Independent AI execution governance

Move AI agents
from pilot to
governed production.

Assess agents before release. In production, govern model access, MCP tool calls and agent actions with policy enforcement, human approvals and compliance evidence across supported integrations.

Request a briefing

Starts with read-only discovery
Hosted SaaS, your cloud or data center
Deterministic policy, evaluated beside the agent

Illustrative workflow: an unsafe action is denied on a governed path. Authority is rechecked; human review and any separately permitted action are recorded separately from dispatch.

Write policy once. Enforce it everywhere.

Native controls where a platform has them. Ours where it doesn’t.

See what each surface can carry out

Governance across models, tools and actions

Models and inference

Control model access, inspect inputs and outputs, and apply data policies.

Explore model governance

MCP and tools

Review MCP servers, inspect tool-call arguments, and authorize invocations.

Explore MCP governance

Agent actions

Allow, deny or hold refunds, data transfers and production changes for authorized review.

Explore action governance

Available controls depend on the integration and enforcement path.

Let AI agents act.
Hold the actions that need a human.

Identity, security and tool permission can all pass an action. GovernorAI decides whether this one should proceed.

Inside GovernorAIRecorded demo tenant

GovernorAI

The governance lifecycle, in the product.

Console preview. The video plays on request.

Recorded against a demo tenant with seeded activity.Recording details

A governed refundSample data, runs in your browser

See the policy

policy refunds, version 14 (signed)

allow_support_tools        support.issue_refund is permitted
original_destination_only  any other destination is denied
hold_high_value_refunds    over $10,000 waits for finance-approver;
                           deny where the path cannot hold

Deny wins over hold. Hold wins over allow.

Digest sha256:…

Held for approval

decision_demo_001

Hold

You act as the Finance approver.

Held before dispatch.

The hero and the evidence log follow this decision.

Assurance earns production.
Enforcement governs it.

An agent version is assessed against the policy it will run under before it ships. Once it is live, that same policy decides each consequential action. See assurance

One governance layer
across your AI stack.

One policy model and one evidence schema at every supported enforcement point. Each integration states what it can enforce.

Your policyKeep your Rego and OPA review process, or write native rules.
Your enforcement pathsSidecars, MCP proxies, SDKs and in-tenant SaaS controls. No single provider’s gateway.
Your evidenceGateway records name the policy that decided them.

The refund rule, enforced in three places

Any framework, calling tools over MCPMCP proxyAllow, deny, or hold for approval

An agent on AWS BedrockBedrock inbound pathAllow, deny, or hold for approval

A write in ServiceNowBefore-write rule, before the record commitsAllow or deny. No hold on this path, so this policy denies the write.

All three share one evidence schema and one policy.

Illustrative workflow: an unsafe action is denied on a governed path. Authority is rechecked; human review and any separately permitted action are recorded separately from dispatch.

Capabilities differ by surface, and event-based controls are not inline.

View capability matrix

Govern centrally.
Enforce locally.

Agents chain dozens of tool calls, so governance overhead compounds. GovernorAI evaluates policy in a sidecar beside each agent: the policy files mounted with it, plus a Rego and kill-switch bundle the control plane signs.

When policy changes

Approve
Mount the files, sign the bundle
Sidecar loads and pulls
Verify the bundle signature
Activate

Active policy digest sha256:…

When an agent acts

Intercept the call
Evaluate beside the agent
Allow, deny or hold
Record the decision

Deterministic: policy, evaluated beside the agent
Policy decides: an optional detector can only add a deny
No remote call: for routine policy decisions in sidecar mode

The gateway adapters fail closed when the gateway does not answer. Benchmark method

One policy, from the release gate to the evidence.

One versioned policy is assessed at the release gate and enforced at runtime. Gateway records name the policy that matched, when one did; they do not yet carry its revision.

assetassessed versionpolicydecisionhuman responseevidence

Decide at the action boundary.

Evaluate the action before it takes effect. Allow it, deny it, or hold it for an authorized approver where the integration supports that outcome.

Outcomes vary by enforcement point.

Explore runtime enforcement

Observability spans every stage.No fixed stage order.

“Can your evidence prove that the policy that passed your pre-production gate is the policy that made this decision?”

Today the decision record names the policy and rule that matched, not the revision, so it cannot yet answer that.

Review-ready evidence

Turn every AI decision into evidence your reviewers can trust.

GovernorAI captures the action, policy, verdict and human response as they happen—giving security and compliance teams one record they can verify, export and use in a review.

