Pipevals is the visual pipeline builder for evaluation-driven AI development.

Build evaluation graphs. Run them against datasets. Track quality over time.

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The Vibe Check

Most teams evaluate AI by eyeballing results. It works until it doesn't — and you won't know when it stops working.

The Compound Error

95% accuracy per step sounds great. Over 10 steps, that's 60% accuracy overall. The pipeline is only as good as its weakest link.

The Eval Gap

Everyone agrees you need evaluation pipelines. Somehow, you're still expected to build them from scratch.

Build. Run. Measure.

01

Build

Drag steps onto a canvas and wire them together. Call models, reshape data, capture scores, or pause for human review — all without writing orchestration code.

02

Run

Trigger pipelines one at a time or batch them against a dataset. Each item runs through the full graph, durably, with step-by-step results you can inspect after.

03

Measure

See where quality stands and where it's headed. Trend charts, score distributions, step durations, and pass rates — all populated automatically from your pipeline runs.

Start in minutes, not sprints.

AI-as-a-Judge

Trigger

Generator

Judge

Metrics

Score any model's output with an LLM judge.

Model A/B Comparison

Trigger

↓    ↓

Model A   Model B

↓    ↓

Collect Responses

Judge → Metrics

Compare two models head to head.