Faramesh – Deterministic Governance and Control for AI Agent Actions

Summary: Faramesh provides a deterministic governance system for AI agents, enabling policy-based access control, approval workflows, and detailed observability. It addresses the risks of agentic hallucinations by treating agent-to-system interactions as a distributed systems problem rather than relying on prompting.

What it does

Faramesh enforces a stable Action Authorization Boundary using deterministic canonicalization to produce consistent cryptographic hashes from varied LLM outputs, ensuring reliable RBAC, audit trails, and fail-closed security for autonomous agents.

Who it's for

It is designed for teams deploying LLM-based agents with access to critical systems requiring secure, auditable control over agent actions.

Why it matters

It prevents catastrophic failures caused by agent jailbreaks by providing a robust, verifiable control layer between AI agents and system resources.