Find the failures that matter to your application.
An overall score can hide failures in a document type, workflow step, or domain requirement. Task-level evaluation helps your team decide what data or behavior to improve.
We build evaluation tasks, expert rubrics, and automated verifiers around the capability you need. Reviewer notes and execution evidence explain the failure categories behind the scores.
Start with the decisions the evaluation will inform
Set the use case, target behavior, and acceptance criteria before selecting metrics. Include representative difficult cases and document the test conditions.
- Align tasks and rubrics to the intended workflow.
- Keep evaluation material separate from training data.
- Define what constitutes a meaningful failure.
Turn failure patterns into training priorities
Group errors by task and decision point. Where loss information is available, review it alongside execution evidence and expert findings.
- Group errors by capability and cause.
- Review disagreements and ambiguous cases.
- Use findings to scope the next data collection cycle.
What a program can include
Scope can include:
- Custom evaluation tasks and review criteria
- Expert scores and verifier specifications
- Failure categories and supporting examples
- Analysis to inform follow-up training priorities
Illustrative task / Not a production record
Make the objective concrete.
- Objective
- Evaluate whether an agent completes a document-review workflow.
- Context
- Held-out tasks, source files, model outputs, and a defined scoring rubric.
- Review
- Check completion, evidence grounding, missed requirements, and the specific decisions associated with failure.
Common questions
Should we use public benchmarks or custom evaluations?
They answer different questions. Public benchmarks provide a shared reference, while custom tasks can assess requirements specific to your application. Choose the mix around the decisions your team needs to make.
Do you need model access to scope the evaluation?
Begin by discussing the task, inputs, outputs, and review criteria. The required model access or supplied results depend on the agreed evaluation workflow.