\n					\n					\n						\n						September 10\, 2025 \n					\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n					\n\n\n\n\n	\n		\n		\n      		\n	            \n                \n                    \n\n                    \n                    \n                                                \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                \n                                                                                                                                \n                                                                                                                            \n                                                                                                                                                                                                                        \n                                                                                                                                                                                                                                    \n                                                                            \n                                                                                                                                                                                    \n                        \n                                            \n                    \n                    \n                \n                            \n        \n      		\n		\n		\n		\n	\n	\n\n				\n			\n				\n				\n				\n				\n				Fill out the form to watch this webinar\n			\n				\n				\n				\n				\n				\n			\n				\n				\n			\n		\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Unlock the Power of Connected Data in Minutes  \nAre you curious about the power of GraphDB and knowledge graphs\, but unsure where to start? Graphwise Sandbox\, our newly launched self-service environment\, provides you with immediate\, hands-on access to GraphDB\, complete with curated datasets and interactive guidance—no setup required! \nIn this webinar\, you’ll learn about the capabilities included in Graphwise Sandbox\, from the ease of launching isolated demo environments to exploring data through natural language queries. We’ll showcase the initial set of demo projects\, including Ontotext’s Knowledge Graph\, European Railway Navigator\, Ontology Navigator with FIBO\, Star Wars Universe Explorer\, and the Semantic Movies Recommender. Discover how these real-world datasets and guided interactions allow users—from data enthusiasts to enterprise architects—to experience semantic technology in action. \nWe’ll cover key features such as tenant-level data isolation\, external tool connectivity\, and flexible sandbox lifespans\, along with clear insights into resource limitations\, including data volume constraints\, query concurrency\, and token usage. Lastly\, we’ll offer a glimpse into future enhancements\, revealing our plans to expand the Sandbox to additional Graphwise products and datasets. \nWatch this webinar and learn how you can instantly start exploring the value of GraphDB and semantic technologies through Graphwise Sandbox. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Key takeaways from this webinar include:\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						How to quickly register and launch Graphwise Sandbox. \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						The available demo projects and how they illustrate real-world graph use cases. \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Technical capabilities and limitations of the Sandbox. \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Best practices for maximizing your sandbox experience. \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						What’s coming next from Graphwise! \n					\n				\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Ready to explore GraphDB instantly? Watch this webinar and unlock the full potential of your data. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				Watch the webinar\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n                \n                    \n\n                    \n                    \n                                                                                    Speaker\n                                                                            \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                        \n                                                                                                                                                    Gerald Mann is VP of Presales at Graphwise and a veteran sales engineering leader who helps organizations turn complex\, siloed data into actionable insights using graph\, semantic\, and AI-driven architectures. He is known for making advanced data and analytics concepts clear\, practical\, and tied to real business outcomes for both technical and executive audiences.
