Scorecard

Scorecard is an AI testing and evaluation platform for teams building agents and LLM products. Simulate scenarios, compare changes, turn failures into reusable tests, and monitor production quality.

Desenvolvimento Agentes IA Ferramentas Dev IA AI Testing & QA

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Overview

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.

Core capabilities

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.

Test set management from real incidents

Capture production failures and convert them into reusable test cases for launch evaluation, hillclimbing, and regression testing.

Trustworthy metrics

Use a validated metric library, customize existing metrics, or create new ones to measure the behaviors that matter to your product.

Prompt Playground and A/B comparison

Prototype and compare different prompt or system versions in the Playground using actual requests before you ship changes.

Evaluation history and production monitoring

Track performance over time with run history and review incoming traces with real-time quality monitoring and custom reporting.

Human labeling and review

Let human raters score mission-critical launches when subject-matter judgment is required, with support for human labeling and ground-truth scoring.

Practical use cases

Pre-release agent validation
Evaluate an agent against many realistic scenarios before launch so teams can identify weak spots without waiting for production feedback.
Regression testing from real incidents
Turn production failures into reusable test cases and use them again during regression testing or hillclimbing as the system changes.
Prompt and model iteration
Compare prompt or model variants in the Playground using actual requests to decide which version should move forward.
High-stakes review workflows
Use human raters and ground-truth scoring when accuracy, judgment, or domain expertise matter more than automated scoring alone.
Production quality monitoring
Monitor incoming traces and track run history after deployment to spot quality issues and trends over time.

Pros and Cons

Pros

Focuses on realistic simulation rather than only log review or manual QA.
Supports reusable test cases, prompt versioning, and run history in one workflow.
Includes both automated metrics and human labeling for higher-stakes evaluation.
Offers a free Starter tier and a paid Growth plan, with Enterprise options for larger teams.

Cons

The public site does not provide a complete integrations catalog or platform compatibility matrix.
Some workflow details are described at a high level rather than as a step-by-step implementation guide.
The source does not show every pricing limit or usage cap beyond the plan summaries.

FAQ

How does Scorecard fit into an AI testing workflow?

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.

Who is Scorecard for?

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.

What does Scorecard help teams produce?

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.

What pricing options are available?

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.

What integrations does Scorecard support?

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.

Quick Facts

Category: AI testing and evaluation platform
Primary users: Teams building and shipping AI agents
Core workflow: Simulate scenarios, score behavior, turn failures into tests, and monitor production
Pricing: Starter $0/month, Growth $299/month, Enterprise custom pricing
Enterprise security: SAML SSO, SOC 2 reporting, end-to-end encryption
Website: scorecard.io