Engineering for AI that has to work on Monday morning.
Every engagement starts with the outcome, not the technology. If a simpler fix will do, I will tell you. If AI is the right answer, it is built with security, governance and a person in control.
AI strategy and governance
Decide where AI will genuinely pay off, set the rules it has to follow, and give leaders and auditors the evidence they need. Practical, not a slide deck that sits on a shelf.
Typical work
- AI readiness and opportunity assessment
- Acceptable-use and AI governance policy
- Risk assessments and DPIA support
- Vendor and tool evaluation
- Prioritised, costed roadmap
What you get
- A written report your board can act on
- Policies ready to adopt
- A shortlist of quick wins with costs
- Clear ownership and controls
AI solutions and agents
Put AI to work on jobs that are repetitive but need judgement: reading documents, answering questions, routing work, taking action in other systems. Every tool logs what it did and keeps a person in the loop where it matters.
Typical work
- Assistants grounded in your policies, contracts or knowledge base
- Extraction from invoices, forms and reports
- Triage and drafting for inboxes and service desks
- Agents that update records through APIs
What you get
- A working system tested on your real examples
- Evaluation results you can see
- Audit log and human review steps
- Notes on data flows and model choices
Applications and integration
Focused web applications that replace fragile processes, and the integration work that connects them to the platforms you already rely on. One place to look instead of five. The Core platform is the proof.
Typical work
- Internal tools, booking, quoting and case management
- Customer, partner and supplier portals
- Integrations with CRM, ERP, finance and HR systems
- Single sign-on and role-based access
What you get
- A live application on infrastructure you own
- Source code, documentation and runbooks
- Automated tests and deployment
- Post-launch fixes included
Data platforms and analytics
AI is only as good as the data beneath it. I bring scattered data into one trustworthy place, then build the pipelines, models and dashboards on top.
Typical work
- Unifying spreadsheets and system exports
- Automated data pipelines and warehousing
- Executive, operational and financial dashboards
- Data quality, migration and clean-up
What you get
- Clean, documented data you can rely on
- Reports that refresh themselves
- A plain-English guide to every measure
- Data protection considered throughout
However we work together
Prices agreed before work starts. Changes are quoted, never sprung on you.
You see real progress every week and can steer as we go.
Infrastructure, code and data live in accounts you own and control.
If something is not worth building, I will say so, whatever the budget.
Not sure where to start?
Most engagements combine two or more of these. A discovery call is the quickest way to find the right shape.