AI that removes a real task, not AI for the press release
We start by finding the job your staff repeat fifty times a day, then automate that one. No strategy deck, no chatbot bolted onto a homepage and called transformation.
Free first call. Fixed price before you commit. Source code handed over at launch.
Why most business AI projects quietly die
They get built against a demo instead of a workflow. The model is impressive in a meeting, then it invents an answer in front of a customer, nobody can tell where the answer came from, and within a month the team stops using it. The failure is almost never the model. It is the absence of sources, limits and a human check.
- Answers with no source, so nobody can verify them
- No handover to a person when confidence is low
- Trained or prompted on the open internet rather than your own material
- No measurement, so nobody knows if it is right more often than it is wrong
written plan ... within 48 hours
price ... fixed, not hourly
sprints ... 2 weeks each
source code ... yours at launch
If the price does not work we cut scope together until it does, before you pay anything.
The four patterns that consistently pay off
Almost every profitable AI build we do is one of these. If your problem is not on this list, that is worth a conversation, but be sceptical of anyone promising something far more exotic.
Answers from your own documents
Policies, manuals and past tickets become an assistant that cites the page it answered from, so staff can check it in one click.
Reading paperwork
Invoices, delivery notes and forms photographed and turned into structured records, with anything uncertain routed to a person.
Sorting the inbox
Email and messages classified, tagged and sent to the right team with a draft reply attached.
Seeing demand early
Sales history turned into reorder suggestions, so a stockout is not something a customer tells you about.
The limits we build in every time
These are not optional extras. An assistant that confidently invents an answer costs more than the staff time it saved.
Cited answers only
If it cannot point at a source document, it says it does not know.
A human on the risky path
Anything touching money, stock or a commitment to a customer needs approval before it takes effect.
Measured before rollout
Accuracy tested against a real sample of your documents, with the score shown to you before go live.
Your data stays yours
No training on your content, and deployment options that keep everything inside your own accounts.
What changes depending on where you trade
The build is not the same in every market. Tax, accessibility law and data rules differ, and they change the design rather than just the paperwork. Here is what shifts.
For businesses in the United States
Sector rules decide the shape of the build more than the technology does. Healthcare, finance and education each carry constraints on where data may sit and who may see it, and those need designing in.
- HIPAA aware handling where healthcare data is involved
- SOC 2 friendly logging and access control for enterprise buyers
- Deployment inside your own AWS or Azure account, in a US region
- State privacy laws such as the CCPA reflected in retention and deletion
For businesses in the United Kingdom
UK GDPR governs automated processing of personal data, and gives people rights over decisions made about them. Where an AI step affects a person, there has to be a route to a human.
- UK GDPR lawful basis documented for each automated step
- A human review route wherever a decision affects an individual
- UK or EU hosting, with no transfer outside without a legal basis
- Retention and deletion that a data subject request can actually satisfy
For businesses in Europe
The EU AI Act classifies systems by risk, and the obligations that follow depend on which class yours falls into. Most business automation sits in the low risk band, but transparency duties still apply, and it is far cheaper to establish that at scoping than after launch.
- Risk classification assessed under the EU AI Act during scoping
- Transparency: people are told when they are dealing with an automated system
- EU hosted deployment with a data processing agreement in place
- Technical documentation and logging kept to the standard the Act expects
Questions we get asked about this
Q1 Will our data be used to train someone else's model?
Q2 How do we know it is accurate enough to trust?
Q3 How much does an AI build cost to run each month?
Tell us the problem. We send back a plan in 48 hours.
A written plan with every screen mapped, a fixed price and a delivery date. Yours to keep whether or not you hire us.
Often built alongside this
- ERP SoftwareOff the shelf ERP asks you to change your process to match the software. We do it the other way round. You get the modules you actually need, wired to the tools you already pay for, at a price agreed before anyone writes code.
- Web DevelopmentA website that takes four seconds to load on a phone has already lost most of the people who clicked. We build sites your team can edit, that pass Core Web Vitals, and that are structured so search engines can actually read them.
- SEO ServicesA ranking report is not a result. The number that matters is how many enquiries arrived and what each one cost, so that is what we report, in language that needs no translation.