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Enterprise AI governance

See Oconee Runtime in 30 Seconds

Text version

What this demo shows: Oconee Runtime in 30 seconds

A short overview of what Oconee Runtime is: governance for AI actions across browser AI tools, coding agents and IDE workflows.

  1. The problem

    AI tools and coding agents already act inside engineering organizations — sending source code to AI tools, exposing credentials, modifying files and invoking external tools — and most organizations have no visibility or control over any of it.

  2. Where Oconee sits

    A browser extension covers browser AI tools; an IDE extension covers VS Code and its forks. Both observe the action being attempted rather than only the text being typed.

  3. What happens to an action

    The action and its context are evaluated against organizational policy, and the result is allow, warn or block.

  4. What security gets

    Every decision becomes a recorded event: the AI activity feed, policy violations with severity, and enforcement logs in a central dashboard.

  • Browser AI
  • Engineering workflows
  • Policy enforcement
  • Centralized visibility

No sales call required.

Full walkthrough

Want the complete walkthrough?

The longer tour of the platform: what Oconee Runtime governs, how policy is applied, and what security sees afterwards.

Text version

What this demo shows: What is Oconee Runtime? — full platform walkthrough

The complete walkthrough: what Oconee Runtime governs, how policy is applied to an AI-assisted action, and what security sees afterwards.

  1. Coverage

    The surfaces Oconee Runtime governs: browser AI tools including ChatGPT, Claude, Gemini and Perplexity, and AI-assisted engineering in VS Code and its forks.

  2. Detection

    What is identified in real time — credentials and API keys, personal and health data, source code and secrets, financial and confidential data, internal repository and infrastructure references, and prompt-injection or unsafe instruction patterns.

  3. Policy

    Organization-wide policies are applied to the detected activity: allow, warn or block, with tool governance and repository sensitivity controls deciding which applies.

  4. Enforcement

    Enforcement in the engineering path covers command execution, file mutation, credential blocking and alerting on high-risk actions.

  5. Visibility

    The dashboard collects the result: an AI activity feed, policy violations with risk severity, session timelines, command detections, repository sensitivity and enforcement logs, with Slack alerting available.

Go deeper

Two specialized demonstrations

Sensitive Data Enforcement

See Oconee detect and govern sensitive AI activity, then record the evidence.

Watch 60-sec Demo

AI Engineering Governance

See Oconee govern higher-risk AI-assisted engineering activity across repositories.

Watch Engineering Demo

Seen enough?

Start on your own, or talk through where this would sit in your environment.

No sales call required.

Related

Where these controls are explained in more depth.