Context graphs are emerging as one of the most important structural ideas in enterprise AI.

The recent article by Jaya Gupta and Ashu Garg from Foundation Capital on context graphs crystallizes why: as AI agents move into execution, organizations need a way to preserve decision context over time, so autonomy is grounded in policy, precedent, and the full execution context present at decision time.

This is the critical gap many enterprises are struggling with. Agents work in demo environments or within a single system but are wildly risky in the chaos of cross system deployment. Security, governance and control weren’t built for the agentic AI era.

Enterprises need a way to keep data coherent as it is accessed and used across systems, where data is bound to its context - relationships, provenance, and usage constraints - in a way that provides traceability of all data interactions and decisions.  

This is the missing layer for enterprise AI. Context and decision traceability that can inform not just what happened by why it was allowed.

At IndyKite, we take it one step further – combining context, full provenance, decision precedents with embedded data trust to inform use and enforcement at runtime.

This combination turns trust and context into an operational layer for agentic AI. Context, provenance, and trust are evaluated together, allowing enforcement to reason over the actual conditions under which data is being used and how.

With this in place, autonomy can extend beyond isolated systems into real enterprise environments (chaos and all).  Decisions span data domains and applications while remaining anchored in the same governing conditions, because use and enforcement are resolved against live context and embedded trust, rather than rigid rules and static permissions.

This provides the enabling architecture for agents to securely access and use data, while also being safe and compliant with full decision transparency.

This is the architectural shift that will determine which enterprises can move from experimenting with agents to operating them at scale.

Learn more here: https://www.indykite.ai/indykite-ai