AI development that survives contact with real customers.
AI development is building an AI feature or product that works in your business every day — not a demo that works once. We do the whole job: the model work, the system around it, the failure cases, the access rules, and the record of what it did. Senior hands throughout, and it lives in systems you own.
The gap that costs money is not getting AI to work. It is getting it to keep working when the inputs are strange, the volume is real, and somebody acts on an answer that turned out to be wrong. Roughly 95% of business AI projects never make it past the demo, and it is almost never the model that stopped them.
Book a Reality CheckIs this you?
Where this earns its place.
- You have a prototype that impressed everyone and nobody will sign off for production.
- You want to put AI in front of customers and need to know it will not embarrass you.
- You have AI working internally and now it has to handle real volume and real data.
- Your own team can build it but nobody has taken an AI system into production before.
If you want a proof of concept to test an idea cheaply, you do not need us — build it fast, learn, and come back when it has to be real. We will say so on the call rather than sell you the expensive version of a cheap question.
What you get
Specifically, not in principle.
The system around the model
Retrieval over your own material so answers are grounded and traceable, limits on what the AI is allowed to do, and a human in the loop wherever being wrong is expensive. The model is the easy part; this is the work.
Failure handled out loud
What happens when the model is wrong, the API times out, someone pastes forty thousand words, or the answer is confidently incorrect. Each of those is a decision. The ones nobody makes surface later, in front of a customer.
Automated checks on quality
A set of real questions with known-good answers, run on every change to model, prompt or retrieval. Without it you cannot tell whether a change improved anything — only that it still runs.
A record you can answer questions from
Input, output, model version, prompt version, who reviewed it, when. Retrievable months later, because that is when someone asks — an auditor, a customer, or your own team wondering why it said that.
Data kept where it belongs
If you serve more than one customer, each one's data sealed off from every other's — enforced in the data layer, not by a filter in the application that one query can forget.
How it runs
Specified first, built by the person who scoped it.
We write down what it does, what it must never do, and how we will know it is working — before anything is built. That document is the thing you approve, and it is what keeps a build from quietly becoming a different build.
Whoever scopes your work is who builds it and who answers the phone. No account managers, no juniors learning on your systems. Everything is documented and lives in your repositories, so you are never locked into us.
Before you ask
Straight answers.
Yes, and that is often the best arrangement. We bring the production discipline, your team keeps the domain knowledge, and everything we write lives in your repositories with the reasoning documented so they can carry it on.