AI integration & software consultancy · LondonAI that knows your business.

With an operations audit. Most businesses can’t say what to automate — not because there’s nothing, but because the time is lost in places nobody is measuring: re-keying between systems, chasing approvals, hunting for answers, fixing the same mistakes.

• You talk, we listen. Walk us through how work actually gets done — the tools, the people, the hand-offs, and where things wait.
• We find the bottlenecks. Where hours, money or accuracy leak, and which of those AI or automation can genuinely fix.
• You get a plan. What to automate first, what it would save, and a fixed-price first step — or an honest “not worth it”.

You don’t need a brief, a spec or tidy data. You need to know how your business runs — that’s the part only you can bring.

Yes — and we treat it the way regulated businesses do, because that’s where we’ve spent the last few years: payments, banking, car finance and insurance.

• No training on your data. We only use business-tier AI services — Anthropic, OpenAI, Microsoft Azure, AWS Bedrock or Google Cloud — whose terms say your data isn’t used to train their models. Zero-retention options are used where they’re available.
• It stays in your accounts. Wherever possible we build inside your own cloud and tools, in UK or EU regions, so the data never sits on our systems.
• People only see what they already could. The AI respects your existing permissions. Sensitive details — card numbers, IDs, health data — can be masked before anything reaches a model.
• Everything is logged. Who asked what, what the AI looked at, and what it answered. You can audit any decision after the fact.
• Paperwork first. An NDA before you share anything, and a data processing agreement under UK GDPR. Our access is removed when the work ends.

If your sector has stricter rules — FCA, healthcare, public sector — tell us on the first call and we’ll design to them from day one.

No — it’s the usual starting point. Most businesses we speak to run on spreadsheets, shared drives, inboxes, WhatsApp groups and a system or two that don’t talk to each other.

Pulling that together is part of the job, and often half the value. We build pipelines that read your sources where they are, clean and organise what’s there, and keep it up to date when it changes — so your team can keep working the way they do today.

You don’t need a data project before an AI project. We do them together, one useful piece at a time.

Design, not hope. AI that touches real customers or real money needs the same discipline as any other production system.

• Answers with sources. The AI shows where every answer came from, so people can check it in a click.
• Tested before it’s live. We build a test set from your real questions and cases, and measure accuracy against it before launch and after every change.
• Guardrails. Clear rules for what it may and may not do, and it says “I don’t know” rather than guessing.
• A person in the loop. For decisions that matter, AI recommends and a person approves — until the numbers show it can be trusted with more.

It’s how we built AI that reviews disputes for a payments company serving 15 million customers a month.

Almost certainly. If a tool has an API, an export or an inbox, we can usually connect to it — Google Workspace, Microsoft 365, Slack, WhatsApp, CRMs, helpdesks, accounting and e-commerce platforms, databases and in-house systems.

We’d rather fit around how your team already works than ask them to learn a new tool. Often the best AI is the one that appears inside the app they already have open.

That’s your call, but it isn’t how we design it. The aim is to take the repetitive part of the job — searching, copying, checking, summarising — off your team, so the same people handle more, faster, with fewer mistakes.

In practice that means growing without hiring at the same rate, and freeing your best people for the work only they can do.

Whichever does the job best for the cost — Claude, GPT, Gemini or open-source models. We’re not tied to any vendor.

We measure the options against your real questions before choosing, and build so the model can be swapped later. AI moves quickly; you shouldn’t be locked into last year’s best option.

Every deliverable has a fixed price, agreed in writing before work starts. No day rates and no hourly meter — you always know the cost of the next step before you commit to it.

We size the first deliverable to be small, useful on its own, and quick to prove its value. You’ll have numbers in writing after the first call.

Running costs — AI usage and hosting — are estimated upfront and billed by the providers straight to your own account, with no mark-up from us. For most business tools they’re small next to the time saved.

Weeks, not months. The first deliverable is chosen to be useful on its own, so your team is using it while we build the next.

You see working software every couple of weeks, tested on your real work — not slide decks and status reports.

Yes. The code, data pipelines, prompts and tests are yours once each deliverable is paid for.

It lives in your repositories and your cloud accounts, under your name, with documentation your own team — or anyone else — can pick up. No lock-in, no licence fees to us.

Your choice. We can hand it over to your team with documentation and a walkthrough, or keep improving it as an ongoing partnership — monitoring accuracy, adding sources and extending it as your business changes.

Either way, you’ll have the monitoring to see how it’s performing, not just our word for it.

Then you don’t pay for it. Each deliverable has acceptance criteria agreed upfront. If it falls short, we fix it at no cost until it meets them — or you walk away.

You can stop at any point and keep everything you’ve already paid for: the working software and the code.