Oconee RuntimeEnterprise AI Governance

AI Agent & Engineering Governance

Govern What AI Actually Does

Oconee Runtime helps organizations govern supported AI-assisted engineering activity using organizational policy and development context.

Text version

What this demo shows: AI engineering governance demo

An AI-assisted engineering action evaluated against repository context and organizational policy — the same action producing a different outcome in a different repository.

AI action
An AI-assisted engineering action is attempted: a command run, a file modified, or a change staged in a repository.
Context evaluated
The evaluation reads the development context — which repository, its sensitivity, and the nature of the action — rather than only the prompt that produced it.
Policy applied
Organizational policy is applied to that action in that context.
Warn or block
In a low-sensitivity scratch repository the developer is warned and keeps moving. The same action in a production or critical repository is blocked. The decision changes because the context does, not because the action does.
Audit evidence
Both outcomes are recorded, so a warned action and a blocked one are equally visible to security afterwards.

AI action
Context evaluated
Policy applied
Warn / Block
Audit evidence

What you get

Governance that understands the action, not just the prompt

Prompt filtering answers what someone typed. Engineering governance answers what the AI is attempting to do, and where.

Action-aware governance
Repository-aware policies
Command and engineering activity controls
Allow / Warn / Block
Centralized audit visibility
Real-time alerts

No sales call required.

Proportional enforcement

Governance proportional to risk

Same AI action. Different repository. The policy decision changes because the context does.

Scratch repository

AI action
→ Policy evaluated

WARN

Low-sensitivity context. The developer is informed and keeps moving.

Production / critical repository

Same AI action
→ Repository sensitivity evaluated

BLOCK

High-sensitivity context. The action is stopped and recorded as evidence.

Blanket blocking gets switched off. Governance that scales with risk gets kept.

See it in your own environment

Install in minutes and watch real AI activity from your own repositories flow into the dashboard.

No sales call required.

Free developer tool

Check your own repository.

Run the free Oconee AI Agent Risk Scanner to identify common AI-agent governance gaps in your own project.

Run the Free Scanner View on GitHub

Install from source

$ git clone https://github.com/oconeesoftware/oconee-scan
$ cd oconee-scan
$ npm install && npm run build
$ node dist/cli/index.js

How coding-agent governance works, in more depth.