TLDR: Scorecard, a new evaluation platform, has officially launched, securing $3.75 million in seed funding. The platform is designed to dramatically accelerate the testing and deployment of AI agents by up to 100 times, addressing critical bottlenecks in current AI development workflows. It offers a robust solution for continuous, high-frequency evaluation in virtual environments, enabling developers to rapidly iterate and improve AI product performance.
San Francisco, CA – September 25, 2025 – Scorecard, an innovative AI agent evaluation platform, today announced its official launch, poised to revolutionize the development and deployment of artificial intelligence agents. The company claims its platform can accelerate the testing and deployment of AI agents by an unprecedented 100 times, a significant leap forward in the rapidly evolving AI landscape.
The launch is bolstered by a successful seed funding round, where Scorecard secured $3.75 million. The investment saw participation from prominent venture capital firms including Kindred Ventures, Neo, Inception Studio, and Tekton Ventures. Additionally, the round attracted angel investors from leading technology companies such as OpenAI, Apple, Waymo, Uber, Perplexity, and Meta, underscoring the industry’s confidence in Scorecard’s vision and technology.
Founded by Darius Emrani, an ex-Waymo Simulation Lead, Scorecard was born out of the need to democratize high-speed, large-scale testing for every AI team. Emrani’s experience highlighted the inefficiencies plaguing AI development.
The current state of AI agent development is often characterized by slow and error-prone testing processes. Manual evaluation typically involves writing custom scripts, curating datasets, and exporting results, a laborious process that can consume days or weeks and is susceptible to human error. This sluggish feedback loop not only delays feature rollouts but also obscures critical blind spots in an AI agent’s behavior, posing risks to compliance, security, and user trust. Without rapid, repeatable validation, teams struggle to confidently ship innovations or swiftly address production issues.
Scorecard directly addresses these challenges with its fully managed evaluation engine. The platform allows AI developers to define test suites in minutes, utilizing either a no-code API or an open-source TypeScript SDK. Users can script comprehensive, end-to-end scenarios, ranging from conversational prompts and compliance checks to performance benchmarks. The system is capable of executing tens of thousands of tests per day against live or staged AI agents within a virtual environment.
All test results are fed into an interactive dashboard, providing real-time metrics, detailed failure reports, and trend analysis. This comprehensive overview makes it effortless for teams to identify regressions, diagnose edge-case errors, and measure improvements over time, thereby enabling continuous iteration and performance enhancement.
Scorecard has already demonstrated its efficacy with key customers. Thomson Reuters, for instance, is leveraging Scorecard to test and deploy CoCounsel, their suite of professional-grade legal AI agents. Tyler Alexander, Director of AI Reliability at Thomson Reuters, commented on the partnership, stating, “At Thomson Reuters, the reliability and effectiveness of CoCounsel Core, our professional-grade legal AI assistant, are paramount. Scorecard enables us to scale our continuous evaluation efforts.”
The company’s technology empowers developers to continually test and “break” their AI agent products at high frequency in a virtual environment, fostering rapid iteration and performance improvement. Scorecard has already facilitated millions of tests for its customers, proving its capability to handle large-scale evaluation needs.
With millions of AI agents projected to be built and deployed across various sectors like legaltech, fintech, healthtech, and insurtech in the coming years, Scorecard positions itself as a crucial tool for ensuring the quality and reliability of these advanced systems.
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Developers interested in learning more or trying Scorecard can visit scorecard.io.
