Systematic quality grading for LLM outputs
Prompt Evaluation
Expert evaluation of LLM outputs for quality, safety, and alignment across your model's real-world use cases.
Overview
What is Prompt Evaluation?
Prompt evaluation is systematic expert grading of model outputs against rubrics for helpfulness, accuracy, safety, and style — the feedback loop that tells you whether your model is actually improving.
Why it matters: Benchmark scores don't tell you how a model performs on your real user prompts. Structured human evaluation is the only way to know if a fine-tune, prompt change, or model swap actually helped.
Custom Rubrics
Multi-dimensional scoring built around your model's specific goals
Domain Evaluators
Subject-matter experts matched to your use case and industry
Rationale Capture
Every score includes written rationale, not just a number
Failure Analysis
Systematic pattern detection across low-scoring outputs
Workflow
How We Do It
01
Rubric Design
We collaboratively design multi-dimensional evaluation rubrics — helpfulness, accuracy, safety, style.
02
Evaluator Selection
Domain-expert evaluators matched to your use case are recruited and calibrated.
03
Calibration Sessions
Structured calibration with gold examples aligns evaluator judgment across the panel.
04
Evaluation
Evaluators score outputs against your rubric with rationale documentation.
05
Reporting
Delivered as structured scores plus a summary report of systematic failure modes.
Case Study
Enterprise LLM Vendor
Enterprise LLM Vendor
Evaluate model output quality across 8 enterprise use cases
Solution
Custom rubric per use case with domain-expert evaluator panels and weekly reporting
Results
50K
Outputs evaluated
8
Use cases covered
0.86
Evaluator agreement
Ready to Get Started with Prompt Evaluation?
Tell us about your project and we'll scope a pilot within 48 hours.