Simulation-based testing
Run agents through thousands of realistic scenarios and get results in minutes, which is positioned as a faster alternative to waiting on manual review cycles.
Scorecard è una piattaforma di test e valutazione AI per team che sviluppano agenti e prodotti LLM.
Scorecard is a simulation and evaluation platform for building and testing AI agents. It is designed to help teams replace spreadsheet-based, subjective QA with structured testing, reusable scenarios, and clearer metrics.
The product centers on a fast feedback loop: run agents through realistic scenarios, score their behavior, turn production failures into tests, and compare changes before deployment. The site also positions Scorecard as useful for prompt management, evaluation, and production quality monitoring.
Run agents through thousands of realistic scenarios and get results in minutes, which is positioned as a faster alternative to waiting on manual review cycles.
Capture production failures and convert them into reusable test cases for launch evaluation, hillclimbing, and regression testing.
Use a validated metric library, customize existing metrics, or create new ones to measure the behaviors that matter to your product.
Prototype and compare different prompt or system versions in the Playground using actual requests before you ship changes.
Track performance over time with run history and review incoming traces with real-time quality monitoring and custom reporting.
Let human raters score mission-critical launches when subject-matter judgment is required, with support for human labeling and ground-truth scoring.
Evaluate an agent against many realistic scenarios before launch so teams can identify weak spots without waiting for production feedback.
Turn production failures into reusable test cases and use them again during regression testing or hillclimbing as the system changes.
Compare prompt or model variants in the Playground using actual requests to decide which version should move forward.
Use human raters and ground-truth scoring when accuracy, judgment, or domain expertise matter more than automated scoring alone.
Monitor incoming traces and track run history after deployment to spot quality issues and trends over time.
Scorecard is designed to run and evaluate agents through realistic scenarios, track performance, and turn failures into reusable test cases. The product page emphasizes prompt testing, evaluation, Playground usage, and production monitoring, but does not spell out a step-by-step onboarding process.
The source highlights teams building and testing AI agents, including product teams, engineers, and companies working on legal, fintech, compliance, healthcare, and chatbot use cases. Its About page says the company focuses on helping teams replace subjective reviews with structured testing.
Scorecard shows prompt Playground access, test set management, human labeling, run history, A/B comparison, and real-time quality monitoring in the product and pricing pages. These outputs support experimentation, regression testing, and production scoring.
The pricing page lists Starter, Growth, and Enterprise plans. Starter is shown at $0/month, Growth at $299/month, and Enterprise uses customized pricing with sales contact for a demo.
The source does not provide a detailed integrations list. It does say Scorecard can be integrated into production deployments and that it supports SAML SSO for Enterprise customers.
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