URL:https://graphwise.ai/event/introducing-graphwise-sandbox-explore-the-power-of-graphdb-in-minutes/
LOCATION:Online
CATEGORIES:On-demand Webinar
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/08/Sept-10-2025-featured-image-webinar.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20250909T160000
DTEND;TZID=Europe/Vienna:20250909T193000
DTSTAMP:20260527T005910
CREATED:20250811T133509Z
LAST-MODIFIED:20250811T153906Z
UID:240986-1757433600-1757446200@graphwise.ai
SUMMARY:UNDERPIN Road Show | Vienna
DESCRIPTION:Join us for the UNDERPIN Road Show in Vienna\, a key event exploring how data spaces and AI are transforming the future of manufacturing and energy sectors. Part of the UNDERPIN project\, this event brings together industry leaders\, innovators\, and stakeholders for an afternoon of expert talks\, real-world use cases\, and networking. \nWhat to Expect: \n\nInsights into data sharing and predictive maintenance in manufacturing\nLatest on the Underpin Data Space for Manufacturing Excellence\nUpdates on Digital Product Passports (DPP) and their role in sustainability\nPerspectives from SMEs\, service providers\, OEMs\, and more\nNetworking with drinks & finger food\n\nAgenda Highlights: \n\nWelcome by Vienna Business Agency\nKeynotes from Graphwise\, Motor Oil\, and AIT\nUse cases in wind energy\, AI-driven maintenance\, and digital twins\nInteractive Q&A and networking session\n\nThis event is ideal for professionals in manufacturing\, energy\, AI\, and sustainability—from machine tool makers to recyclers. \n			\n				register now
URL:https://graphwise.ai/event/underpin-road-show-in-viennaon-site-event-template-duplicate-me/
LOCATION:Expat Center of the Vienna Business Agency\, Schmerlingpl. 3\, Vienna\, 1010\, Austria
CATEGORIES:Event
ATTACH;FMTTYPE=image/jpeg:https://graphwise.ai/wp-content/uploads/2025/08/VIENNA-Road-show-all-980x551-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250903
DTEND;VALUE=DATE:20250906
DTSTAMP:20260527T005910
CREATED:20250514T161458Z
LAST-MODIFIED:20250618T144425Z
UID:168073-1756857600-1757116799@graphwise.ai
SUMMARY:SEMANTiCS 2025
DESCRIPTION:  \n📢Last Chance to Submit: SEMANTiCS 2025 – Industry & Use Case Presentations \nHave a real-world solution using Linked Data\, Knowledge Graphs\, Artificial Intelligence\, Machine Learning\, Data Publishing\, Thesaurus and/or Ontology management\, and any related fields? This is your chance to showcase it! SEMANTiCS 2025 is looking for impactful Industry & Use Cases that go beyond prototypes and demonstrate the power of semantic systems. \n📍 Vienna\, Austria | Sept 3-5\, 2025\n🗓️ Submission Deadline Approaching: June 1\, 2025 (11:59 pm AoE) \n🔗 More info: https://2025-eu.semantics.cc/page/industry \n \n			\n				register now
URL:https://graphwise.ai/event/semantics-vienna-2025/
LOCATION:Hilton Vienna Waterfront\, Handelskai 269\, Vienna\, 1020
CATEGORIES:Event
ATTACH;FMTTYPE=image/jpeg:https://graphwise.ai/wp-content/uploads/2025/05/semantics_2025_feature_img.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20250828T180000
DTEND;TZID=Europe/Vienna:20250828T190000
DTSTAMP:20260527T005910
CREATED:20250807T130422Z
LAST-MODIFIED:20260219T115224Z
UID:164832-1756404000-1756407600@graphwise.ai
SUMMARY:Webinar: Building a Semantic Layer with AI Agents
DESCRIPTION:On-Demand WEBINAR \n			\n				\n				\n				\n				\n				Building a Semantic Layer with AI Agents\n			\n				\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						August 28\, 2025\n					\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n					\n\n\n\n\n	\n		\n		\n      		\n	            \n                \n                    \n\n                    \n                    \n                                                \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                \n                                                                                                                                \n                                                                                                                            \n                                                                                                                                                                                                                        \n                                                                                                                                                                                                                                    \n                                                                            \n                                                                                                                                                                                    \n                        \n                                            \n                    \n                    \n                \n                            \n        \n      		\n		\n		\n		\n	\n	\n\n				\n			\n				\n				\n				\n				\n				Fill out the form to watch this webinar\n			\n				\n				\n				\n				\n				\n			\n				\n				\n			\n		\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Unlocking Intelligent Insights \nAs organizations drown in vast volumes of structured and unstructured data\, the need for a robust semantic layer has become critical to enable intelligent understanding across heterogenous data. \nThis on-demand webinar\, discusses building graph-structured semantic layers that encodes ontologies\, metadata\, and lineage allowing explainable understanding of domain semantics using AI agents powered by knowledge graphs and Graph RAG. \nThis combines symbolic reasoning capabilities of knowledge graphs with generative power of LLMs for AI agents to dynamically interpret business context\, navigate complex data relationships\, and generate accurate\, context-aware insights. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Key Takeaways from the webinar:\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Why Semantic Layer is the critical missing piece in the enterprise data management space\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						How can organizations approach building a Semantic Layer\n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						How Graphwise.AI can help organizations build the Semantic layer with Agents \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Live demo with Q&A session!\n					\n				\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				The session will cover architectural patterns and design principles for integrating Graph RAG into your data ecosystem\, enabling agents to retrieve precise subgraphs relevant to a user query\, and augment generative responses with structured context. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				Watch the webinar\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n                \n                    \n\n                    \n                    \n                                                                                    Speaker\n                                                                            \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                        \n                                                                                                                                                    Gerald Mann is VP of Presales at Graphwise and a veteran sales engineering leader who helps organizations turn complex\, siloed data into actionable insights using graph\, semantic\, and AI-driven architectures. He is known for making advanced data and analytics concepts clear\, practical\, and tied to real business outcomes for both technical and executive audiences.
