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AI engineering and AI governance services

Comonad Limited offers two services for AI in production systems. AI engineering builds agent harnesses, quality gates and automation into systems you already run. AI governance decides what those systems may do and writes the controls that show they do it. Many engagements need both, and we scope them separately.

Book an introductory call

Which service do you need?

  • Choose AI engineering if you need an AI feature, agent or automated workflow built into a system that already has users, audit logs and a release process.
  • Choose AI governance if you need to know how an AI system is classified, what controls it needs, and how those controls map to the EU AI Act, UK regulatory guidance, ISO/IEC 42001 or the NIST AI RMF.
  • Choose both if you are building or changing an AI feature and need the build and the control set to agree. Governance defines what the system must satisfy; engineering implements it.

AI governance

We help UK organisations govern AI that is in production or about to be. We classify each system, state what it may and may not do, and write the control set: evaluation, access control, audit trails, human oversight, and model and vendor risk. The outputs are documents and decisions your teams can act on. Legal sign-off stays with your counsel.

For risk, legal and compliance teams who need a regulation or standard mapped onto a real system.

AI governance consultancy

AI engineering and agent harnesses

We design and build the harness around a large language model: orchestration, the tools it may call and with what permissions, evaluation, guardrails, logging and a documented way to switch it off. The work follows your release process and does not require a rewrite of the surrounding application.

For platform and engineering leads putting AI into an existing estate.

AI engineering and agent harnesses

AI-assisted SDLC

We bring AI into the software development lifecycle (SDLC): specification, code generation, review, testing, CI/CD and release, with a quality gate at each step so that generated work is checked before it moves on. A record of which changes were AI-assisted keeps audit and incident review working.

For engineering leaders introducing AI across teams who need gates and evidence on generated work.

AI-assisted SDLC with quality gates

How engagements are scoped

  • Every engagement starts from the system you already operate, or the one you are about to release.
  • Scope is written down first: for engineering, the model, the tools it may call, the evaluation it must pass and what is out of bounds; for governance, the systems in scope and the frameworks that apply.
  • Governance work ends at a written control set and a review of the running system, unless implementation is agreed separately as AI engineering.
  • Your team keeps the tests, runbooks, control lists and the ability to switch the AI feature off.
  • Alex Vakhitov, Comonad's founder, leads every engagement and does the work personally.

Questions about Comonad's services

Which service do we need, AI engineering or AI governance?

Choose AI engineering if you need an AI feature, agent or workflow built into a system you already run. Choose AI governance if you need AI systems classified and a control set mapped to the EU AI Act, UK regulatory guidance, ISO/IEC 42001 or the NIST AI RMF. Many organisations need both; we scope them separately so the build and the control set can each be reviewed.

How are Comonad engagements scoped?

Every engagement starts from the system you operate or are about to release. Before any work begins, the scope is written down: for engineering, the model, the tools it may call, the evaluation it must pass and what is out of bounds; for governance, the systems in scope and the frameworks that apply. Milestones are agreed in writing before any production code is written.

Do you work in regulated sectors?

Yes. The approach is designed for regulated environments: written scope, controls mapped to the EU AI Act, UK regulatory guidance, ISO/IEC 42001 and the NIST AI RMF, evidence your risk team can review, and legal sign-off left with your counsel. Comonad's founder spent almost seven years as co-founder and CTO of Cloud KB, which built software for UK energy-market participants.

Do you replace our platform or engineering team?

No. We work with the team that owns the system, so that they can release, observe and switch off the AI feature without us. Implementation follows your release process, and at handover you keep the tests, the runbooks, the control set and a documented, tested way to disable the AI feature and fall back to the previous behaviour.

Book an introductory call

Tell us about the system and what you want AI to do in it. It can already be in production or about to ship.

Book an introductory call