Where AI quality is enforced. Not wished upon.

The platform where your evals, observability, and red teaming stop being workflows teams hope to run — and instead controls they can't ship without.

TRUSTED BY 500+ LEADING AI COMPANIES

Evals ran to date[-9,450,988,961+]

How It Works

Turn your standards into enforceable policies.

1. 01

Define organization-wide eval standards.

Translate your standards into controls that can be checked — operational, runtime, and pre-deployment. "Ready to ship" stops being an opinion.

2. 02

Create policies for different AI use cases.

Group controls into a policy you own — not a borrowed framework. Staging and Production each carry their own bar to clear.

3. 03

Enforce it automatically, every day.

Controls re-evaluate across every project on a schedule. Compliance becomes continuous — not a scramble before the next review.

4. 04

See who's compliant, and who's accountable.

One report covers every project, its status, and its owner. Gaps surface early, with a name beside them.

Define Your Controls

Turn what 'good' means into checks — how teams operate, how their app behaves, what must pass to ship.

Bundle Controls Into a Policy

Group controls into a policy you own — one per environment. Staging and Production each get their own bar to clear.

Policies

Enforced Automatically, Every Day

Every control re-runs on every project, every day. Compliance stays continuous, with no one chasing it.

Know Exactly Who's Compliant

A live report per policy — every project, every owner, pass or fail. No hiding.

Testimonials

Trusted by enterprises that enforce AI standards at scale.

Finom

"Before Confident AI, a single improvement cycle took 10 days — I'd create a task, assign it to an engineer, wait for availability, and go back and forth. Now the same cycle takes three hours, and our product managers can run it themselves."

Igor Kolodkin, Head of AI Quality, Finom

"Confident AI saves us 480+ hours of manual AI evaluation every month — and gives us the data to defend every quality decision in front of engineering, product, and leadership."

Anoop Mahajan, Director of QA, Amdocs

"Confident AI gave our team one place to turn production failures into datasets, align metrics, and keep regressions out of releases without waiting on custom engineering work."

SD, Senior Director of Engineering, Fortune 500 medical device company

Humach

"We run a lot of large-scale, multi-turn simulations, and Confident AI made it far easier to design scenarios and execute those tests without piecing together external tools."

Sean Austin, Chief AI Officer, Humach

"Thanks to Confident AI, we were able to move to a fine-tuned model and cut our LLM costs by 80%. This opens up whole new use cases now to generate better output with more targeted LLM calls."

John Lemmon, AI Lead, Supernormal

FAQ

Have a Question?

Checkout our FAQs below, or talk to a human. They won't hallucinate.

What does AI governance actually enforce?

Your standards, on every team. Define the controls a project must satisfy, and no one ships until they're met. Standards become guaranteed, not suggested.

How does governance gate deployments?

Required controls block the release until they pass — then the evidence is recorded automatically. No more shipping on the honor system.

How do you make sure teams set things up correctly?

Governance checks every team daily — evals connected, tracing on, thresholds set. The moment something's misconfigured, you see it.

How is this different from just rolling out a platform?

Handing out a tool and hoping leaves you blind. Governance tracks who actually adopted it, flags who's falling short, and shows leadership exactly where you stand.

What frameworks does it map to?

EU AI Act, NIST AI RMF, ISO/IEC 42001, and your own policies — so compliance gets audit-ready evidence on demand.

More on AI governance

• How RLDatix standardized AI evals enterprise-wide
• LLM safety & AI regulations guide
• Dev, staging & production standards
• What makes a good eval