"They helped us cut invoice processing time from two days to forty minutes. No grand promises — just a working model in production within six weeks." — Finance director, Cardiff-based logistics firm
That project started with a single question: where is the real bottleneck? Every engagement we run begins the same way.
Most AI projects fail not because the technology is wrong, but because the problem was never properly defined. We exist to close that gap — to make sure every model, pipeline and dashboard we build solves something you actually need solved.
We are a small, focused consultancy based in Wales. We work with mid-sized UK companies — manufacturers, logistics operators, financial services teams, healthcare providers — who want to use machine learning and language models without betting their budget on hype.
We spend the first week understanding your data, your team and your constraints. If a spreadsheet formula solves the problem, we say so. Nobody needs a neural network to sort a mailing list.
Our first deliverable is always a working prototype connected to your own data, not a slide deck. If it does not perform against a baseline, we adjust or stop.
We never train on client data outside the engagement scope. Models run on your infrastructure or a private cloud instance. When the project ends, we hand over every artefact — weights, code, documentation.
Dependency on external consultants is expensive. Every project includes hands-on training so your engineers can maintain, retrain and extend what we build.
We quote fixed fees for defined scopes. If the scope changes, we renegotiate before any new work starts. No surprise invoices.
Bias audits, explainability reports and data-governance checklists are part of every delivery. We follow the UK AI Regulation white paper guidelines and prepare clients for upcoming legislation.
What we actually build, who it serves, and how long it typically takes.
| Capability | Typical client | Timeline | Stage |
|---|---|---|---|
| Demand forecasting models | Retail, manufacturing | 4–6 weeks | Production-ready |
| Document classification and extraction | Legal, finance, insurance | 3–5 weeks | Production-ready |
| Conversational AI assistants (LLM-based) | Customer service teams | 5–8 weeks | Rapid iteration |
| Anomaly detection for IoT sensor data | Utilities, infrastructure | 4–7 weeks | Production-ready |
| Computer vision quality inspection | Manufacturing lines | 6–10 weeks | Rapid iteration |
| Data strategy and governance audit | Any sector | 2–3 weeks | Advisory |
| ML Ops pipeline setup | Engineering teams | 3–5 weeks | Production-ready |
A demo running on clean sample data in a notebook is not a product. The gap between "it works on my laptop" and "it runs reliably at 3 a.m. when nobody is watching" is where most projects die. Deployment means monitoring, retraining triggers, fallback logic, and someone who knows what to do when the data distribution shifts.
We build for that second stage from day one. Our prototypes already include logging, input validation and a basic retraining schedule. When the pilot succeeds, production is a configuration change, not a rewrite.
A Welsh manufacturing client told us their previous vendor spent five months on a proof of concept that never left a Jupyter notebook. We rebuilt and deployed it in four weeks.
We listen. You describe the problem, the data you have, and what success looks like. No sales pitch — just questions.
We examine a sample of your data under NDA. Within five working days you receive a written feasibility note: can this work, what approach fits, what it will cost, and what risks exist.
A working model on your data, tested against a baseline metric you define. This is the point where most engagements prove their value — or we stop and save you money.
We containerise the model, set up CI/CD pipelines, monitoring dashboards and alerting. Your team gets access to everything from day one.
Documentation, a recorded walkthrough, and two live training sessions for your engineers. After that, the system is yours. We remain available for quarterly check-ins if you want them.
Answer these honestly. If most answers are "not yet," that is fine — the data strategy audit exists for exactly that situation.
Book a free 30-minute discovery call. No slides, no pressure, just a conversation about your data and what it could do for you.
Get in touch belowEmail: [email protected]
Phone: +44 7840 344091
Address: 18 Anderson Square, Lindgrenton, Wales, DT9 5OF, United Kingdom
We typically respond within one working day. If your enquiry is urgent, call us directly.
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Last reviewed: January 2026.
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Project timelines, costs and outcomes mentioned on this site are based on past engagements and may vary depending on your specific data, infrastructure and requirements.
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