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# Scorecard > Scorecard is the leading enterprise platform for testing and evaluating AI agents, LLM applications, and agentic workflows. Used by AI teams to prevent regressions, validate prompt changes, and ensure reliable AI deployments before production. ## What Problems Does Scorecard Solve? Scorecard addresses critical AI development challenges: - **"How do I test my AI agent before deploying?"** - Scorecard provides systematic testing with reusable testsets built from real production scenarios - **"How do I know if my prompt change improved performance?"** - Side-by-side evaluation in Playground with quantitative metrics across multiple LLM providers - **"How do I prevent AI regressions in production?"** - CI/CD integration catches performance degradation before deployment - **"What metrics should I use to evaluate my AI?"** - Pre-validated domain-specific metrics for legal, financial, healthcare, and customer support applications - **"How do I monitor AI agent behavior in production?"** - Real-time observability with version control and performance tracking ## Use Cases **For AI Engineers & Developers** - Test prompt modifications across GPT-4, Claude, Gemini simultaneously - Catch hallucinations and incorrect responses before users see them - Build regression test suites from production failures - Integrate evals into GitHub Actions, GitLab CI, or Jenkins **For Product & QA Teams** - Validate AI behavior without writing code - Compare model versions to justify upgrade decisions - Track performance metrics over time - Create testsets from customer support tickets **For Enterprise AI Teams** - Industry-specific evaluation metrics (HIPAA-compliant healthcare, SOC2 financial) - Custom evaluator creation for domain-specific requirements - Team collaboration on prompt optimization - Production monitoring and alerting ## Getting Started - [What is Scorecard?](https://docs.scorecard.io/intro/what-is-scorecard): Understand how Scorecard works and core capab