Human model evaluation.
Structured human evaluation of model responses — safety, factuality, helpfulness, and instruction following — reviewed against your guidelines, not a generic rubric.
Response evaluation, grounded in your criteria.
Only capabilities Ayta can currently deliver or is genuinely prepared to pilot are listed below.
Response evaluation
Full model responses are reviewed end-to-end against your guidelines, not scored from isolated fragments.
Safety evaluation
Responses are checked for harmful, unsafe, or policy-violating content before anything is reported back to you.
Factuality
Claims in model output are checked against ground truth or source material you provide.
Helpfulness
Responses are judged on whether they actually solve the user's request, not just whether they're well-formed.
Instruction following
Responses are checked against the specific instructions in the prompt, not just general quality.
Need preference data for fine-tuning instead? See RLHF.
From guidelines to a scored dataset.
Every evaluation program follows the same operating sequence.
Guideline intake
Your rubric, edge cases, and pass/fail criteria are built into the evaluation protocol before review starts.
Rater calibration
Evaluators are trained and tested against your guidelines until their judgments are consistent with each other and with you.
Structured review
Every response is scored against the defined criteria — not a free-form impression.
Inter-rater agreement
Disagreement between raters is tracked and resolved, so scores reflect a consistent standard.
Delivery & reporting
Scored results are delivered on your schedule, with disagreement and edge cases flagged for your review.
Have a data requirement?
Give us the specification — we'll build the operation around it.
Start a Pilot →