Enterprise AI has a new cost to consider: tokens. You pay for every answer an LLM gives in the context it has to read. When that context is raw documents, costs climb faster than accuracy does. As GenAI moves from pilot to production, token consumption is turning into one of the clearest signs of whether an AI system can scale.
In the Graphwise Platform Pulse #3, Helmut Nagy, Christian Blaschke and Ben White look at the Graphwise Platform through this lens. They’ll explain why a knowledge graph gives an LLM less to read and more to reason with. Then they’ll show what’s new in the platform:
- Ontology Management: modeling your business logic so enterprise AI works from verified structure, not guesswork
- GraphRAG 2.0: a closer look at how token consumption is measured and kept under control when questions are answered
The session wraps up with a short tour of the full Graphwise Platform 26.3 release, focused on what we haven’t covered yet, and a first look at what’s coming in 27.1.