Scorecard
Scorecard is an AI evaluation and simulation platform that helps LLM and agent development teams test, measure, and improve AI system behavior using simulation-based testing, validated metrics, and OpenTelemetry tracing. It serves enterprise AI teams including Thomson Reuters via a freemium SaaS model.
- Company typePrivate
- Founded-
- HeadquartersSan Francisco, United States
- Headcount11–50
- GTM typeB2B
- OfferingSoftware
What Scorecard does
Scorecard Technologies, Inc. is a San Francisco-based AI evaluation and simulation platform that helps teams developing LLM-powered agents test, measure, and improve system behavior before and after deployment. The product spans a visual Playground for iterating prompts against testcases, a validated metric library with customizable templates for hallucination detection, PII leakage, coherency, and other quality dimensions, OpenTelemetry-based tracing with flame graph visualizations, multi-turn Sim Agents for conversation simulation, A/B comparison, production Online Evaluations, and dedicated MCP server evaluation via MCPEvals.ai. The platform is delivered through a web application (app.getscorecard.ai), Python and Node.js SDKs, an official MCP server (the 28th registered), GitHub Actions integration, and a Vercel AI SDK wrapper, with a self-serve freemium motion complemented by enterprise sales.
The company monetizes via tiered SaaS subscriptions — a free tier with a default Gemini Flash API key, a Growth plan available at no cost for up to 12 months through the Anthropic partnership (with up to $10,000 in evaluation credits), and an Enterprise plan with SOC 2 compliance, custom endpoints, and advanced collaboration on annual contracts. Customer evidence includes Thomson Reuters as a named enterprise, an unspecified set of "multi-billion dollar customers" per the company's careers page, and case studies showing 87% accuracy / 56% improvement over previous solutions in DOM-parsing evaluations. The company raised $3.75M in seed funding in September 2025 led by Kindred Ventures, with participation from Sheryl Sandberg, Inception Studio, Neo, and Tekton Ventures, and is led by CEO and founder Darius Emrani, who previously led evaluation of the self-driving system at Waymo.
Scorecard firmographics
Firmographics- Name
- Scorecard
- Legal name
- Scorecard Technologies, Inc.
- Website
- https://scorecard.io
- Company type
- Private
- Operating status
- Operating
- Headcount range
- 11–50 employees
- Short description
- Scorecard is an AI evaluation and simulation platform that helps LLM and agent development teams test, measure, and improve AI system behavior using simulation-based testing, validated metrics, and OpenTelemetry tracing. It serves enterprise AI teams including Thomson Reuters via a freemium SaaS model.
- Ownership category
- akta.pro rank
Scorecard industry classification
Industry- Product category
- AI Evaluation Software
- NAICS
- Greeting Card Publishers (513191)
- SIC
- Services-Prepackaged Software (7372), Services-Testing Laboratories (8734)
- akta.pro primary industry
- RLHF, Human Feedback & Evaluation Data Tools (HDAAALAJ)
- akta.pro secondary industry
- Data Labeling & Annotation Services (HDAAALAB)
Keywords
Where Scorecard is headquartered
LocationHeadquarters
- HQ city
- San Francisco
- HQ country
- United States
- HQ region
- North America
Offices1 record
Markets served
Scorecard business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Marketing or Sales, Infrastructure
Revenue model
- SaaS Platform Subscription: Scorecard operates as a SaaS platform with subscription-based pricing. The platform offers a free tier for new organizations with default API keys (Gemini Flash), and paid Growth and Enterprise plans. Revenue is generated through recurring subscriptions with automatic renewal.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Freemium | Others | Free tier with basic features |
| Subscription | Annual | Growth plan with comprehensive evaluation features |
| Subscription | Annual | Enterprise plan for large organizations |
Go-to-market motion2 records
Distribution channels5 records
Marketing channels7 records
Scorecard product offering
Product offeringCore offering
Scorecard provides an AI evaluation and simulation platform that enables development teams to test, score, and monitor large language model (LLM) agents before and after production deployment. The platform combines a visual Playground, validated metric templates, OpenTelemetry-based tracing, multi-turn simulation with Sim Agents, and SDK-based programmatic access to deliver fast feedback loops for agent development.
