AI Development Services
AI built to improve one named business decision, with the way we will measure it agreed before the first line of code rather than bolted on later when somebody asks whether it worked.
Something that runs, measured against how you perform today.
- You have one job in mind, one person responsible for it, and a number you want to move.
- Something works on one person's laptop and nobody knows how to turn it into a system the business can use.
- You want AI inside the process people already follow rather than in a separate tool nobody opens.
- You have an AI system running live and no idea whether it is still any good.
Building the AI is the part everybody wants to start with and the part that goes wrong most predictably. The models themselves are close to being an off-the-shelf product now. It goes wrong because teams build without agreeing what success looks like, then find afterwards there is no way to tell whether the thing helped.
We start at the other end. We agree which decision the system is meant to improve, how well that decision goes today, and what number would count as good enough. Then we build the smallest version that could realistically hit it, working the whole way through, on real records.
What we build depends entirely on the problem. It might be a system that searches your own documents and answers from them, a model trained on your own examples, older and simpler statistical methods, or software that takes actions in your systems instead of only answering questions. We have delivered all of these. They include chat assistants that qualify enquiries and chase follow-ups in WhatsApp and Telegram and write the result straight into the CRM with nobody retyping anything, and freely published connectors that put 143 different AI tools inside AutoCAD and Revit.
Then comes the part trials skip: who is allowed to use it, a hard ceiling on what it can spend, a record of every question asked and every answer given, a limit on how hard it can be worked, and an alarm if the answers start getting worse. A system that quietly gets worse is more dangerous than no system, because people carry on trusting it.
What you get
Working system
Running on your own systems. It might search your documents and answer from them, be trained on your own examples, use older and simpler statistical methods, or take actions in your systems. Whichever the problem actually needs rather than whichever is fashionable.
Test set and scores
Real examples with known right answers, kept aside, with a pass mark agreed in advance, so "is it good enough" has a number for an answer and the test runs again automatically on every change.
Limits and monitoring
Who is allowed to use it, what it is allowed to spend, a record of every question and every answer, and an alarm when the quality starts slipping, before your users are the ones who notice.
Documentation and training
How it works, where it breaks, and how to train it again as your data changes. Written for whoever inherits it, not for us.