URL:https://graphwise.ai/event/building-a-semantic-layer-with-ai-agents/
CATEGORIES:On-demand Webinar
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/05/Webinar-Featured-Image_August-28-2025.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20250819T170000
DTEND;TZID=Europe/Vienna:20250819T180000
DTSTAMP:20260527T005910
CREATED:20250807T113041Z
LAST-MODIFIED:20260219T120411Z
UID:240779-1755622800-1755626400@graphwise.ai
SUMMARY:How to Think About Agentic AI’s Challenges and Opportunities
DESCRIPTION:ON-Demand WEBINAR \n			\n				\n				\n				\n				\n				How to Think About Agentic AI’s Challenges and Opportunities\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						August 19\, 2025 \n					\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n					\n\n\n\n\n	\n		\n		\n      		\n	            \n                \n                    \n\n                    \n                    \n                                                \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                \n                                                                                                                                \n                                                                                                                            \n                                                                                                                                                                                                                        \n                                                                                                                                                                                                                                    \n                                                                            \n                                                                                                                                                                                    \n                        \n                                            \n                    \n                    \n                \n                            \n        \n      		\n		\n		\n		\n	\n	\n\n				\n			\n				\n				\n				\n				\n				Fill out the form to watch this webinar\n			\n				\n				\n				\n				\n				\n			\n				\n				\n			\n		\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Gartner predicted in June 2025 that 40 percent of agentic AI projects would be cancelled by 2027 due to a lack of sufficient controls\, resources or clear objectives. In the same report\, however\, Gartner also predicted that 15 percent of daily work decisions would be made autonomously with the help of agentic AI by 2028.  \nWhat do enterprises do to position themselves to take advantage of agentic AI’s promise?  Executives get excited about the prospects of agentic AI when they hear about its numerous business transformation possibilities. But then they worry about agent-based malware or other new classes of vulnerabilities and attack vectors that are emerging.  \nWhat’s less evident but equally concerning is context scarcity. Despite its name and its popularity with applications builders\, Model Context Protocol doesn’t really do more than connect agentic users and models to data resources. It’s a clever wiring protocol\, but if the quality\, contextualized data agents need to consume for their purposes\, doesn’t exist\, the agents will fail. \nOrganizations will be quick to start using MCP\, and they will worry less about wiring up and prototyping agentic AI applications\, but the problems with data quality and effective\, scalable integration and interoperation remain unsolved. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				This webinar will review the most effective\, timely ways to build and evolve a ready data and knowledge foundation for agentic AI:\n\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						How do organizations use best practices to create contextualized data?  \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						How can a good knowledge graph help with process improvement and identifying the best agentic AI use cases? \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						How do companies harness the power of knowledge engineering and standards-based knowledge graphs?  \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						How do they overcome the organizational challenges that often get in the way of agentic AI success? \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Semantic search enabled in Microsoft Teams documents \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Microsoft Copilot native integration  \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						And much more! \n					\n				\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Watch this webinar to find out more about how to boost your own organization’s data maturity so that successful\, governed AI agent deployments become the norm\, rather than the exception.\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				Watch Now\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n                \n                    \n\n                    \n                    \n                                                                                    Speaker\n                                                                            \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                        \n                                                                                                                                                    Gerald Mann is VP of Presales at Graphwise and a veteran sales engineering leader who helps organizations turn complex\, siloed data into actionable insights using graph\, semantic\, and AI-driven architectures. He is known for making advanced data and analytics concepts clear\, practical\, and tied to real business outcomes for both technical and executive audiences.
