Core capability
AI Evaluation & Benchmarking
Measure what matters. Custom benchmarks, golden sets, rubric design and human preference evaluation that show exactly how your models perform — and where they fail.
Problems we solve
When teams bring us in
- Public benchmarks do not reflect your product, users or domain.
- You cannot tell whether a new model or prompt is actually better.
- RAG, search or agent quality is judged by anecdote instead of evidence.
What you receive
Deliverables
- Custom benchmark and golden set built around your use case
- Evaluation rubric with scoring definitions
- Model-to-model comparison results with failure categories
- Evaluation report with prioritized recommendations
What we do
Capabilities
- LLM Evaluation
- AI Model Benchmarking
- Model-to-Model Comparison
- Human Preference Evaluation
- Pairwise Ranking
- Response Quality Evaluation
- Factuality Evaluation
- Grounding Evaluation
- RAG Evaluation
- Agent Evaluation
- AI Search Evaluation
- Recommendation Evaluation
- Multilingual Evaluation
- Cultural / Localization Evaluation
- Regression Testing
- Continuous Evaluation
- Custom Benchmark Creation
- Golden Set Creation
- Evaluation Rubric Design
Quality
How we keep results reliable
- Rubric piloting before full runs
- Evaluator calibration and agreement checks
- Blind / pairwise comparison where relevant
- Traceable evidence for each finding
Related programs
Fixed-scope ways to start
- LLM Benchmark Program
Custom benchmark creation + human evaluation + comparative model testing.
- RAG Evaluation Sprint
Test retrieval quality, grounding, factuality and response quality.
- AI Model Health Check
A rapid evaluation of an AI system across accuracy, consistency, safety and failure modes.
Scope your ai evaluation & benchmarking project
Send us what you are building. We will scope the data, evaluation, benchmarking or testing program and come back with a proposal.