AI Governance

AI you can use.
AI you can trust.

AI adoption is accelerating faster than most organizations' ability to govern it. We help turn principles and regulatory requirements into practical processes, controls and accountability, so you can move from experimentation to governed AI without slowing down the work that matters.

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Governance is a practice, not a document.

Most governance work starts with real care behind it. It tends to lose momentum when the resulting policy ends up sitting apart from the systems it describes and the teams building them. We aim for the opposite: governance that lives inside how systems get built and decisions get taken, so it keeps holding as things change.

Assess

Understand your AI landscape, use cases and risk exposure.

Govern

Define policies, roles, risk classifications and controls.

Implement

Embed governance into technology, workflows and decisions.

Monitor

Continuously evaluate systems, risks and changing requirements.

Frameworks we work with.

Your counsel interprets the regulation. We build what it requires into the system: risk classification, controls, documentation trails, human oversight and monitoring that live in the product rather than in a policy document.

EU AI Act: The EU's risk-tiered rulebook for AI systems, with obligations that scale to how much a system can affect people.
NIST AI RMF: A US framework for identifying and managing AI risk across an AI system's lifecycle.
ISO/IEC 42001: The international management-system standard for running AI responsibly across an organization.
Responsible AI: The practical principles underneath all of the above: fairness, transparency, accountability, and human oversight.

Not sure where your AI risk actually sits?

That's usually the right place to start. Let's talk through what you're already using and what governing it well would actually look like.