Demo Area

Graphwise helps users to find answers and documents across multiple repositories in a precise way.
Example: Improve help desks and self-service portals to search over regulations or product documentation.

• Provide actionable insights for industries where the stakes are high.
• Benefit from precise GraphRAG and content recommendation services
• See how personalisation based on domain knowledge models works!

This Graph RAG demo is a great example to show when we want to illustrate self-training and self-support use cases. It has a chatbot-like interface which keeps the context of the interaction and provides a quiz to self-test the acquired knowledge

• Graph RAG applied to the technical documentation domain - drink your own champagne scenario!
• The knowledge graph contextualises questions and answers and helps retrieving the relevant documents
• Reduce hallucinations and provide provenance to answers through the recommended documents

A publicly available demo for a flagship customer who makes very heavy use of the automatic tagging capabilities. Valuable for technical documentation domains, automatic tagging (across data silos) or just for the brand name of the customer.

• One-stop-shop for all Microsoft learning content The Knowledge Hub centralises search and access to million of distributed pieces of content maintained by thousands of contributors
• A centralised source of truth Changes to taxonomies managed centrally drastically reducing the time to production, and allowing the creation of complex relations between products
• Automatic tagging of content at-scale Shift from manual tagging of million of pieces of content to an automated approach which enables the growth of the business unit

The GBA thesaurus demonstrates how Graphwise’s core capabilities in managing and bringing together complex knowledge helps a federal agency become a pioneer using linked data in the geospatial sector in the EU.

• Provides users with a bilingual and connected knowledge representation of the geological survey.
• GeoSphere enables its users to explore and traverse their knowledge graph in a visual manner for quick information retrieval and discovery
• The Knowledge Graph is used in geoscientific text publications and geological maps

The perfect synergy between  Custom Taxonomies, Graph and LLM
OTKG transforms content into a strategic asset by structuring it with custom taxonomies and ontologies and thus enabling: seamless content reuse across platforms, LLM-powered search and interaction with content, easy discovery of content gaps through domain knowledge analytics, automated schema.org markup, personalized experiences  and content recommendations.

• Content discovery and efficient information sources retrieval. 
• Tailored navigation and relevant recommendations
• Question-answering and insights through a natural language interface to consume knowledge graph information  in a user-friendly way

Transform business processes such as hiring, talent management and human resources pooling into a dynamic Knowledge Graph, providing a 360-degree view of human resources and enable precise impact analysis and risk quantification of people, skills and projects.

• Deliver precise, data-driven answers to key HR and strategic workforce planning questions.
• Make informed decisions based on real-world skill requirements, compensation patterns, and market trends.
• Suggest relevant candidates based on skills and experience 

The buildingSmart Data Dictionary (bSDD) is an important shared resource in the Architecture, Engineering, Construction, and Operations (AECO) domain. Yet bSDD data is not well-structured, and there is no parity in data retrieved via different APIs. 

Semantic bSDD improves bSDD data quality, usability and validity. Semantic bSDD provides a SPARQL endpoint using  Graphwise GraphDB, and a GraphQL endpoint using Semantic Objects.

• Semantic bSDD enhances the interoperability,  integrity and reliability of bSDD data, making it easier and safer to use in AECO workflows.
• The demo showcases how addressing inconsistencies in structure and content across APIs, bSDD data can be retrieved easier.
• bSDD enables data access through both a SPARQL endpoint and a GraphQL endpoint.

HR Recommender provides an attractive example of an application that takes advantage of connection between concepts i.e. skills and considers implicit relations within families of skills (e.g. programming languages) 

• HR Recommender showcases knowledge graph powered recommendations for the domain of HR
• Employees, positions and projects are semantically profiled for meaningful comparisons and better matching
• The knowledge graph relations enables the on-the-fly recalculation or rankings

With Transparency Energy Knowledge Graph (TEKG) you can explore the world of open electricity data. TEKG integrates part of ENTSO-E Transparency Platform data and showcases how applying Linked Data principles and semantic technology to electricity data can turn fragmented data into a semantically linked, queryable format for better integrated and validated electricity data.

• A Knowledge Graph with electricity data enables the integration between TSOs, DSOs, market participants, and regulators.
• Linked Data supports grid optimization, sustainability tracking, and policy compliance using a common data language.
• Electricity data in a knowledge graph supports the access to cross-border, cross-actor electricity data.