Team
The people on the call are the people on the work
Each of us leads a discipline, backed by associates we have worked with before. You deal with whoever is doing the work.
Leadership team
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Tom
Founder · AI infrastructure & security lead
Owns the platform build, the hardening and the assurance evidence.
Tom came to AI from software and quality engineering: test automation, device management, security tooling. On an engagement he owns infrastructure and security: the STIG and CIS baselines, the air-gapped artefact pipeline, the NCSC CAF mapping, and the deviation list behind all three. He founded Flowing Mind and still does the work.
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Nigel
Lead architect
Decides where the boundary sits, and what the system looks like either side.
Nigel owns system design: the decisions that are expensive to reverse. Where the data boundary sits, what runs inside it, how models are served and sized against real concurrency. His standing rule: applications talk to an interface you own, never to a model directly, so the model can be swapped without rewriting everything above it.
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Dave
Delivery lead
Runs the engagement: scope, sequence, and the assurance timetable.
Dave has run complex technology delivery in government and large enterprise, mostly multi-supplier programmes from discovery through to post-launch support. AI programmes rarely fail on the model. They fail on sequencing, on decisions taken without the right person in the room, on an assurance gate nobody planned. That half is his: what gets built in what order, and who signs what, when.
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Andy
AI development lead
Leads the build: retrieval, agents, evaluation and the serving stack.
Andy leads the engineering: retrieval over your own material with citations that hold up, agents where the task varies, the inference stack underneath, and the tests that let your team change any of it safely after we leave. The evaluation harness is his too. Without a measured baseline on your own material, nobody can say whether a change helped.
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Tammy
Lead business analyst · AI assistive technology for SEN
Turns the stated requirement into the one that was meant. Specialises in assistive AI for special educational needs.
Tammy runs the analysis: what the process is, where the time goes, and which requests would survive contact with the work. Many proposed AI projects turn out to be a reporting or form design problem. Finding that out in analysis is cheap. In a build, it is not.
She also specialises in AI as assistive technology for special educational needs, where the line between supporting a learner and deciding about them matters enormously, and accessibility and equality impact are the assessment itself.
Associates
Associates we have worked with before
When a job needs more hands, or a specialism the five of us lack, we bring in engineers, analysts and specialists we know.
You are told who they are and what they will do before they start, and one of us stays accountable for their work. We do not put senior names on a proposal and send a stranger to deliver it.
How we staff
Where we stop
If a job needs more capacity than we can field, we say so. Stretching helps nobody.
Some things we do not do: specialist legal advice, clinical safety, sector regulatory work. We bring in someone who does.
On clearance, tell us the level and any facility requirement in the first conversation. We will say straight away whether we meet it, and where we would need to work alongside your own cleared staff.
Next step
Talk to whoever you need
Architecture, ask Nigel. Hardening or an accreditor, ask Tom. Whether it lands by March, ask Dave. Book a call and we will put the right one on it.