Scorecard

Scorecard is a platform designed to help teams build, test, evaluate, optimize, and ship enterprise AI agents, particularly LLM apps. It aims to deliver predictable AI experiences that improve with every update by providing tools for continuous evaluation, performance testing, and prompt management. Scorecard helps users understand how their AI models behave, catch problems early, fix them fast, and ensure AI agents work reliably in production. It addresses common challenges in AI development such as slow feedback cycles and silos between development and production by creating a continuous feedback loop.

How to Use

Scorecard allows users to test the performance of their AI agents against vetted metrics, create experiments to quickly test ideas in an AI laboratory, and manage/deploy agents to production. It facilitates a continuous feedback loop by connecting development, testing, and production environments, enabling users to see how models perform with real user requests. Users can gain live observability, version and store prompts, create trustworthy metrics, and validate performance through structured tests.

Key Features

• Evaluate and test AI agent performance against vetted metrics
• Continuous evaluation and live observability of AI behavior
• Version and store best-performing prompts in one place
• Create and customize trustworthy metrics for business needs
• Run structured tests for clear, actionable insights

Use Cases

• Building and testing LLM applications for predictable AI experiences
• Identifying and addressing real-world usage issues in AI agents
• Optimizing AI agent performance with fast feedback loops
• Managing and deploying AI agents to production confidently
• Creating a continuous feedback loop between AI development, testing, and production