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AI search infrastructure and vector database

Chroma

Chroma builds open-source search infrastructure that helps developers supply AI applications with relevant documents and data. Its database supports vector similarity, lexical, full-text, regex, and metadata search. Developers can run it on their own infrastructure or use Chroma Cloud, its managed serverless service. Chroma Sync automates ingestion, including chunking, embedding, and indexing GitHub repositories and web pages. Customers use Cloud for documentation search, code search, and code review agents.

Founded in 2022 by Jeff Huber, its CEO, and Anton Troynikov, Chroma combines database engineering with research into retrieval and context management. Its search architecture uses object storage with automatic data tiering and caching. The Context Rot study tested 18 language models while holding task complexity constant, finding inconsistent performance as input length increased. Its Context-1 search model applies context management during iterative retrieval: it breaks questions into subqueries, discards irrelevant results, and returns ranked supporting documents to a separate answering model.

In 2026, the company reported use in over 90,000 open-source GitHub codebases, a measure of its developer ecosystem. Chroma raised an $18 million seed round led by Quiet Capital in 2023.

www.trychroma.com

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Affiliations reflect their AIE appearances, not necessarily current employment.

Company sources · checked 2026-08-27