AI systems built on your own data.
For established companies with something valuable already in the building, a clear idea of what they want done with it, and nobody who could build it. We build the whole thing.
Where most companies get stuck.
You tried ChatGPT inside the business. It was impressive for ten minutes, then you hit a wall.
The knowledge that makes you good sits in documents, inboxes, and a few people’s heads.
The same questions get answered by hand, over and over, by people who are expensive.
You know exactly what you want built. There is nobody in the building who could build it.
Off-the-shelf tools nearly fit, but not on your data and not the way you actually work.
Work that should take minutes takes days, because it has to pass through three people first.
A system that knows what your business knows.
Law firms, insurance brokers, recruitment agencies, clinic groups, media and research businesses, trade bodies. Established companies whose real asset is what they have accumulated, and who have never had a reason to employ engineers.
Four things, described by what they do.
Answers from your own material
A system that has read everything your business knows, your documents, records and past decisions, and gives real answers from it. Not a chat window making a confident guess.
Work that runs without being asked
Jobs that take several steps and several sources, done end to end without a person driving them. It keeps going when a step fails, and it tells you when something needs a human.
Something changes, the right person hears about it
The system watches whatever matters to you as it happens, works out what it means, and gets it to the person who needs to act. Detection to notification in under a second.
Plugged into what you already use
It works with the systems your business already runs on, rather than becoming another place your team has to remember to check.
What these systems actually did.
Client work is under NDA, so these describe what was built rather than who it was for.
One system behind every channel, not a separate bot per channel.
The difference between a system that scales and one that becomes six systems to maintain.
Questions arrive through several different routes, each about a different part of the business. The system works out what is being asked, finds the right source, and answers from it.
Adding a new route later is a setting, not another build. That is what stops this becoming six things to look after.
Years of records turned into plain written analysis
An AI layer over years of accumulated trading records plus everything arriving live, producing written analysis of behaviour and performance rather than another dashboard.
The supporting numbers come back in one to two seconds and stay that fast as the records grow.
Several sources, several steps, one answer
A framework that pulls in several independent sources, works through a problem in stages, and produces a single result.
Built to run unattended for months, handling its own failures, rather than to look good in a demonstration.
Sub-second detection to notification
Live market data feeding model-driven alerting, on the same architecture used for financial systems.
Connections into live business systems
Custom MCP servers and consumers, personal and email agents, and the infrastructure that connects models to the systems a business already runs on.
The parts you should not have to ask about.
Systems like this can get expensive quietly, because they run continuously. We control that from the start through compression, caching, batching and routing work to the cheapest model that can do it properly. Most of that spend is recoverable without the output getting worse.
Most of these systems fail at the data underneath rather than at the model on top. That layer is our specialism, and it is why the numbers stay fast as your records grow.
Automated test coverage as standard, and written documentation at handover so you are never locked in, whether or not you have engineers of your own.
If you already run monitoring we work with it. Otherwise we watch the system ourselves and hold the alerts, for cost as well as for failure.
Already got something running?
A written assessment of where it stands and what to do next.
Not a verdict on whoever built it. Systems drift, models change and costs move, and it is usually cheaper to find out where you are before deciding what to build next. You get the document either way, and you are free to hand it to anyone.
- How it is put together, and what that will cost you later
- Where it slows down or breaks as volume grows
- What happens when a step fails
- What you are spending to run it, and how much of that is recoverable
Production systems, not demonstrations.
Delivered across six years, profitable throughout.
Build size supported, on real timelines.
Large-scale real-time systems on Kubernetes at a global custodian bank, where being wrong was not an option. That is the standard these are built to.
Senior and principal engineers only. Nobody is learning the job on your budget.
The engineer building it, not an account manager.
Fixed scope and fixed price, agreed in writing. Staged payments. The system is yours outright on final payment. For most clients we stay on afterwards as the engineering team they do not have.
Established businesses with a real budget behind the work. We are not the cheapest option and we will say so early if we are not the right fit.