AI solutions
AI that earns its keep
We build AI into the workflows where your team loses hours — document handling, drafting, triage, data entry — engineered properly, measured honestly, with humans in the loop where it matters.
AI, without the theatre
AI that's wired into the work — not bolted on beside it
Most "AI adoption" fails the same way: a chatbot nobody asked for, floating outside the systems where work actually happens. We do the opposite. We find the tasks that eat your team's hours — reading documents, re-keying data, drafting the same email fifty ways, triaging inboxes — and build AI into the workflow that does them, with a human checkpoint wherever judgement or liability is involved.
Because we're engineers first, the unglamorous parts get done properly: data preparation, access control, audit trails, cost control, and honest measurement of whether the thing is actually saving time.
And none of it is theoretical: our team has delivered AI agent and chatbot builds under repeat contract for one of the big-three global strategy consultancies — work where "it usually answers correctly" doesn't survive review.
- Document intelligence — extract structured data from invoices, contracts, applications and reports automatically.
- Workflow copilots — drafting, summarising and classification built into the tools your team already uses.
- Decision support — surface the right information at the right moment instead of burying people in dashboards.
- Process automation — chain AI with your systems so whole processes run end-to-end with review points, not babysitting.
- Honest scoping — if a rules-based automation does the job for a tenth of the cost, that's what we'll recommend.
Where it pays off first
The three fastest returns we see
Inbound document handling
Invoices, orders, applications and supplier documents read, checked and entered into your systems in seconds — with exceptions routed to a person.
First-draft generation
Quotes, reports, responses and client communications drafted from your data and templates, then reviewed by your team instead of written from scratch.
Search that actually finds things
Ask questions of your own documents, policies and job history in plain English — with sources cited, so answers can be trusted.
Questions
Straight answers
Is our data used to train AI models?
No. We architect solutions so your data stays within your controlled environment, using enterprise API terms that exclude training on your inputs — and we put that in writing as part of the design.
We tried ChatGPT and it made things up. How do you deal with that?
By never letting a model answer unsupervised where accuracy matters. We ground responses in your own data, cite sources, add validation rules, and keep a human review step on anything consequential. Our AI for SMEs guide explains the approach in plain English.
Do we need to be a big company to benefit?
No — smaller firms often see the fastest payback because one automation can free a meaningful share of a small team's week. Start with one painful process, measure the hours saved, then scale what works.