The eval that
actually reflects users.
Multi-rubric scoring with PhD reviewers, calibrated per dimension. Side-by-side comparisons, free-form rationales, and per-rater quality metrics — usable for release gates and model selection.
Built for production, not just demos.
- Per-rubric scoring (helpful, accurate, safe, concise, style, citation)
- Side-by-side and N-way model comparison
- Free-form rationale + tagged failure modes
- Domain-expert reviewers (MD, JD, PhD-CS, PE, tax)
- Multilingual evaluation across 60+ languages
- Adversarial probe-set evaluation
- Per-rater quality + calibration dashboards
- Integration with HELM, MT-Bench, custom suites
How a typical engagement runs.
Rubric
Define dimensions, anchor examples, and scale (Likert / pair-wise / N-wise).
Calibrate
Reviewers complete 50 gold tasks per rubric; tune anchors based on misses.
Pilot
500 evaluations with per-rater IAA and rubric drift analysis.
Production
Scale to weekly batches with API + dashboards + adjudication queue.
Release Gate
Pre-release evaluation packs to certify model versions against your bar.
What you get in your bucket.
Questions, answered.
What's the IAA target?
We aim for >0.78 inter-annotator agreement on hard rubrics. For subjective rubrics (style, tone), we use multi-rater majority and report distribution.
Can you compare against OpenAI / Anthropic baselines?
Yes — we run head-to-head A/B with the same rubric against any vendor model you have API access to.
How fast can a release-gate eval run?
For a 1k-prompt gate against 4 rubrics, end-to-end including QA takes 2-3 business days. Smaller gates within 24h.
Do you publish results?
By default everything is private to you. We do publish anonymised methodology + aggregate statistics for benchmark transparency on opt-in.
Ready to build
AI you can trust?
Talk to a solutions architect — get a pilot scoped in 48 hours.