Why You Need a Context Graph

Everyone is talking about connectors, MCP, and real-time access to enterprise apps – but is that enough to power trustworthy enterprise AI? 

In this webinar, you’ll see where federated approaches break down – from inconsistent API responses and fragmented ranking to weakest-link filtering and limited context – and why a permissions-aware enterprise graph preserves relationships, understands processes, and makes it possible for enterprise AI to take on real work.

We’ll also explore why this matters even more in the age of AI agents, where enterprises need to give more work over to agents that can follow the same process flows, understand the judgment calls, and personalize how work happens across the organization.

‍What you will learn:

• Why federated approaches fall short in quality, context depth, and token efficiency
• How to build a context graph that gives AI the relationships, process flows, and judgment to reason and act reliably at scale
• Why agents built on an enterprise graph can take on real end-to-end work, not just query tools
• What to look for when evaluating enterprise AI platforms on indexing, ranking, permissions, and governance

If you want to understand what separates a federated connector strategy from a real foundation for enterprise AI, this session is for you.

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