Artificial intelligence
Models trained on your data, shipped into the product
- Machine learning
- Automation
- Document AI
- Forecasting
AI that does a job, not a demonstration. Almost every useful model we have built solves something narrow and specific — reading documents a person used to key in, ranking what a support queue should look at first, forecasting demand from three years of the client’s own sales.
What the work consists of
Model development
Trained on your data rather than a public dataset that resembles it. We start by establishing what accuracy is worth the cost, because most projects do not need the last two percent.
Language and document work
Extracting structure from invoices, forms and reports, and answering questions over a body of internal documents — the two applications that pay for themselves fastest.
Shipping and monitoring
A model in a notebook is not a product. We put it behind an API, watch what it does in production, and tell you when its inputs have drifted far enough that it needs retraining.
Automation
The routing, scoring and triage work that sits between a model and an actual saving. Usually the part that turns an interesting result into a smaller payroll line.
What you end up with
- A measurable baseline before any model is trained
- The model serving live traffic, not sitting in a notebook
- Monitoring that tells you when it starts drifting
- An honest answer when the problem does not need AI
Other capabilities
Have something like this in mind?
Tell us what you are trying to build. The quotation is free and it commits you to nothing.