Evaluation data.
Know what your models can do.
Develop custom evaluation datasets and assessment criteria around the capabilities, challenges, and real-world tasks that matter to your research.
Discuss a Data PartnershipTraining teaches.
Evaluation measures.
Training data helps models learn. Evaluation data helps us understand how well they perform.
We work with AI developers to create evaluation datasets that assess specific capabilities, identify weaknesses, and measure performance against defined criteria.
From professional workflows to complex reasoning tasks, evaluations can reveal where models succeed, where they struggle, and where further development is needed.
Specify what
success means.
Evaluation task development
We work with you to develop realistic evaluation tasks around the capabilities and challenges you want to assess, including professional workflows, complex reasoning, and real-world scenarios.
Reference outcomes and scoring rubrics
Establish clear expectations for successful performance through reference outcomes, evaluation criteria, and scoring rubrics tailored to your research objectives.
Expert assessments and human evaluation
Bring human expertise into the evaluation process through professional assessments, qualitative feedback, comparative judgments, and structured review.
Evaluate the capabilities
that matter.
Explore the types of evaluation data and assessment materials we can develop around your research needs.
Professional workflow evaluations
Realistic task scenarios that assess how AI systems perform across professional workflows, including multistep processes, exceptions, and domain-specific requirements.
Agent performance evaluations
Evaluation tasks designed to assess how AI agents use tools, follow instructions, complete tasks, and respond to changing conditions.
Targeted failure-mode evaluations
Specialized evaluation sets that test model weaknesses, edge cases, challenging scenarios, and situations where expected behavior is difficult to determine.
Evaluation projects are developed around your research objectives and agreed delivery requirements.
Let’s define the data
your model needs.
Discuss your target capabilities, data requirements, and evaluation objectives with Streamlytics.