THE INTENT PLANE
Capture intent.
Govern your agents.Octopi AI
A Kubernetes-native layer that captures agent intent, with reinforcement learning behind every verdict. Ready when fraud, AML, and compliance come asking.
CONTINUOUS MONITORING · AUDIT READY · DESIGNED FOR SOC 2
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AI agent · matches invoices to payments
You launched an AI agent. What is it actually doing?
How the Intent Plane Works
From unknown agents to governed autonomy. Capture intent, lock a baseline, catch every deviation, and decide what happens next.
01 · Capture
A read-only probe deploys into your Kubernetes cluster and reads what every agent is wired with. Models, tools, MCP servers, and permissions all land in an Intent Record before the agent touches anything.


02 · Baseline
The Intent Plane observes real behavior, from the destinations an agent calls to the traffic it sends and the commands it runs. Once normal is clear, your team approves it and the record freezes into a fingerprint.

03 · Detect
Every execution is compared against the baseline in real time. A new destination, a new command, or a changed capability surfaces as a scored deviation event, not a mystery in a log file.
04 · Govern
The gateway enforces the record at the network edge. Requests inside the baseline flow while everything else is intercepted. Your team accepts a deviation as the new normal or ships a fix, and every decision lands in the audit trail.

Empowering AI
in a Digital Frontier.
Kubernetes Native, Zero Code Changes
The Intent Plane installs as a read-only probe and a network gateway inside your cluster. No SDKs, no wrappers, no changes to agent code. Your agents keep shipping while the plane starts learning what they are and what they do.
Two-Level Agent Identity
Every agent carries a lineage that survives restarts and redeploys, plus an incarnation fingerprint that changes when its code, config, or capabilities change. A new version is a new fingerprint, and new fingerprints need your approval before they inherit trust.
Observe First, Enforce When Ready
Nothing is blocked on day one. Agents run in observe mode while their baselines form, and enforcement only turns on when a human approves the record. From that moment the gateway allows what the baseline allows and intercepts everything else.
Deviation Math You Can Read
The deviation score is one honest number, deviating executions divided by total observed executions since the last approved baseline. No opaque risk scores. Anyone on your team can check the math behind every alert.
Every Verdict Makes It Smarter
Accepting a deviation as the new normal or rejecting it and shipping a fix are both labeled examples. Reinforcement learning sits behind every verdict, so the plane gets sharper about your environment with each decision your team makes.
Audit Ready by Design
Every intent capture, baseline approval, deviation, and enforcement decision lands on a timeline. When fraud, AML, or compliance comes asking what an agent did and who allowed it, the answer is already written down. Designed for SOC 2 from the start.





