Models.
Choosing, fine-tuning and evaluating the right model for the job — then proving it with the numbers before it ships.
Get in touch ↗Most teams pick a model by reputation and find out later whether it was right. We start from the job the model has to do and the numbers it has to hit, then work back to the smallest, cheapest model that meets them.
Selection
We shortlist hosted and open-weight models against your real tasks, data and constraints: latency, cost per request, privacy and where the model is allowed to run.
Evaluation
Before anything ships we build an evaluation set from your own examples, with clear pass and fail criteria. Every model change runs against it, so quality is a number you can track, not a feeling.
Fine-tuning
When prompting alone won't get there, we fine-tune on your data and compare the result against the baseline, so you only pay for training that measurably helps.
What you get
- A recommended model with the evidence behind it
- An evaluation suite your team can keep running
- Cost and latency estimates at your expected volume