Use case - PM, Domain experts, Engineering
Structure human expert reviews.
Turn feedback into reusable memory
Put humans in the loop on your AI traces. Capture expert judgment as reusable data while a copilot speeds grading with end-to-end context.
Across every review
How a review flows
From a shared standard to reusable ground truth.
Set the standard once, run traces through the loop, and every correction feeds back on its own.
Define the standard
In Rubric Studio you set the dimensions to grade, a scoring type for each, and good, bad, and ambiguous examples from real traces. One rubric guides every reviewer, and later calibrates your judge.
Route & grade
Queues hand traces to the right reviewers, rubric attached. Reviewers score each dimension in an in-built workbench, set rationale, and edit the answer inline. The copilot drafts the correction and rationale with full context.
Reuse every correction
No review is a one-off. Each correction is distilled into memory that shortens the next similar case, and flows straight into judge calibration and regression datasets.
Review Copilot
A copilot that grades with the full picture.
Grounded in the same rubric it grades against, so its help always matches your standard.
Knows
Outcomes
Every review makes the next one easier.
The value shows up after the first review, and compounds from there.
Consistent standards
A shared rubric enable reviewers to reach the same verdict on the same trace.
Trustworthy ground truth
A reviewer-agreement score tells you whether the standard is solid, or ambiguous enough to fix before you build on it.
Faster reviews
The copilot drafts rationales and corrections with full context, so reviewers approve instead of writing from scratch.
Reusable memory
Each correction is distilled into memory that shortens the next similar review, so review effort compounds instead of repeating.
Judges & datasets
The same rubric calibrates an LLM judge, and every correction becomes a regression test case.
History that survives
Versioned rubrics keep past grades intact, and every review stays in DataFramer when a reviewer moves on.
Stop losing expert judgment to one-off reviews.
Free to start, no card required. Bring your own model key or use DataFramer credits.