Chroma provides a fast, serverless, and scalable search platform supporting vector, full-text, regex, and metadata search capabilities. This platform is built on object storage to offer low-latency queries over billions of multi-tenant indexes without requiring extensive engineering operations. It enables developers to build intelligent AI applications that can effectively know, learn, and search through complex datasets.
Funding
$18M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Developing AI applications requires managing diverse data types, including embeddings, documents, and metadata, which can be complex and inefficient when using separate systems. Existing solutions often lack a unified platform for vector search, full-text search, and multi-modal retrieval, leading to increased development overhead.
Solution
Chroma provides an open-source, unified database solution designed to simplify data management for AI applications. It integrates vector search, document storage, full-text search, metadata filtering, and multi-modal retrieval into a single platform. This integration streamlines the process of handling embeddings and diverse data types, reducing complexity for developers and enabling efficient data retrieval.
Target Audience
The primary users are AI application developers who need a streamlined, unified solution for managing and retrieving diverse data types, including embeddings, documents, and metadata.
Features
- Unified platform for vector search, document storage, full-text search, metadata filtering, and multi-modal retrieval
- Open-source under the Apache 2.0 License
- Python and JavaScript quick start guides
- Integrations for deploying Chroma to the cloud
- Support for full-text search and metadata filtering
- Ability to retrieve images with multi-modal capabilities