Ranking · Factuality · Safety
Generative AI Evaluation
Structured human evaluation for prompts, responses and conversational AI systems.
What we operate
A workflow shaped around your data and quality bar.
Evaluation programs translate product goals into review rubrics, calibrated examples and repeatable judgment across response quality, relevance, factuality and safety.
Prompt-response reviewPreference rankingFactuality reviewSafety reviewRed-teaming supportOutput quality evaluation
Operations in practice
Depth where the workflow needs it.
Each focus area stays connected to the same calibration, production, escalation and quality structure.
01Response quality
Evaluation of relevance, clarity, instruction following and overall usefulness against an explicit rubric.
02Preference and ranking
Calibrated comparison of candidate outputs to capture nuanced human preference signals.
03Factuality and safety
Targeted review for unsupported claims, policy risks and domain-specific failure modes.
Workflow
From requirements to reviewed delivery.
The exact sequence adapts to the project, while readiness, calibration and issue resolution remain explicit.
Build calibration examples
Qualify evaluators
Evaluate and adjudicate
Report issue patterns without inventing performance claims
Applications
Where this capability fits.
LLM evaluation
Assistant quality
Search relevance
Response safety
Domain-specific review
Discuss a representative pilot
Bring the workflow, a sample and the decisions that matter. We’ll respond with practical next steps without assuming scope or inventing estimates.
Start a Pilot