Prove your AI controls are working — with evidence, not promises

Turn policy into enforceable controls, validate them under real attack paths, and export an Evidence Pack whenever Security, Legal, or an auditor asks for it.

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Launch blocked pending Security/Legal sign-off

Audit asks for evidence of AI controls

Procurement needs an AI risk attestation

Three things you need to make compliance real

Most AI compliance is a spreadsheet that proves nothing. Enkrypt AI makes it provable.

The Evidence Pack - one forwardable artifact

Everything Security, Legal, and auditors need to sign off — generated from real controls, real validation, and real runtime decisions.

Executive Summary

Top-line risk posture, open items, and approval status for leadership review

Control Inventory

Every control with owner, scope, policy ID, and enforcement status

Coverage Report

Which controls are validated (red team) and enforced (runtime) and which aren't

Runtime Receipts

Allow/block/modify/escalate decisions with policy ID, reason code, and trace ID

Approval Records

Who approved what, when, and under which policy version

Exception Register

Open risks accepted with justification, owner, and review date

Why Enkrypt AI

Most compliance tools generate paperwork. Enkrypt AI generates evidence from real controls enforced under real attack paths.

Red-team validated controls

Controls aren't just documented — they're tested under adversarial conditions and pinned as regressions that run with every release.

Agent + MCP governance built in

MCP Scanner and Gateway enforce allowlists, approvals, and traceability exactly where audit coverage matters most.

Receipts, not dashboards

Every enforcement decision exports with policy ID, reason code, and trace ID — structured for auditors, not just for monitoring screens.

How teams use it

Whether you're unblocking a launch, surviving an audit, or gating releases — same platform, same evidence.

Built on five Enkrypt AI products

Each product handles one part of the compliance pipeline. Together, they produce the Evidence Pack.

Policy Engine

Governance

PDFs → controls with policy IDs

Red Teaming

Pre-launch

Validate controls, pin regressions

Guardrails

Runtime

Enforce at runtime, generate receipts

MCP Scanner + Gateway

Tools

Govern tool access with audit trails

Data Risk Audit

Data

Approve data sources by policy

Integrations

Compliance evidence and alerts flow into the tools your GRC, security, and engineering teams already use.

Approvals

Jira
ServiceNow

Security

Splunk/ Sentinel/ Datadog
Webhooks

Alerts

Slack
Teams

Exports

JSON/CSV evidence for reviews and retention

Frequently Asked Questions

Is this just documentation?

No. Evidence is generated from adversarial red-team validation and runtime enforcement decisions — each tied to a policy ID and control ID. It's proof that controls work, not a claim that they exist.

Can we bring our own policies and regulation PDFs?

Yes. Import internal policies or regulation PDFs and Enkrypt AI converts them into versioned controls with owners, approvals, and enforcement intent. You maintain full control over what your control map looks like.

How do you prove continuous compliance as things change?

Pinned regressions re-run with every release — whenever prompts, models, tools, or data change. Evidence Packs are exportable by system, tenant, business unit, or release at any time.

Does this cover PII, PHI, PCI, and data minimization?

Yes. Controls can cover detection, redaction, minimization, retention, and escalation for sensitive data types. Red teaming validates that these controls hold under adversarial conditions.

How do we get started?

Pick one high-impact system — an agent, RAG app, or MCP deployment. Import your policy, generate the control map, validate via red teaming, and export your first Evidence Pack. Most teams have this done in under 30 days.

Make AI compliance provable — with controls and evidence that update as you ship.