Measure what the model actually knows.Scored by people who know it too.

Saolabs builds expert-written tests and scores model and agent outputs with vetted specialists. You get results you can act on, and a clear account of what the evaluation does not cover.

What expert evaluation is

Expert evaluation measures a model's outputs against the judgement of people who practise in the field. Saolabs specialists write test prompts, define what a correct answer requires, and score responses against a rubric.

It sits between automated benchmarks and live user feedback. Benchmarks are fast but often saturated or easy to overfit. User feedback is real but arrives after release. Expert evaluation tests the hard, specific cases before users see them.

Tests written for your use case

Public benchmarks measure what someone else cared about. Saolabs experts write tests around the tasks your model will actually face, in the domains where it will face them.

A legal evaluation might focus on jurisdiction-specific rules and when to refuse. A software evaluation might check whether generated code handles the error paths, not just the happy path. The test set reflects your risk, not a leaderboard.

  • Domain question sets with expert reference answers
  • Scenario-based tests for multi-turn conversations
  • Agent tasks scored step by step, not only on the final result
  • Targeted sets for known weak spots or past failures

Rubrics and scoring

A score is only useful if you know what it measures. We agree rubrics with your team before scoring starts: correctness, safety, completeness, appropriate uncertainty, or whatever criteria matter for the task.

Experts score against the rubric and add short written comments where a number would hide something important. Where several experts score the same item, the level of agreement shows which results are firm and which reflect genuinely hard judgement calls.

Evaluating agents

Agents fail differently from chat models. A run can reach the right final state through an unsafe step, or stall because one tool call went wrong early.

Saolabs experts review agent trajectories action by action. They judge whether each step was reasonable, where the agent should have stopped or asked, and whether the outcome would be acceptable to a professional in that field.

How an evaluation engagement runs

We scope the domains, tasks and decisions the evaluation needs to support, then draft test items and rubrics with you. A pilot round shows how the scoring works in practice and lets us tighten the rubric.

We then match vetted experts and run the full evaluation, with expert review and quality checks. Delivery includes item-level scores, written comments and notes on known limits, such as areas the test set does not cover.

Questions, answered.

What is AI model evaluation?

AI model evaluation is the process of measuring a model's outputs against defined tests and criteria. It shows where a model performs well, where it fails, and whether a change has made it better or worse.

How is expert evaluation different from automated benchmarks?

Automated benchmarks score models quickly on fixed public datasets, which models can overfit. Expert evaluation uses specialists to write tests for a specific use case and to judge open-ended answers that automated scoring cannot assess reliably.

What is an evaluation rubric?

An evaluation rubric is a written set of criteria that defines what a good answer looks like, such as correctness, safety and completeness. It makes scores consistent across evaluators and tells you exactly what a score measures.

Can you evaluate AI agents?

Yes. Saolabs experts evaluate agent trajectories step by step, judging each action and tool call as well as the final outcome, and noting where the agent should have stopped or asked for help.

Which domains can Saolabs evaluate?

Saolabs evaluates model and agent outputs in medicine, law, finance, engineering, software, science, mathematics and languages, using vetted experts from each field.

Every safe modelhas an expert behind it.