URL:https://graphwise.ai/event/webinar-how-to-think-about-agentic-ais-challenges-and-opportunities/
CATEGORIES:On-demand Webinar
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/08/March-25-2025-featured-image.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20250724T200000
DTEND;TZID=Europe/Vienna:20250724T210000
DTSTAMP:20260527T005910
CREATED:20250618T144119Z
LAST-MODIFIED:20260219T120703Z
UID:239479-1753387200-1753390800@graphwise.ai
SUMMARY:Is Your Data Ready for AI?
DESCRIPTION:On-Demand WEBINAR \n			\n				\n				\n				\n				\n				Is Your Data Ready for AI?\n			\n				\n				\n				\n				\n				How to Build a Solid Foundation \n			\n				\n				\n				\n				\n				\n				\n				\n					\n\n\n\n\n	\n		\n		\n      		\n	            \n                \n                    \n\n                    \n                    \n                                                \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                \n                                                                                                                                \n                                                                                                                            \n                                                                                                                                                                                                                        \n                                                                                                                                                                                                                                    \n                                                                            \n                                                                                                                                                                                    \n                        \n                                            \n                    \n                    \n                \n                            \n        \n      		\n		\n		\n		\n	\n	\n\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Fill out the form to watch this webinar\n			\n				\n				\n				\n				\n				\n						\n						\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				As AI adoption continues to accelerate\, the pressure is on IT leaders and data teams to deliver clean\, reliable and scalable data pipelines. At the same time\, building an AI-ready data foundation requires more than just cleaning up tables – it takes the right architecture\, governance and tools. \nWatch this special roundtable webinar that explores proven best practices\, modern architecture strategies\, and new technologies to optimize your data for successful AI deployment. \nThis expert panel dives into: \n\nThe key technical requirements for AI-ready data\nBest practices for data quality\, integration\, and lineage\nArchitectures that support scale: from data lakes to real-time pipelines\nTools and platforms to streamline AI data prep: from ingestion to semantic enrichment\nHow to align infrastructure with business-driven AI initiatives\n\nWhether you’re managing infrastructure\, pipelines\, or platforms\, this session will give you the practical guidance to build a future-proof data environment for AI. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				Watch Now
URL:https://graphwise.ai/event/is-your-data-ready-for-ai-dbta-2025/
CATEGORIES:On-demand Webinar
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/06/Screenshot-2025-06-18-at-16.24.23.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20250716T150000
DTEND;TZID=Europe/Vienna:20250716T160000
DTSTAMP:20260527T005910
CREATED:20250626T110010Z
LAST-MODIFIED:20260225T105804Z
UID:239612-1752678000-1752681600@graphwise.ai
SUMMARY:Graph RAG - Why Your RAG Needs a Graph
DESCRIPTION:On-Demand WEBINAR \n			\n				\n				\n				\n				\n				Graph RAG – Why Your RAG Needs a Graph\n			\n				\n				\n				\n				\n				Unifying Structured and Unstructured Data in Graph to Give Context \n			\n				\n				\n				\n				\n				\n					\n					\n						\n						July 16\, 2025 \n					\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n					\n\n\n\n\n	\n		\n		\n      		\n	            \n                \n                    \n\n                    \n                    \n                                                \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                \n                                                                                                                                \n                                                                                                                            \n                                                                                                                                                                                                                        \n                                                                                                                                                                                                                                    \n                                                                            \n                                                                                                                                                                                    \n                        \n                                            \n                    \n                    \n                \n                            \n        \n      		\n		\n		\n		\n	\n	\n\n				\n			\n				\n				\n				\n				\n				Fill out the form to watch this webinar\n			\n				\n				\n				\n				\n				\n			\n				\n				\n			\n		\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Chunk Is Dead\, Long Live the Graph RAG! \nAs AI applications increasingly rely on large language models (LLMs) for search\, summarization\, and decision support\, one major limitation persists: traditional Retrieval-Augmented Generation (RAG) systems often treat knowledge as disconnected chunks of text\, missing the deeper context behind relationships. But what if we could connect the dots more intelligently? \nSmarter Retrieval for Smarter AI \nIn this on-demand webinar\, we introduce a graph-based approach to RAG that leverages the power of knowledge graphs to represent meaning more holistically. By structuring information as a web of semantic relationships\, this method enables LLMs to retrieve and generate content that is not only more accurate but also more contextually aware. \nWatch Márcia R. Ferreira and Astrid Krickl\, Data and Knowledge Engineers at Graphwise\, as they walk through the Graphwise Graph RAG framework—an innovative architecture that enhances semantic retrieval using graph-connected data. Through real-world use cases and the Graphwise platform\, they’ll demonstrate how this approach bridges gaps left by chunk-based methods and discuss practical implementation challenges often overlooked in AI pipelines. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Discover these key takeaways:\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Knowledge Graphs are Everywhere: Fortune 500 companies are using them\, are you? \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Graph vs Knowledge Graph: Learn what differentiates a Knowledge Graph from a regular Graph. \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Enterprise Structure: Find out the secret recipe for Knowledge Graphs and LLMs in an enterprise.  \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Vector and Graph: What are the differences and benefits of vector-based RAG and a graph-based RAG approach? \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						And much more!\n \n					\n				\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Whether you’re designing search systems\, building intelligent assistants\, or architecting AI solutions\, this webinar will give you a fresh perspective on integrating structured knowledge into modern workflows.\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				WATCH NOW\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n                \n                    \n\n                    \n                    \n                                                                                    Speaker\n                                                                            \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                        \n                                                                                                                                                    Gerald Mann is VP of Presales at Graphwise and a veteran sales engineering leader who helps organizations turn complex\, siloed data into actionable insights using graph\, semantic\, and AI-driven architectures. He is known for making advanced data and analytics concepts clear\, practical\, and tied to real business outcomes for both technical and executive audiences.
URL:https://graphwise.ai/event/webinar-graph-rag-why-your-rag-needs-a-graph/
LOCATION:Online
CATEGORIES:On-demand Webinar
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/07/WebFeatImg_WhyGraphNeedRag_16172025.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250623
DTEND;VALUE=DATE:20250628
DTSTAMP:20260527T005910
CREATED:20250618T130328Z
LAST-MODIFIED:20250618T130329Z
UID:164350-1750636800-1751068799@graphwise.ai
SUMMARY:Microsoft 365\, Data & Power Platform Conference
DESCRIPTION:The ultimate gathering for Microsoft technology professionals and innovators! Held in the vibrant city of Seattle\, our event brings together three specialized conferences—TechCon 365\, PWRCON\, and DATACON—each offering deep\, targeted insights into key areas of the Microsoft ecosystem. Attendees have the unique flexibility to mix and match sessions across all three events\, crafting a personalized agenda that fits their goals. \nTechCon 365TechCon 365 is your go-to conference for everything Microsoft 365. Designed to boost workplace productivity and collaboration\, it offers expert-led sessions on tools like Microsoft Teams\, SharePoint\, OneDrive\, Loop\, OneNote\, and Copilot. Discover how to create a seamless digital workplace that enhances communication\, engagement\, and teamwork. \nPWRCONPWRCON dives deep into the Microsoft Power Platform\, empowering both citizen developers and IT professionals to streamline and innovate business processes. Learn how to build impactful solutions with Power BI\, Power Apps\, Power Automate\, Power Pages\, and Copilot Studio—no coding required. \nDATACONDATACON is tailored for data professionals and analysts who want to harness the full potential of Microsoft Azure’s data capabilities. Key topics include Azure SQL\, data warehousing\, Microsoft Fabric\, and advanced analytics. Gain the skills to turn complex data into actionable insights that drive smarter decisions. \nWhat you can expect from these conferences: \n\nIn-depth technical sessions: Tailored for all experience levels.\nHands-on workshops: Gain practical knowledge through interactive demos.\nNetworking opportunities: Connect with peers and thought leaders.\nLatest technologies: Stay ahead with cutting-edge Microsoft tools and best practices.\nReal-world solutions: Apply what you learn immediately in your organization\n\n  \n			\n				register now
