Reprose is building the missing interface between product teams & ML engineers in the model improvement loop.

Today’s LLM evaluation tools are skewed toward developers. Product teams rely on spreadsheets and static criteria documents that are hard to scale and maintain. Evaluation standards quickly become stale and fail to measure LLM performance.

Thematic clustering

Group model responses by topic, scenarios, or confidence level to reduce review time and surface patterns faster.

Edge case fine tuning

Target specific examples where the model misbehaves. Annotate, adjust, and track improvements without rerunning full evals.

Memory & Traceability

Every edit and judgment updates future evaluation logic. Each review teaches the system how to evaluate future responses.

Waitlist signup

Reprose

Funnel feedback into better models.

Today’s LLM evaluation tools are skewed toward developers. Product teams rely on spreadsheets and static criteria documents that are hard to scale and maintain. Evaluation standards quickly become stale and fail to measure LLM performance.

Thematic clustering

Group model responses by topic, scenarios, or confidence level to reduce review time and surface patterns faster.

Edge case fine tuning

Target specific examples where the model misbehaves. Annotate, adjust, and track improvements without rerunning full evals.

Memory & Traceability

Every edit and judgment updates future evaluation logic. Each review teaches the system how to evaluate future responses.

Waitlist signup

Reprose

Funnel feedback into better models.

Today’s LLM evaluation tools are skewed toward developers. Product teams rely on spreadsheets and static criteria documents that are hard to scale and maintain. Evaluation standards quickly become stale and fail to measure LLM performance.

Thematic clustering

Group model responses by topic, scenarios, or confidence level to reduce review time and surface patterns faster.

Edge case fine tuning

Target specific examples where the model misbehaves. Annotate, adjust, and track improvements without rerunning full evals.

Memory & Traceability

Every edit and judgment updates future evaluation logic. Each review teaches the system how to evaluate future responses.

Waitlist signup

Reprose

Funnel feedback into better models.