01
Assess
Readiness across data, controls, skills and appetite. We classify candidate use cases by regulatory risk before anyone writes a prompt, so nothing gets built that cannot be deployed.
Advisory & delivery
AI consulting
Artificial intelligence you can put in front of a regulator.
The hard part of artificial intelligence is no longer the model. It is proving the thing is safe, lawful, evidenced and worth the money — and doing that on data you are legally responsible for.
Our AI consulting practice takes organisations from a list of ideas to a small number of AI systems running in production with governance around them. We do the unglamorous work: finding the use cases with real economics, fixing the data foundations underneath, engineering retrieval and evaluation properly, and building the AI governance framework that satisfies your board, your DPO and your customers' due-diligence questionnaires.
We are opinionated about two things. Generative AI belongs behind the same access control and audit trail as any other system that touches personal data. And an AI system without an evaluation harness is a prototype, whatever it is called in the budget line.
Capabilities
What we actually do.
AI strategy & readiness assessment
Where AI actually pays in your operating model, what your data and controls can support today, and the sequence that gets you there. Costed, not aspirational.
Use-case discovery & value modelling
Workshops that turn a long list into a short one — scored on value, feasibility, data availability and regulatory exposure, with a build-or-adopt recommendation on each.
Generative AI & LLM engineering
Production RAG pipelines, agentic workflows, tool use, prompt and context engineering, structured output, and evaluation harnesses with regression tests — not demos.
Data foundations & MLOps
Data quality, lineage, vector and feature stores, model deployment, monitoring, drift detection and cost control across the model lifecycle.
AI governance & assurance
An AI management system aligned to ISO/IEC 42001, EU AI Act risk classification and obligations, DPIAs for AI processing, model cards, human-oversight design and an AI use register.
AI security & red-teaming
Threat modelling against the OWASP Top 10 for LLM applications — prompt injection, data exfiltration through tools, training-data leakage — with adversarial testing and mitigations.
How we work
The shape of an engagement.
02
Prove
One use case to a working, measured pilot — with an evaluation set, a baseline and a cost model. If the numbers do not hold, we say so and stop.
03
Productionise
Engineered into your estate: authentication, authorisation, data residency, logging, monitoring, cost ceilings, fallbacks and a full audit trail on every inference that matters.
04
Govern
The management system that keeps it defensible — policy, use register, risk assessments, human oversight, review cadence and evidence a customer or auditor can be shown.
Platforms & frameworks
What we work with.
Models & platforms
- Anthropic Claude
- Google Gemini & Vertex AI
- OpenAI
- Azure AI Foundry
- Amazon Bedrock
- Open-weight models, self-hosted
Engineering
- Retrieval-augmented generation (RAG)
- Agentic workflows & tool use
- Model Context Protocol (MCP)
- Vector search & embeddings
- Evaluation harnesses & LLM-as-judge
- Fine-tuning & distillation where it pays
Governance frameworks
- ISO/IEC 42001 AI management systems
- EU AI Act risk classification
- NIST AI Risk Management Framework
- UK GDPR Article 22 & DPIAs
- OWASP Top 10 for LLM applications
- ICO guidance on AI and data protection
What you get
- AI readiness and data-maturity assessment
- Scored use-case portfolio with build-or-adopt calls
- Working pilot with an evaluation harness
- Production reference architecture
- AI governance framework and use register
- DPIA and AI risk assessments
Who we work with
- Financial services & fintech
- Legal & professional services
- Property & lettings
- Healthcare & life sciences
- Recruitment & staffing
- Public sector & not-for-profit
Not on the list? The constraint we design to is regulatory exposure, not sector — talk to us about yours.
Common questions
Questions we get asked.
Can we use generative AI on personal or client data lawfully?
Usually, with the right architecture. It turns on lawful basis, transparency, data residency, retention and whether the provider trains on your inputs. We assess those first and design the deployment so the answer is documented rather than assumed. We give practical design guidance, not legal advice.
Do we need to comply with the EU AI Act?
If you place an AI system on the EU market or its output is used in the EU, likely yes — and obligations depend on the risk class. We classify your use cases and map the obligations that follow so you can plan against a real list.
Will you build it, or just advise?
Either. We are a software house first, so we can take a use case from assessment through to a production system your team owns — or hand over an architecture and governance pack and stay advisory.
How do you stop a model from making things up?
You constrain it and you measure it: grounded retrieval with citations, structured outputs, tool use instead of recall, refusal paths, human oversight on consequential decisions, and an evaluation suite run on every change.
Related practices
- Technology & solution consulting
Architecture that holds when the load and the auditor arrive.
- Business consulting
Strategy that survives contact with your operating model.
- Security audits & ISO lead auditor services
Audits led by a certified ISO/IEC 27001 Lead Auditor — findings you can act on, evidence you can show.
Products that carry this
- Skyie Vault
Encrypted document storage with keys that stay on UK soil.
- VerifyFlow
Right-to-work, KYC and AML checks that clear in minutes, not days.
- Trustiey
Vendor trust and compliance posture, continuously evidenced.
Ready when you are
Start with a conversation, not a proposal.
Thirty focused minutes. Tell us the problem and the constraints, and we will tell you honestly whether we are the right people for it.