Scorecard
Evaluate, Optimize, and Ship AI Agents
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Scorecard is an evaluation platform for teams building AI agents in high-stakes domains. It combines automated LLM-based evaluations, structured human feedback, and real product signals into one loop so an agent's quality can be measured and improved systematically before and after release.
Rather than shipping and hoping, teams define what good output looks like, run agents against test cases, collect reviewer judgements, and track whether changes actually help, closing the gap between a demo and a reliable production system.
It is aimed at engineering and product teams in areas like healthcare, finance, and law, where an agent's mistakes carry real cost and confidence in behaviour has to be earned with evidence.
AI-assisted draft, human-reviewed before publishing — see how we choose & review tools.
Why we picked it
Scorecard made the cut for combining automated evals with structured human feedback and real product signals in one loop — for high-stakes agent deployments specifically, no single signal alone is trustworthy, and naming that combination is the actual reason to pick it.
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