Product overview
Scorecard is an AI evaluation and simulation platform designed to help teams test, evaluate, and improve AI agents. The platform operates on the principle that 'you can't QA your way to the frontier' - instead, self-improving agents need realistic simulation and encoded expert judgment. The core platform includes the Playground for visual testing, Metrics for evaluation with AI/LLM-as-judge scoring, Tracing for OpenTelemetry-based observability, Runs & Results for execution, Records for consolidated result analysis, Testsets for test case management, and Prompts for version control. Additional modules include Multi-turn Simulation with Sim Agents, A/B Comparison, Synthetic Data Generation, Custom Endpoints, AI Guardrails, Custom LLM Providers, and GitHub Actions integration. The platform offers Python and JavaScript SDKs and an official MCP Server for integration with AI tools. A dedicated MCPEvals.ai platform supports MCP server evaluation, while Online Evaluations enables production monitoring.
Differentiator
Problem solved
Functional benefit
Products and services
- Scorecard Platform SaaS platform for AI evaluation and simulation that lets teams test, score, and monitor LLM agents across thousands of realistic scenarios; includes Playground, Metrics, Tracing, Runs, Records, Testsets, Prompts, A/B Comparison, Multi-turn Simulation, Custom Endpoints, Synthetic Data Generation, AI Guardrails, Online Evaluations, and SOC 2-aligned enterprise features.
- Scorecard Python SDK Python package (pip install scorecard-ai) providing programmatic access to Scorecard's API for projects, testsets, testcases, metrics, runs, records, scores, systems, and system versions, with Bearer token authentication and helper methods such as run_and_evaluate.
- Scorecard JavaScript/TypeScript SDK JavaScript/TypeScript package (npm install scorecard-ai) providing programmatic access to all Scorecard API endpoints with full TypeScript support and ergonomic helpers such as runAndEvaluate for CI/CD-driven evaluation workflows.
- Scorecard MCP Server Official Model Context Protocol server (registered as the 28th MCP server) that exposes Scorecard's evaluation capabilities inside AI assistants such as Claude.ai and Cursor, accessible via https://mcp.scorecard.io.
- MCPEvals.ai Dedicated platform for evaluating Model Context Protocol servers using AI-generated tests and standardized performance metrics, paired with open-source evaluation tools on GitHub.
- Vercel AI SDK Wrapper Wrapper for Vercel AI SDK that adds Scorecard evaluation and monitoring to AI applications built with Vercel AI SDK, requiring minimal code changes for instrumentation.
Quantifiable outcome
- Enables developers to run tens of thousands of tests daily and ship trusted AI 100x faster
- +2 more outcomes
Companies that use Scorecard
Customer profileNamed customers3 records
Segments3 records
Ideal customer profiles1 record
Scorecard technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration6 records
AI capability8 records
Feature7 records
Scorecard partnerships and signals
Strategic signalPartnerships
One partnership is on record.
- AnthropicflagshipPartnership providing eligible companies with up to $10,000 in joint evaluation credits plus free access to Scorecard Growth plan for up to 12 months. Designed to help organizations make data-driven decisions about AI tooling and compare Claude models against existing AI solutions.
Scale indicators3 records
Recent moves6 records
Expansion highlights6 records
Scorecard competitors and assessment
Company assessmentBroad incumbents
- Weights & Biases: Weights & Biases is an established ML platform with Weave for LLM tracing and evaluation, serving as a broader incumbent in ML experiment tracking, observability, and evaluation. It overlaps with Scorecard on LLM evaluation and tracing but serves a much wider ML workflow.
- Honeycomb.io: Honeycomb provides observability and tracing for production systems with OpenTelemetry support. While not LLM-specific, it competes for the same observability budget as Scorecard's tracing product, especially among enterprises standardizing on OTel.
