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.
On February 11, we invite you to join 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.
Mohammad 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:
Case 1: Smarter recipes with domain-aware AI
By grounding generative AI in structured knowledge about products, ingredients, and dietary rules, the customer was able to deliver more personalized recipe recommendations.
Case 2: Turning IoT data into meaningful insights
Sensor data rarely tells the full story on its own. In this use case, knowledge graphs connect sensor readings with external context such as weather conditions, production settings, and energy prices.Â
Whether 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.
​
