Scorecard: Building Reliable AI Through Continuous Evaluation

Scorecard is a powerful AI performance platform that helps teams evaluate, optimize, and ship enterprise-ready AI agents with confidence. It transforms the way organizations develop large language model (LLM) applications by ensuring every version improves through data-driven testing, evaluation, and feedback.

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Scorecard: Building Reliable AI Through Continuous Evaluation

Introduction

What Is Scorecard?

Scorecard is an integrated platform created to help AI teams build and maintain predictable, high-performing agents. Designed for enterprise use, Scorecard connects every stage of AI development—design, testing, and production—into a single feedback loop.

At its core, Scorecard enables continuous evaluation of AI performance. Teams can test agents against vetted metrics, observe real-time behavior, and detect performance drift before it impacts end users. By combining observability, evaluation, and experiment management, Scorecard ensures that every AI agent shipped performs reliably and consistently in production.

Unlike traditional testing tools, Scorecard eliminates the long feedback cycles and communication silos that often slow down AI development. With automated monitoring and customized metrics, teams can fix issues quickly and push improvements continuously—delivering better, more predictable AI experiences.

How to Use Scorecard

Using Scorecard is straightforward and highly adaptable to different AI workflows. After integrating your LLM or AI agent, you can begin evaluating performance against pre-validated or custom-built metrics.

Scorecard allows teams to:

  • Run structured tests to compare AI models and analyze output quality.
  • Create experiments in a dedicated AI laboratory to test new ideas rapidly.
  • Gain live observability into real-world usage and model behavior.
  • Version and store prompts to maintain consistency across deployments.
  • Validate AI performance through transparent, measurable testing results.

This process closes the loop between development and production. By continuously collecting real-world feedback, Scorecard helps teams understand how models behave in the wild and make evidence-based improvements that translate into business results.

Core Features of Scorecard

1. Evaluate and Test AI Agent Performance

Scorecard enables detailed analysis of how AI agents perform using vetted, trustworthy metrics. Teams can assess reasoning accuracy, response quality, and other business-critical outcomes to maintain consistent standards.

2. Continuous Evaluation and Live Observability

With Scorecard, users gain ongoing visibility into AI behavior in production. This feature ensures early detection of anomalies and rapid response to issues before they escalate.

3. Version and Store Prompts

Scorecard acts as a central hub for all prompt versions, allowing teams to store, compare, and retrieve their best-performing prompts. This organized prompt management creates a single source of truth for the entire organization.

4. Custom Metrics for Business Needs

Every business has unique success indicators. **Scorecard