URL:https://graphwise.ai/event/microsoft-365-data-power-platform-seattle-2025/
LOCATION:Seattle Convention Center\, 900 Pine Street - Summit Building\, Seattle\, WA\, 98101-2350\, United States
CATEGORIES:Event
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/05/TechCon365Seattle_2025_img1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250623
DTEND;VALUE=DATE:20250625
DTSTAMP:20260527T005910
CREATED:20250618T140529Z
LAST-MODIFIED:20250618T140936Z
UID:239443-1750636800-1750809599@graphwise.ai
SUMMARY:Knowledge Summit Dublin
DESCRIPTION:Join a dynamic community of CKOs\, CIOs\, IT professionals\, knowledge managers\, content and records managers\, learning professionals\, researchers\, and educators—anyone passionate about building knowledge-centric organizations. \nAt Knowledge Summit Dublin\, you’ll hear from a world-class lineup of global experts sharing how to harness AI\, knowledge management\, and the human experience to drive smarter\, more connected organizations. \nSet in Dublin—a city rich in literary heritage and now a thriving digital and business hub—this summit offers the perfect backdrop for meaningful conversations\, collaboration\, and co-creation of new knowledge. \nExperience our innovative ‘flipped’ conference format\, designed to foster dialogue over decks. With fewer slides and more interaction\, we prioritize the exchange of tacit knowledge in an environment curated by practitioners\, for practitioners. \nExtend the learning beyond the main sessions with our after-hours knowledge exchange. Don’t miss the immersive ancient knowledge experience\, followed by insightful conversations in the same historic pubs once frequented by literary greats like Joyce\, Wilde\, Beckett\, and Yeats. \n			\n				register now
URL:https://graphwise.ai/event/knowledge-summit-dublin-2025/
LOCATION:Trinity College Dublin\, College Green\, Dublin 2\, Ireland
CATEGORIES:Event
ATTACH;FMTTYPE=image/webp:https://graphwise.ai/wp-content/uploads/2025/06/Screenshot-2025-05-08-at-10.40.34.webp
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250610
DTEND;VALUE=DATE:20250614
DTSTAMP:20260527T005910
CREATED:20250424T122519Z
LAST-MODIFIED:20250521T145510Z
UID:167121-1749513600-1749859199@graphwise.ai
SUMMARY:EVENT: Data Week Leipzig 2025
DESCRIPTION:Join us at Data Week Leipzig\, a premier networking event that delves into the multifaceted world of data from scientific\, economic\, and social angles. Engage in meaningful dialogues with leaders from government\, industry\, academia\, and business.\n\nWe invite you to Leipzig for a week brimming with enlightening sessions\, where the forefront of digital city innovations and artificial intelligence will be unveiled. With a special emphasis on climate and energy\, seize the chance to participate in hands-on training and workshops. A dedicated day on semantics and AI will reveal how these cutting-edge technologies are shaping a sustainable and resilient future.\n\nBe sure to stop by the Graphwise booth and connect with Márcia R. Ferreira\, Senior Data Engineer and Technical Consultant\, and Michael Sikic\, Senior Channel Marketing Manager!\n			\n				register now
URL:https://graphwise.ai/event/data-week-leipzig-2025/
LOCATION:Leipzig Neues Rathaus/City Hall\, Martin-Luther-Ring 4-6\, Leipzig\, 04109\, Germany
CATEGORIES:Event
ATTACH;FMTTYPE=image/jpeg:https://graphwise.ai/wp-content/uploads/2025/04/241114_Twitter-Save-the-date_engl-1440x820-1.jpg
ORGANIZER;CN="Eccenca":MAILTO:info@eccenca.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Vienna:20250521T160000
DTEND;TZID=Europe/Vienna:20250521T170000
DTSTAMP:20260527T005910
CREATED:20250425T162701Z
LAST-MODIFIED:20260219T125010Z
UID:167179-1747843200-1747846800@graphwise.ai
SUMMARY:Streamline ESG Reporting with AI
DESCRIPTION:On-Demand WEBINAR \n			\n				\n				\n				\n				\n				Streamline ESG Reporting with AI\n			\n				\n				\n				\n				\n				A Deep Dive into Recomentor by Graphwise \n			\n				\n				\n				\n				\n				\n					\n					\n						\n						May 21\, 2025 \n					\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n					\n\n\n\n\n	\n		\n		\n      		\n	            \n                \n                    \n\n                    \n                    \n                                                \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                \n                                                                                                                                \n                                                                                                                            \n                                                                                                                                                                                                                        \n                                                                                                                                                                                                                                    \n                                                                            \n                                                                                                                                                                                    \n                        \n                                            \n                    \n                    \n                \n                            \n        \n      		\n		\n		\n		\n	\n	\n\n				\n			\n				\n				\n				\n				\n				Fill out the form to watch this webinar\n			\n				\n				\n				\n				\n				\n			\n				\n				\n			\n		\n			\n			\n				\n				\n				\n				\n			\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Recomentor\, powered by Graphwise\, is a comprehensive\, AI-driven solution that brings clarity and efficiency to ESG (Environmental\, Social\, and Governance) reporting and compliance. By unifying multiple regulatory frameworks—such as CSRD\, GRI\, and more—into a single\, intuitive interface\, it enables organizations to quickly evaluate how their disclosures align with both legal requirements and industry benchmarks.  \nRecomentor’s unique indicators—covering Coverage\, Specificity\, Ambition\, Risks\, and Opportunities—pinpoint precisely where improvements or deeper exploration may be needed. In parallel\, the platform integrates seamlessly with the ESG Knowledge Hub\, a low-hallucination chatbot (Knowledge-hub.eco) that provides transparent\, source-traceable ESG insights. \nThis powerful combination supports a wide range of stakeholders\, including sustainability teams\, ESG consultants\, and financial institutions\, driving faster compliance checks\, richer peer benchmarking\, and more informed\, data-driven decisions. With Recomentor’s assistance\, users can meaningfully elevate their ESG reporting while navigating a rapidly evolving global regulatory landscape. \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Discover these key takeways:\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Unified ESG Landscape: Simplifies working with multiple frameworks like CSRD and GRI under one roof. \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Advanced Indicators: Identifies gaps and opportunities via Coverage\, Specificity\, Ambition\, Risks\, and Opportunities metrics. \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						AI-Powered Efficiency: Automates data analysis and reporting\, freeing resources for strategic ESG decision-making. \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Low-Hallucination Chatbot: Integrates with Knowledge-hub.eco for reliable\, traceable ESG insights and streamlined user support. \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						Broad Applicability: Supports sustainability teams\, consultants\, and financial institutions aiming to foster compliance and innovation across diverse industries. \n					\n				\n			\n				\n				\n				\n				\n				\n					\n					\n						\n						And much more! \n					\n				\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Watch now to be among the first to learn about Recomentor by Graphwise! \n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				Watch the webinar\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n                \n                    \n\n                    \n                    \n                                                                                    Speaker\n                                                                            \n                        \n                                                                                                                                    \n                                                                                                                        \n                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                    \n                                                                                                                                                                                    \n                                                                    \n                                                                                                                                                                                                                                                                                                                                                                                                                            \n                                                                                                                                    \n                                                            \n                                                            \n                                                                Gerald Mann                                                                                                                                                                                                        \n                                                                                                                                                    Gerald Mann is VP of Presales at Graphwise and a veteran sales engineering leader who helps organizations turn complex\, siloed data into actionable insights using graph\, semantic\, and AI-driven architectures. He is known for making advanced data and analytics concepts clear\, practical\, and tied to real business outcomes for both technical and executive audiences.