- Datadog (LLM Observability): Datadog has expanded into LLM observability with native tracing and evaluation features. As a broad observability incumbent, it competes for the same monitoring and evaluation budgets and could absorb evaluation workloads into its existing platform.
Direct peers
- Arize AI: Arize AI provides LLM observability and evaluation infrastructure for AI applications, including tracing, evaluation metrics, and production monitoring. It directly competes with Scorecard in the AI agent evaluation and observability category.
- LangSmith: LangChain's LangSmith is a direct competitor offering LLM application evaluation, tracing, and monitoring. It targets the same AI engineering and product teams building with LLMs and supports similar workflows around testing, prompt iteration, and production observability.
- Braintrust: Braintrust is an AI evaluation platform offering prompt versioning, test cases, scoring, and production monitoring for LLM applications. It targets the same developer and enterprise personas with overlapping evaluation and tracing features.
- Patronus AI: Patronus AI is an LLM evaluation and observability platform focused on hallucination detection, safety, and quality monitoring. It competes with Scorecard in automated evaluation metrics and production monitoring for enterprise AI deployments.
- Confident AI (DeepEval): Confident AI commercializes DeepEval, an open-source LLM evaluation framework, offering metric libraries, test management, and CI/CD integrations. It is a direct competitor in LLM evaluation with overlap in metric templates and test case management.
- Maxim AI: Maxim AI provides an evaluation and observability platform for LLM applications, supporting simulation, agent evaluation, and tracing. It is a direct peer in the AI agent testing and evaluation space, particularly for multi-turn workflows.
Emerging players
- Helicone: Helicone is an observability and monitoring layer for LLM applications, offering logging, evaluation, and prompt management. It overlaps with Scorecard's tracing and monitoring capabilities but is positioned primarily as a logging and gateway layer.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat5 records
Key risks6 records
Key highlights7 records
Customer concentration
Scorecard social profiles
Digital presenceScorecard compliance and trust
Trust signalCompliance1 record
Scorecard financial estimates
Financial estimateRevenue estimate
Valuation estimate
Scorecard leadership team
Management profileNumber of profiles
Profiles1 record
Scorecard funding detail
Funding detailFunding overview
Funding rounds1 record
Investors4 records
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Scorecard M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about Scorecard
What does Scorecard do?
Scorecard provides an AI evaluation and simulation platform that enables development teams to test, score, and monitor large language model (LLM) agents before and after production deployment. The platform combines a visual Playground, validated metric templates, OpenTelemetry-based tracing, multi-turn simulation with Sim Agents, and SDK-based programmatic access to deliver fast feedback loops for agent development.
Is Scorecard a public or private company?
Scorecard is a private company. It is classified as venture growth investor backed and is currently operating.
When was Scorecard founded?
Scorecard was founded in -1. It employs 11 to 50 people.
Where is Scorecard based?
Scorecard is headquartered in San Francisco, United States, in the North America region.
How does Scorecard make money?
One revenue line is on record: saaS Platform Subscription.
Who are Scorecard's main competitors?
Broad incumbents on record are Weights & Biases, Honeycomb.io and Datadog (LLM Observability). Direct peers are Arize AI, LangSmith, Braintrust, Patronus AI, Confident AI (DeepEval) and Maxim AI. Helicone is listed as an emerging player.
Does Scorecard have an API?
Yes. Scorecard provides a REST API for programmatic management of projects, testsets, testcases, metrics, runs, records, scores, systems, and system versions. Available SDKs in Python (pip install scorecard-ai) and JavaScript/TypeScript (npm install scorecard-ai). The SDKs support endpoints for creating, listing, updating, and deleting across all entities, with pagination support and Bearer token authentication. Developer documentation is at docs.scorecard.io/api-reference/overview.
What industry is Scorecard in?
Scorecard's product category is AI Evaluation Software. Its primary akta.pro industry code is HDAAALAJ, RLHF, Human Feedback & Evaluation Data Tools, with a secondary code of HDAAALAB, Data Labeling & Annotation Services. Its NAICS code is 513191 and its SIC code is 7372.