See how AI is used.
Govern what happens next.
Deploy endpoint and browser controls to discover Shadow AI and browser-based agent activity across your organization. Define acceptable use, detect policy violations, and block high-risk activity without retaining sensitive prompts by default.
From visibility to governance
Deploy
Install the Shadow AI endpoint agent and browser extension through your existing device-management tools.
Discover
Identify AI tools, browser-based usage, and the users or processes involved.
Define policy
Create an AI acceptable-use policy, classify tools by risk, and define approved, restricted, and prohibited use cases.
Govern
Alert, investigate, or block activity that violates your policy. Keep routine telemetry metadata-first and escalate payload evidence only when policy requires it.
Explain the controls clearly
| Capability | What it does |
|---|---|
| Endpoint agent | Uses OS-level telemetry to identify DNS activity, process context, device attribution, and related evidence |
| Browser extension | Observes supported browser interactions before encryption and can apply browser-level policy controls |
| Policy engine | Maps tools, users, behaviors, and data classifications to approved or prohibited use cases |
| Investigation Capsules | Retains policy-triggered evidence securely for a strict 30-day auto-purge period, rather than storing all prompts by default |
| Governance dashboard | Shows discovered tools, users, risks, policies, violations, and enforcement outcomes |
Policy and Enforcement Architecture
Define which AI tools and use cases are approved, restricted, or prohibited. Shadow AI Gov can alert on violations, preserve policy-triggered evidence for investigation, and enforce controls for unwanted use cases where supported.
Shadow AI Gov combines endpoint and browser-level evidence to improve visibility into AI use without relying on TLS interception. Coverage and enforcement depend on the device, browser, application, and policy controls deployed.
Frequently Asked Questions
How do you classify usage without reading our employees' raw data?
Payloads are evaluated locally, in-browser memory, and never leave the device unless a policy violation is triggered — our backend has no access to payload content at all during classification. Our Endpoint Agent relies entirely on metadata (DNS queries, process tracking) mapped against our Tool Registry to classify risk, meaning it never sees TLS-encrypted payloads.
How does the local browser extension detect sensitive payloads like source code?
Currently, we use lightweight, local regex and pattern-matching classifiers to evaluate payloads directly in the browser memory. While effective for catching common patterns (like API keys or source code headers), we recognize regex has limitations. Advanced ML-based local classification is currently on our roadmap to improve accuracy.
How can we independently verify that benign payloads aren't transmitted?
We believe in complete transparency for security teams. We offer extension manifest transparency during due diligence. We are currently scheduling third-party penetration testing and will make the full results available to prospective enterprise customers once completed.
Core Governance Capabilities
Discovery
Identify AI tools, agents, users, and risk patterns.
Governance
Define acceptable-use policy, risk thresholds, investigation workflows, and 30-day retention controls.
Enforcement
Apply browser and endpoint controls to warn, block, or escalate prohibited activity where supported.
Shadow AI Gov helps organizations discover AI use, define acceptable-use policy, and govern or block prohibited activity—while minimizing routine collection of sensitive prompts and payloads.