URL:https://graphwise.ai/event/webinar-streamline-esg-reporting-ai/
CATEGORIES:On-demand Webinar
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/04/Webinar-may-21-2025-streamline-esg-ai.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250514
DTEND;VALUE=DATE:20250516
DTSTAMP:20260527T005910
CREATED:20250424T120611Z
LAST-MODIFIED:20250521T145851Z
UID:167110-1747180800-1747353599@graphwise.ai
SUMMARY:EVENT: Data Summit Boston 2025
DESCRIPTION:At Data Summit 2025\, you’ll discover groundbreaking strategies from the world’s top companies as they tackle the most pressing challenges in data management today. Whether you’re fascinated by the technical intricacies of cutting-edge technologies or keen on leveraging Big Data for business intelligence and analytics\, Data Summit 2025 is your gateway to innovation!\n\nThis event also features three exclusive colocated experiences. Dive into the AI & Machine Learning Summit for a 2-day deep dive into real-world AI applications\, overcoming common hurdles\, and mastering essential technologies.\n\nExpect to leave Data Summit 2025 with a network of new connections and allies\, along with actionable strategies to propel your business forward. Secure your spot now and join us in Boston this May for an opportunity that could redefine your career and organization!\n\nFor more information and to register for the event\, please visit Data Summit Boston 2025.\n			\n				register now
URL:https://graphwise.ai/event/data-summit-boston-2025/
LOCATION:Hyatt Regency Boston\, One Avenue de Lafayette\, Boston\, MA\, 02111\, United States
CATEGORIES:Event
ATTACH;FMTTYPE=image/jpeg:https://graphwise.ai/wp-content/uploads/2025/04/DS25_OG-Website_1200x630_c1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250514
DTEND;VALUE=DATE:20250516
DTSTAMP:20260527T005910
CREATED:20250321T141351Z
LAST-MODIFIED:20250521T145931Z
UID:165490-1747180800-1747353599@graphwise.ai
SUMMARY:EVENT: World AI Technology Expo 2025
DESCRIPTION:Join us at the World AI Technology Expo\, taking place from May 14-15\, 2025\, in lavish Dubai\, UAE. Boasting to be the largest and most comprehensive AI Show & AI Conference globally\, offering an unparalleled platform for innovation and collaboration for businesses in the AI industry\, you won’t want to miss it! \nQuick Facts about the World AI Technology Expo: \n\nConnect directly with AI leaders from over 20 countries.\n50+ speakers from the world’s top AI companies.\nSession in industry-specific AI\, including healthcare\, finance\, and e-commerce. \nAn elaborate awards ceremony and gala evening highlighting over 10\,000 brands in AI and technology.\n\nMake sure to visit the Graphwise booth and connect with our on-site team\, including Andreas Blumauer\, SVP Growth\, and Andrew Frei\, Regional Sales Director Northern Europe & the Middle East. \nFor more information and to register for the event\, please visit World AI Technology Expo. \n			\n				register now
URL:https://graphwise.ai/event/world-ai-technology-expo-2025/
LOCATION:Movenpick Grand Albustan Hotel Dubai\, 51st Street & - Casablanca St\, Dubai\, Al Garhoud\, United Arab Emirates
CATEGORIES:Event
ATTACH;FMTTYPE=image/png:https://graphwise.ai/wp-content/uploads/2025/03/World-AI-Tech-Expo-Dubai-2025-Feature-Image-1.png
END:VEVENT
END:VCALENDAR