AI advice without the hype
We help UK businesses work out where AI genuinely pays off — and where it doesn’t — with vendor-neutral advice, a pilot-first approach, and success metrics agreed before anyone writes a cheque.
How we approach it
Most businesses don’t have an AI problem; they have a signal-to-noise problem. Every vendor now claims their product is AI-powered, every board wants an AI strategy, and the gap between demo and dependable is wider than the industry admits. Our consultancy exists to cut through that: senior engineers who build with these models daily, telling you plainly which of your processes AI can genuinely improve, which it can’t yet, and what each answer is worth in pounds.
We start with your operations, not the technology. The best AI use-cases are usually unglamorous: hours spent re-keying documents, triaging inboxes, summarising calls, answering the same customer questions, or drafting first versions of repetitive documents. We map those workflows, estimate the time and error cost of each, and rank the opportunities by return on investment. Just as importantly, we’ll tell you when the honest answer is a spreadsheet, an automation, or nothing at all.
Then comes the build-versus-buy question and vendor selection — done without allegiance. We work across OpenAI, Anthropic, AWS Bedrock and open-source models like Llama, and we recommend based on accuracy on your actual tasks, cost per unit of work, and data-handling terms, not on partnership deals. We also assess data readiness honestly: many AI projects fail not because the model is weak but because the data is scattered or unusable. UK GDPR, privacy and compliance are addressed in the plan from day one, not retrofitted after a legal review.
Everything we recommend is pilot-first. Rather than a six-figure transformation programme, we define a small, contained pilot with success metrics agreed upfront — accuracy thresholds, time saved, cost per task — and a fixed price. If the pilot hits its numbers, you scale with confidence; if it doesn’t, you’ve spent little and learned a lot. Alongside, we train your team to use and evaluate these tools themselves, because the goal is capability you own, not dependence on us. It starts with a free 30-minute call.
AI Consultancy, done properly
Use-cases ranked by ROI
We map your workflows, cost the manual effort and error rates, and rank AI opportunities by measurable return — including the ones not worth doing.
Build vs buy, answered honestly
Sometimes an off-the-shelf tool wins; sometimes a custom build pays for itself in months. We show the total cost of each option so you can decide on evidence.
Vendor-neutral model selection
OpenAI, Anthropic, AWS Bedrock or open-source — we benchmark candidates on your real tasks and recommend on accuracy, cost and data terms, not partnerships.
Data readiness assessment
An honest review of whether your data is accessible, clean and complete enough for the use-case — and a practical plan to close the gaps if it isn’t.
UK GDPR & compliance built in
Data-processing terms, retention, model-training opt-outs and lawful-basis questions resolved in the plan, so legal review doesn’t derail the project later.
Team enablement & training
Hands-on sessions that teach your team to use, prompt and evaluate AI tools on their own work — building capability you keep, not dependence on us.
From first call to launch
- 01
Discover
We spend time in your actual workflows — the inboxes, documents and handoffs — and identify where hours and errors accumulate. No slideware, just findings.
- 02
Assess & recommend
A written report ranking use-cases by ROI, with build-vs-buy analysis, model and vendor recommendations, data readiness findings and compliance considerations.
- 03
Pilot
A small, fixed-price pilot on the strongest use-case, with success metrics — accuracy, time saved, cost per task — agreed in writing before it starts.
- 04
Scale or stop
If the pilot hits its numbers, we plan the rollout and train your team. If it doesn’t, we say so plainly — a cheap “no” is one of the most valuable things we sell.
AI Consultancy questions, answered
How do you identify which AI use-cases are worth pursuing?
We look for high-volume, repetitive work with clear right answers: document processing, inbox triage, call summarisation, first-draft writing, customer questions asked hundreds of times. For each candidate we estimate current cost in hours and errors, what a model can realistically achieve on your data, and what the change is worth annually. Use-cases are then ranked by return on investment — and we’re explicit about which ones fall below the line.
Which AI vendors and models do you recommend?
We have no reseller deals, so the honest answer is: it depends on the task. We work across OpenAI, Anthropic’s Claude models, AWS Bedrock and open-source options like Llama, and we benchmark candidates on samples of your actual work rather than public leaderboards. Selection weighs accuracy on your tasks, cost per unit of work, latency, and — critically for UK businesses — each vendor’s data-handling and training terms.
How do you handle UK GDPR and data privacy?
From the start, not as an afterthought. We establish what personal data each use-case touches, whether it needs to reach a model at all, and which vendors offer appropriate terms — no training on your data, suitable retention, UK or EU data residency where required. We document lawful basis considerations and produce material your DPO or legal adviser can review, so compliance questions are settled before the pilot, not after it.
What does a pilot involve and what does it cost?
A pilot is a small, contained implementation of your strongest use-case — typically two to six weeks — with success metrics agreed in writing first: accuracy thresholds, hours saved, cost per task. It runs on real work, often shadowing the existing process so nothing breaks if it underperforms. Pilots are fixed-price, scoped in a free 30-minute call, and deliberately sized so a “no” verdict is affordable.
Will you tell us if AI isn’t the right answer?
Yes, and we do it regularly. Plenty of problems brought to us as “AI projects” are better solved with a straightforward automation, a better process, or an off-the-shelf product — all of which cost less and fail less. Because we also build software and automations, we have no incentive to force AI into the answer. You’re paying for the correct recommendation, and sometimes the correct recommendation is “not this, not yet”.
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Let's talk about your project
Tell us what you're trying to achieve. A free 30-minute chat, no obligation — we'll tell you honestly what we'd recommend, what it would cost and what it should pay back.