01 · Governed decisionWhat happened

Not yet verified

Current disposition

Held before dispatch.

HOLD

Ready to verify the event sequence.

02 · Evidence recordWhat reviewers get

Ready to verifydecision_demo_001.json

Decision

Action: support.issue_refund
Amount: $12,400.00
Verdict: HOLD
Dispatch: not_executed

Policy

Policy: refunds
Matched rule: hold_high_value_refunds
Signature: simulated in demo

Human

Required role: finance-approver
Response: pending

Integrity

Events: 3 chained
Head hash: —
Status: not yet verified

Control mapping

NIST AI RMF 1.0all 72 subcategories; 13 backed by live evidencePartial
ISO/IEC 4200132 controls mappedPartial
SOC 2 · HIPAA · PCI DSS · GDPRscored from live stateAssessed
EU AI Act · Colorado SB 26-189programme workspaceAttestation

Sample record, hashed in your browser. A mapping supports review; it is not a certification.Evidence & compliance →

Make compliance part
of execution.

Controls, decisions and evidence come from the same system, so a review starts from records instead of reconstruction.

01
Map requirements to controls
Connect governance requirements to the policies and controls your teams assess.
02
Enforce policies and approvals
Apply policy and authorized review at supported enforcement points.
03
Review and export evidence
Inspect decision records, policy references and human responses for control reviews and audits.

Mapped across eight framework packs, including SOC 2, NIST AI RMF and ISO/IEC 42001, with every control marked automatic, partial or manual attestation. Evidence supports an assessment; it does not confer certification. How evidence is produced

Bring the workflow
you need to trust.

Begin with one action that matters to your business. Define the control, check integration fit, and agree what success looks like.

Money movementRefunds and payoutsSet action limits and require authorized review before a consequential payment proceeds. Sensitive informationData leaving its boundaryDefine permitted destinations and apply supported data controls before information is released. Production systemsChanges with real impactBring agent-driven changes to infrastructure, permissions and records under explicit controls.

For your team: Security, GRC, Platform and AI engineering

Built by people who have
operated at enterprise scale.

Mynul Hoda, Founder, CEO & CTO

Former President of Software & Platform Engineering at Viasat (850+ engineers) and its Executive Sponsor for AI Governance. Dual CCIE (Security), CISSP, Cisco Press author.

Rayaadh Hoda, Co-founder & VP of Engineering

Leads platform engineering, SDKs and developer experience, runtime systems and integrations.

Earlier leadership rolesViasat2TMIBM Public CloudCisco

RecognitionPatent pending: 2 U.S. provisional applications, 66 claimsNVIDIA Inception member

Bring one workflow.
Leave with a plan.

In 30 minutes we’ll map the workflow, check integration fit and agree whether a six-week evaluation makes sense.

Request a briefing

We reply within 48 hours.

Design-partner terms

Engagement: Six weeksAgreed controls targeted by day 30, subject to integration readiness and your approval; decision at week six
Before day one: Security review and accessThe six weeks start after both
Scope: One workflow
Pilot license: Waived for the agreed design-partner scope
Your infrastructure: Customer-funded

Production is priced separately.

The decision demo and evidence log on this page need JavaScript. Everything else — the governance model, the enforcement surfaces and the compliance coverage — is readable without it, and a briefing covers the rest.

Move AI agentsfrom pilot togoverned production.

Governance across models, tools and actions

Models and inference

MCP and tools

Agent actions

Let AI agents act.Hold the actions that need a human.

The recording needs a connection.

Held for approval

Assurance earns production.Enforcement governs it.

One governance layeracross your AI stack.

Govern centrally.Enforce locally.

One policy, from the release gate to the evidence.

Decide at the action boundary.

Held before dispatch.

Decision

Policy

Human

Integrity

Control mapping

Make compliance partof execution.

Map requirements to controls

Enforce policies and approvals

Review and export evidence

Bring the workflowyou need to trust.

Built by people who haveoperated at enterprise scale.

Bring one workflow.Leave with a plan.

Move AI agents
from pilot to
governed production.

Let AI agents act.
Hold the actions that need a human.

Assurance earns production.
Enforcement governs it.

One governance layer
across your AI stack.

Govern centrally.
Enforce locally.

Make compliance part
of execution.

Bring the workflow
you need to trust.

Built by people who have
operated at enterprise scale.

Bring one workflow.
Leave with a plan.