Runtime governance
for autonomous AI agents.
A policy enforcement layer that sits between your agent framework and the actions it takes, before they execute. Deterministic. Sub-millisecond. Built for production.
The Problem
Safety today is probabilistic. It should not be.
85%
USE AI AGENTS IN PRODUCTION
The majority of organizations have already deployed AI agents into production. The question is not whether agents are in your systems, but whether you can see them.
68%
CANNOT DISTINGUISH AGENT FROM HUMAN
Most organizations cannot confidently tell whether an action was taken by a human or an AI agent. If you cannot see the actor, you cannot govern the action.
74%
AGENTS GET MORE ACCESS THAN NEEDED
The vast majority of agents operate with more permissions than their tasks require. The principle of least privilege is not being applied to machine identities.
22%
APPLY IDENTITY GOVERNANCE
Only a small fraction of organizations apply proper access and identity governance to AI agents. The gap between deployment and security is widening.
McKinsey State of AI 2025 / Cloud Security Alliance & Aembit 2026
The Platform
One governance layer.
Six modules.
Policy Engine
Evaluate every tool call, resource access, and inter-agent message against policy before execution. Sub-millisecond. Deterministic.
Zero-Trust Identity
Enforce cryptographic credentials, continuous trust scoring, and strict delegation limits on every actor. Spoofing and escalation have real defenses.
Execution Supervision
Contain failures with privilege rings, resource limits, and kill switches. Recover cleanly through saga orchestration with automatic compensation.
Agent Reliability
Apply SLOs, error budgets, circuit breakers, and chaos engineering to agent fleets. Debug with replay. Recover with precision.
MCP Security Scanner
Scan MCP definitions for poisoning, typosquatting, and embedded directives. Verify third-party tools before they touch your agents.
Governance Visibility
Surface shadow agents, manage full lifecycles from provision through decommission, and maintain operational awareness through real-time dashboards.
How It Works
Check every action before it runs.
Ophanix evaluates each agent action in under 0.1 ms — fast enough that you will not notice it, thorough enough that you can trust it.
01
INTERCEPT
Capture every tool call, resource access, and inter-agent message at the framework boundary. Before execution. Before exposure.
02
EVALUATE
Check each action against policy in real time. Deterministic outcomes. No variance. No exceptions.
03
ENFORCE
Allow legitimate actions to proceed. Block unauthorized requests with full reasoning and complete audit context.
04
AUDIT
Log every decision with agent identity, action context, and policy justification. Immutable. Queryable. Complete.
Works With Your Stack
Early Access
Ship agents with
confidence.
We are running interviews with platform engineers, security teams, and SREs. If you are shipping or planning to ship agentic applications, we want to talk.