Products

/

AI governance

Give your AI agents freedom. Keep control of what they do.

AI in production requires governance in every workflow. We provide one control plane for every model, agent and action across your AI Gateway and Software Factory.

Trusted by teams operating AI in production

Capgemini logo
Vattenfall logo
hear logo
bunq logo
Moneybird logo
Yoco logo
Moss logo
Capgemini logo
Vattenfall logo
hear logo
bunq logo
Moneybird logo
Yoco logo
Moss logo
Capgemini logo
Vattenfall logo
hear logo
bunq logo
Moneybird logo
Yoco logo
Moss logo
Capgemini logo
Vattenfall logo
hear logo
bunq logo
Moneybird logo
Yoco logo
Moss logo

3x

Faster to meet compliance standards

100%

Visibility and auditability across every agent and model

10 -

40%

Lower LLM costs

40%

Of AI projects fail without governance

the problem

AI is no longer just generating answers. It is taking action.

We sit on the critical path and see all AI traffic and intervenes in real time. Other governance tools hook up data after the fact and show what happened - when it’s too late.

Agents access internal systems

Connect agents to internal tools and data while enforcing permissions at every request.

Agents operate continuously

Keep agents running safely with real-time controls, monitoring, and human oversight.

Agents make decisions

Let agents act on context within the limits and rules you define.

Agents modify code and deploy software

Let agents edit code and ship changes, with approval gates at every step.

Agents consume infrastructure and tokens

Track and cap resource and token usage to keep costs predictable.

Agents call tools and APIs

Connect agents to external tools and APIs with scoped, per-call permissions.

The more autonomy organizations give AI agents, the more important it becomes to control what they can do, where they can go and when humans must intervene.

Governance in the Execution Layer

Governance that sits where AI actually runs.

Orq.ai controls AI while it operates. Policies, permissions, evaluations, budgets and approval gates are applied directly within the execution path.

human in control

Autonomous does not mean unsupervised.

Software agents can do more work. Humans should still decide when judgment matters. Orq.ai lets organizations define exactly where agents can act autonomously and where human approval is required.

Control Model

Control every dimension of agent execution.

01

What can this agent touch?

Models, tools, MCPs, repositories, databases and environments.

02

What is this agent allowed to do?

03

Is the output good enough to continue?

04

How much can this agent consume?

05

What must never happen?

06

Where does a person need to approve?

Backlog-to-production workflow

01

What can this agent touch?

Models, tools, MCPs, repositories, databases and environments.

02

What is this agent allowed to do?

03

Is the output good enough to continue?

04

How much can this agent consume?

05

What must never happen?

06

Where does a person need to approve?

Backlog-to-production workflow

sovereignty

Coding agents are only the beginning.

Coding agents dramatically increase engineering capacity. Deploying them across teams also creates a new operating challenge:

Who controls the agents?

Orq.ai gives engineering, platform and security teams visibility and control over:

Which agents are approved

Which models they use

What repositories they access

What tools they invoke

How much they spend

What actions require approval

What code reaches production

sovereignty

One governed runtime for enterprise AI.

AI Gateway

Model access

Routing

Security

Policies

Budgets

AI Gateway decor image
Observability & Evaluation decor image

Observability & Evaluation

Model access

Routing

Security

Policies

Budgets

Software Factory

Orchestration

Agents

Human approvals

Execution

Software delivery

Software Factory decor image

Who it’s for

One platform. Different controls.

Engineering & Platform

Give agents more autonomy, with standardized operations.

Finance

Control what AI consumes.

Security image
Security image

Security

Control what agents can access.

Leadership

Know what AI is actually delivering.

Leadership image
Leadership image

Enterprise Capabilities

Built for enterprise AI.

EU sovereign

Fully governed

Model independent

Enterprise security

Complete observability

Enterprise Capabilities decor image

FAQs

What enterprise teams ask us about AI governance

What does AI governance mean in practice?

Knowing which agents are running, what they can access, what they cost, and having a complete record of every decision — enforced on every request, not reported after the fact.

How is Orq.ai different from other governance tools?

Most tools sit outside your AI traffic and analyze data after the fact. Orq sits on the critical path, so policies are enforced before requests reach a model.

What is red teaming for AI agents?

Systematically attacking your own agents to find where they break. Orq’s workbench tests prompt injection, jailbreaking, secrets exfiltration, and system prompt leakage.

What is a compliance registry?

A centrally managed list of approved agents, models, prompts, and MCPs. Teams work from the approved list; anything outside it is blocked by default.

Can I set different policies for different teams?

Yes — at organization, department, team, project, and agent level. Set once, enforced automatically.

Does Orq.ai enable EU AI Act compliance?

Yes. Orq.ai provides capabilities for EU AI Act, GDPR, ISO 27001, and SOC 2 Type II readiness, including governance, auditability, and policy controls.

Can I deploy Orq.ai on my own infrastructure?

Yes — SaaS, VPC/customer cloud, or fully air-gapped on your own servers.

The autonomous enterprise needs a control plane.

AI agents will write code, operate systems and increasingly execute work across the enterprise.

We'll provides the control and execution infrastructure organizations need to give those agents more autonomy while remaining in control.