What we build with
Models, frameworks and infrastructure chosen against your data and your load, never by fashion.
Tools we build with every week
The full inventory
Every engagement draws from the same nine layers. What changes is which pieces we reach for, and we will tell you why before a line of code is written.
Transformer models for text, image and multimodal work, fine-tuned on your data and wrapped in guardrails before anything reaches a customer.
The tooling that turns a notebook into a service: orchestration, evaluation, experiment tracking and model packaging.
Classical models still win on tabular problems. We pick the smallest model that clears your accuracy bar and keep it explainable.
Detection, segmentation, OCR and speech pipelines that run on edge hardware as happily as they run in a data centre.
Search, classification and document understanding for the messy text that real businesses actually store.
Services, queues and stores built to survive the traffic you expect on your worst day, not your average one.
The surface your users judge everything by. Accessible, fast on a mid-range phone, and typed end to end.
Reproducible environments, one-command deploys and the observability to know something broke before your users tell you.
Test coverage that catches regressions before your users do, with accessibility checked as part of every release.
The same engineering standard applies at every size. What changes is how much of it you need on day one.
We help founders find the smallest system that validates the bet: a scoped MVP, a model that clears the bar on real data, and a deployment you can demo to investors without a rehearsal.
Why teams stay
No handover from a sales engineer to an offshore pool. The engineer in your kickoff call is the one writing the code, and they stay on the project until it is in production.
You see working software every week. If a week produced nothing worth showing, we say that instead of dressing it up.
We agree on the number that defines success before we start, and we report against it. Model accuracy is our problem, not your KPI.
500+
Projects delivered
85+
In-house experts
12+
Industries served
30+
Countries shipped to
We start from your constraints: the data you hold, the systems it has to talk to, the latency your users will tolerate and the budget you have for inference. The stack falls out of those answers. If a smaller open model clears your accuracy bar at a tenth of the cost, we will tell you, even when the larger one is easier to sell.
Bring the problem and the constraints. We will come back with the stack, the timeline and the number it has to hit.
Talk to our engineers
