Quickstart
Prove one task end to end: run a set of models on your data, rank the cheapest one that clears your quality bar, and share a proof. Pick a surface above, or compare all three.
1. Describe the task and give a few examples
A task is a plain-language instruction plus a few example inputs (and, if you have them, the correct outputs to score against).
No labeled data? Set reference_source: "incumbent" to score every challenger against your current model's own output. You prove which config is cheaper at equal-or-better quality without labeling a thing: the incumbent's output is the reference.
Open app.redcrown.ai, land on Prove, paste your task and a few example rows, then choose "Use my data".
redcrown build-dataset --from-csv examples.csv --task summarize \
--input-col text --reference-col summary --out task.jsonprove_task({
"task": "Summarize each support ticket in one sentence.",
"examples": [{"input": "...", "output": "..."}]
})2. Run every candidate and rank them
RedCrown fans the task across the candidate models, scores each against your references, and ranks by the cheapest that clears the bar.
The Prove screen runs the candidates and shows the ranked report with cost, quality, and receipts.
redcrown eval task.json --report-json out.jsonprove_task runs the eval and returns the ranked winner and savings in one call. For a demo with no data, use try_sample.
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