Services
From model to product, one team
We build the model, the data pipeline that feeds it, and the application people use it through. That means no handoff between an ML team and a product team, and no ambiguity about who owns the result.
AI & Machine Learning
Models built for a specific job, evaluated against your data, and shipped where they can be monitored.
Generative AI
LLM features that hold up outside a demo - grounded in your content, measured, and cost-bounded.
Product Engineering
The platforms, APIs, and infrastructure that turn a model into something a customer can use.
Data Services
Pipelines and labelled datasets. The part most teams underestimate, and the reason models underperform.
Annotation and labelling capabilities
Not sure which of these you need?
Most projects touch two or three. Describe the problem and we'll map it out.