AI Governance & Compliance
Prove your AI is safe, traceable and lawful — before a customer's procurement team or a regulator asks you to.
AI governance is the set of policies, technical controls and evidence that show how an AI system is built, monitored and overseen — so you can demonstrate safety, traceability and legal compliance under frameworks such as the EU AI Act.
The problem
Enterprise buyers and regulated customers are already asking how you govern AI. Many scale-ups answer with a slide deck and a hope that nobody digs into the pipelines. That works until a security questionnaire, a procurement lawyer or a regulator asks for lineage, access control and evaluation history you cannot produce.
Governance bolted on after launch becomes a spreadsheet that drifts from reality. The cost is not only compliance risk — it is lost deals and engineering time spent reconstructing how an output was produced after the fact.
Who this is for
- Seed to Series C companies shipping AI features into products used by customers in the UK or EU.
- Teams facing enterprise procurement, due diligence or sector rules that demand evidence of oversight.
- Founders who need EU AI Act readiness without building a full compliance department.
Outcome
Lineage, access control and compliance evidence that holds up to a regulator or a customer's due diligence.
What the engagement involves
- Week 1–2
Classify and scope
Map each AI use case by role and risk, document intended purpose and known limitations, and agree what “good evidence” means for your buyers and your regulators.
- Week 3–5
Instrument the platform
Wire lineage, access control and evaluation records into the same pipelines that feed production — not a side project — so evidence is a byproduct of how you ship.
- Week 6–8
Monitor and package
Stand up bias and drift checks, define human oversight points, and package artefacts your team can reuse in questionnaires and audits.
What you receive
- A written risk and use-case classification your product and legal teams can maintain.
- Lineage and access patterns implemented in your cloud and repos.
- An evaluation and change log for models, prompts and datasets that matter.
- A readiness pack oriented to EU AI Act obligations and customer due diligence.
Core deliverables
- EU AI Act readiness
- Data lineage & cataloguing
- Bias & drift monitoring
What does EU AI Act readiness involve?
EU AI Act readiness means knowing which of your systems fall under the Act, what risk tier they sit in, and having the documentation and technical controls that tier requires — from transparency duties for limited-risk systems through to risk management, data governance and human oversight for higher-risk uses.
In practice we start with inventory and classification, then close the gaps that block a credible answer to a customer or auditor: lineage, access control, evaluation records and clear ownership.
What is AI governance for a scale-up?
For a scale-up, AI governance is not a binder of policies nobody reads. It is engineering discipline: you can reconstruct how an output was produced, who could change the system, and what you measured before and after a release.
That evidence lives in your platform. Policies exist to describe it — they do not replace it.
Do I need AI governance before I have a large compliance team?
Yes, if you sell to enterprises or operate in regulated spaces. Buyers will not wait for your Series C headcount plan. The work scales with how you build: instrument early and governance stays cheap; retrofit later and every questionnaire becomes an incident.
How is this different from a policy-only consultancy?
We implement controls in your cloud and your repositories. You leave with lineage, access patterns and monitoring you can run — not only a PDF of recommendations.
Not sure this is the right fit?
A 30-minute discovery call is enough for us to tell you honestly whether this is what you need.
Book a discovery call