Evaluation Infrastructure & Tooling

Building the foundational infrastructure to support rigorous AI evaluation research. We are developing standardized formats, tooling, and frameworks that enable researchers to conduct reproducible evaluations, share results, and build upon each other's work. Our infrastructure efforts focus on creating interoperable systems that work across different evaluation frameworks and benchmarks. This includes developing schemas for storing evaluation metadata, APIs for accessing and sharing results, and tools that simplify the evaluation lifecycle from setup to analysis. By providing robust infrastructure, we aim to reduce the technical barriers to conducting high-quality evaluations, eliminate redundant computational effort, and accelerate the pace of evaluation science research across the community.