Service
Model and system evaluation
Evaluation is how you find out whether a system works on your task rather than on a benchmark. We build a validation set from your real examples, write a scoring rubric with your reviewers, and measure candidate models and configurations against it. The evaluation set stays yours, and it outlives every model you use.
Who this is for
Teams about to put an AI system in front of customers or staff, and teams who already have one running and cannot say how well it performs.
The business problem it addresses
Public benchmarks tell you how a model performs on someone else’s task. They rarely predict how it performs on yours, and they never tell you what an acceptable failure rate is for your business.
Without an evaluation set, every model decision becomes an argument about impressions, and every regression is discovered by a customer.
Signs you may need this
"It seems better" is the strongest evidence anyone can offer. Nobody can say what changed when the provider updated the model. There is no agreed definition of a wrong answer. Quality is assessed by spot-checking.
What the engagement includes
A validation set drawn from real work. A rubric written with the people who currently do the task. Scoring of candidate models and configurations. Cost and latency measured alongside quality. Failure-mode analysis, not just an aggregate score. A regression suite you can re-run.
What we report
Scores against the rubric, cost per thousand decisions, latency distribution, and the specific cases where each configuration fails. We publish the limitations of the evaluation itself, including what it does not cover.
When this is not appropriate
When the task has no definable correct answer. When the volume is so low that human review is simply cheaper. When the organisation is not prepared to act on an unfavourable result.
Questions buyers ask
How many examples do we need?
Fewer than people expect. A well-chosen set of a few hundred real cases usually separates candidates clearly. Representativeness matters more than volume.
Who writes the rubric?
Your reviewers, with us facilitating. A rubric written without the people who do the work will not survive contact with real cases.
Can you evaluate a system we already have?
Yes, and it is often the fastest way to establish whether the problem is the model, the retrieval, or the workflow around it.
Does this lock us to one provider?
The opposite. The evaluation set is what makes changing provider a measurable decision rather than a leap.