​Context graphs as the control plane for the agentic enterprise, Dave Bennett, Indykite

Indykite proposes using context graphs as a dynamic control plane to solve the fragmentation and security risks of multi-agent systems in the enterprise. By decoupling agent intelligence from governance, organizations can update their AI models without rebuilding their entire policy framework. Unlike traditional knowledge graphs that only store static facts, context graphs incorporate provenance, temporal validity, and decision tracing. This allows every action an agent takes to be materialized in the graph, making it possible to query exactly why and how a specific decision was made.

The strategy shifts governance from static, role-based labels to Knowledge-Based Access Control (KBAC), which evaluates intent, data sensitivity, and trust signals in real-time. By giving agents formal identities within the graph, Indicite aims to move the enterprise from merely governing data to operationalizing it safely. This centralized approach ensures that as companies scale from a few agents to thousands, they maintain human oversight, identity verification, and fine-grained access control across all internal and external tools.