Specialist practice

AI governance & assurance

As AI regulation lands, someone has to prove your systems are safe, fair and accountable. We make your AI audit-ready — and keep it that way.

Why now

Everyone shipped AI. Almost no one can prove it's safe.

New rules — the EU AI Act, sector guidance and disclosure requirements — are turning “trust us” into a liability. Governance isn't optional anymore, and a model can't certify itself. That accountability needs a human, and the evidence needs an engineer.

What we build

Governance that's real, not theatre

Practical controls and evidence — implemented in your stack, owned by accountable people.

AI audits & risk assessment

Independent review of your models, data and pipelines — mapping risk, bias and failure modes before regulators or incidents do.

Model documentation

Model cards, data lineage and decision records that prove how a system was built, trained and validated.

Guardrails & policy-as-code

Input/output controls, content safety, access policies and rate limits enforced in code — not in a slide deck.

Evaluation & monitoring

Eval harnesses, regression suites and drift detection so you know your AI is accurate today and stays that way.

Human-in-the-loop controls

Review, escalation and override workflows for high-stakes decisions — the accountability regulators require.

Compliance mapping

Controls aligned to the EU AI Act, sector rules, SOC 2, HIPAA and GDPR — with the evidence to back them up.

Our framework

Assess. Document. Control. Monitor.

A repeatable assurance lifecycle that turns a pile of AI experiments into a governed, defensible program — with the paper trail to prove it.

  • Security-first, zero-trust engineering discipline
  • Independent assurance — we test what others ship
  • Controls implemented as code, not paperwork
  • Open-source-focused, no black-box tooling
Governed AI in our own products: Sarvyn — grounded, cited, access-scoped
01

Assess

Inventory AI systems, classify risk and surface gaps against the rules that apply to you.

02

Document

Produce model cards, data lineage and audit trails that stand up to external review.

03

Control

Implement guardrails, evals and human-in-the-loop checkpoints as enforceable code.

04

Monitor

Continuously watch for drift, abuse and policy violations — and report on them.

Who needs this

For the teams who answer to regulators

When AI decisions carry legal or financial weight, assurance is the cost of doing business.

Financial services

Model risk, fair-lending and regulator-ready evidence.

Healthcare

Safe, documented clinical and operational AI under HIPAA.

Public sector & enterprise

EU AI Act readiness and board-level accountability.

Is your AI ready for an audit?

We'll assess where you stand and build the controls and evidence to close the gap.