An AI-native product studio in Coimbatore, working inside your team rather than across a contract.
An AI-native product studio in Coimbatore, working inside your team rather than across a contract.
A world where the hard part of software is deciding what to build, not whether it can be built.
To put working AI products in the hands of real teams — measured, maintainable, and owned by them.
Evaluation is built into the project from the first week, running against your data rather than a public benchmark. When we say something works, there is a number behind it and you can see how it was produced. It also means we find out early when an approach is wrong, while changing course is still cheap.
We work in your repositories, your standups and your tools. Our commits go through your review. The point is that when an engagement ends you are not holding a handover document — you are holding software your own engineers have been shipping alongside us for months.
We take on a small number of engagements at a time so each one keeps senior attention from scoping through to handover. It costs us revenue and it is the main reason clients get the same people at the end that they met at the start.
Code, documentation, models and evaluations belong to the client. We work inside your cloud where we can, we do not train on your data, and all of it is written into the contract before a line of code exists. No lock-in and no black boxes.
A thirty-minute call, then a written scope of one page: the problem, what we would build first, what it costs and when we could start. You get a real number and a start date within a week — no procurement cycle to sit through, and no obligation once you have it.
Step 1 of 4Something concrete you can use and react to, running on your data rather than a demo set. By the end of it we know whether the approach holds, and so do you. Roughly half our projects change direction here, which is the point of doing it first.
Step 2 of 4Hardening, integration and evaluation at volume. The timeline depends almost entirely on how much of your existing infrastructure it has to talk to — the model work is rarely the long pole. Your engineers are in the codebase throughout.
Step 3 of 4Documentation, runbooks and the evaluation harness, handed to the people who have been reviewing the work all along. Engagements run month to month after the first phase, so we stay only as long as we are useful.
Step 4 of 4