Machine learning development
A model is a claim about the future. We make it one you can defend.
Model design, training, fine-tuning, and evaluation on your data, measured against a number your organisation already reports. Error analysis is half the work: we write down where the model fails, how often, and at what cost, before anyone builds on top of it.
When to call us
- A vendor demo performed well, but the results did not hold on your data.
- You report a number to a regulator and believe a model could move it.
- You have a model in production and nobody can say precisely when it is wrong.
What lands on your side
- Model design and training on your data, in your environment
- Evaluation against the metric your organisation is accountable for
- Error analysis: failure modes, their frequency, and their cost
- Model documentation a risk officer can read unaided
The line we hold
We report the measured result. If it is below the target, the report says by how much and where.
- Typical engagement
- Standalone, or within a system build
- How long
- 3–8 weeks
- What you keep
- A model, its evaluation, and a written account of its limits
Make the model defensible.
Tell us the number you report and what you believe a model could do to it. The first evaluation conversation costs nothing.
Bring us the number