Exa AI Research Blog | Semantic Search & Neural Network Search Engine

Exa has introduced its Company Search Benchmarks to enhance the precision of AI-driven company searches, expanding on its existing People Search Benchmark. This initiative aims to differentiate the retrieval model's capabilities from memorized knowledge by focusing on fresh, structured data rather than well-known entities. The benchmark involves a dataset comprising diverse company attributes like founding year, location, and funding history, specifically avoiding prominent unicorns. It evaluates both static and dynamic facts, requiring different assessment approaches, and includes a retrieval track to ensure systems return accurate company results for various query types. By open-sourcing the dataset and evaluation harness, Exa seeks to foster advancements in retrieval research, promoting a comprehensive evaluation ecosystem across different entity types and search domains in line with its mission to build perfect search.