Chroma

Chroma's valuation is not publicly disclosed.

Investor information for Chroma is not publicly available at this time.

No public funding round data is currently available for Chroma.

Chroma has approximately 1-50 employees.

Chroma builds an open-source AI-native vector database designed specifically for storing, indexing, and querying the high-dimensional embeddings that power retrieval-augmented generation (RAG) systems, semantic search, and LLM memory layers. The database is designed to be simple to embed in Python applications with minimal configuration, making it the default choice for developers prototyping AI products.\n\nThe company raised approximately 18 million USD and has accumulated significant open-source adoption among AI developers building LLM applications who need a lightweight, locally runnable vector store that can also scale to cloud deployments. Chroma usage grew rapidly in parallel with the LangChain ecosystem, where it became a default integration for document retrieval workflows.\n\nVector databases are foundational infrastructure for the retrieval-augmented generation architecture that dominates production LLM application design. Chroma competes with Pinecone, Weaviate, Qdrant, and Milvus, and while it faces stronger enterprise competition from well-funded rivals, its developer-first positioning and open-source distribution give it deep penetration at the prototyping stage where tool choices frequently persist into production.