Chroma Inc.
Chroma builds memory for AI applications through an open-source embedding database that makes knowledge, facts, and skills pluggable for large language models, enabling developers to build AI applications with semantic search and retrieval capabilities.
At a Glance
- AI/ML developers and engineers
- Software developers building LLM applications
- Enterprises implementing AI solutions
- Startups building on GPT-4 and other LLMs
- +8 more
AI Tools by Chroma Inc.
(1)Chroma
Open Source AI Search Database
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Latest News
Chroma announces seed funding round
Chroma raises $18M seed round led by Quiet Capital at $75M valuation
Chroma releases Version 0.4.0
Chroma reaches major milestone: More than one million computers ran its vector database in October 2023
Products & Services
AI-native open-source embedding/vector database designed for building LLM applications with memory and retrieval capabilities. Provides vector, full-text, regex, and metadata search. Available under Apache 2.0 license for local development and self-hosted deployments.
Fully-managed serverless search database backed by Chroma Distributed, an Apache 2.0 serverless database written in Rust. Features automatic query-aware data tiering, cold and warm storage tiers, scale-to-zero architecture, and usage-based pricing. Supports vector, full-text, and metadata search across terabytes of data.
Market Position
Chroma differentiates itself by focusing on developer-friendliness and ease of use for application developers rather than infrastructure engineers. While competitors like Pinecone emphasize operational simplicity and Weaviate offers deployment flexibility, Chroma provides an open-source, customizable solution optimized for many dynamic smaller indexes (one per user) rather than a single flat index. Chroma's approach prioritizes context engineering over traditional RAG patterns, addressing issues like context rot. The platform balances self-hosted flexibility with managed cloud options, offering both Apache 2.0 open-source and serverless cloud deployments. Cost-effective with automatic data tiering and scale-to-zero architecture.
Leadership
Founders
Jeff Huber
Co-founder and CEO of Chroma. Previously co-founder of Standard Cyborg (Y Combinator alum). Background in machine learning and model interpretability. Second-time entrepreneur with deep experience in model interpretability and latent spaces.
Anton Troynikov
Co-founder of Chroma. Previously computer vision software engineer at Iris Automation Inc. (2016-2017) and worked at Meta. Completed graduate school in Germany (finished 2018) before moving to the US. Deep experience in model interpretability, latent spaces, and computer vision.
Executive Team
Jeff Huber
Co-Founder and CEO
Previously co-founder of Standard Cyborg (Y Combinator alum). Background in machine learning and model interpretability. Second-time entrepreneur.
Anton Troynikov
Co-Founder
Previously computer vision software engineer at Iris Automation Inc. and worked at Meta. PhD-level education with graduate studies in Germany.
Board of Directors
Founding Story
Jeff and Anton were experimenting with model interpretability and needed an open-source vector database that was powerful and easy to use. They found existing products were difficult to use and built for different use cases like web-scale semantic search, so they built Chroma for themselves. After Anton finished graduate school in Germany in 2018 and moved to the US, he reached out to Y Combinator founders in computer vision and robotics, which led to a friendship and eventual partnership with Jeff. Following the release of ChatGPT in late 2022, they pivoted to target developers building on top of large language models.
Business Model
Revenue Model
Usage-based pricing for cloud service (Chroma Cloud) with charges for data written, stored, queried, and network bandwidth. Free open-source version available. Subscription tiers (Starter, Team, Enterprise) with monthly fees and usage-based costs. Enterprise custom pricing available.
Pricing Tiers
Free plan with $5 in free credits. Usage pricing: $2.50/GiB written, $0.33/GiB/month storage, $0.0075/TiB queried, $0.09/GiB network. 10 databases, 10 team members, Community Slack support.
$100 credits included then usage pricing: $2.50/GiB written, $0.33/GiB/month storage, $0.0075/TiB queried, $0.09/GiB network. 100 databases, 30 team members, Slack support, SOC II compliance, volume discounts.
Custom pricing. Unlimited databases, unlimited team members, dedicated support, single tenant clusters, BYOC (Bring Your Own Cloud) clusters, SLAs.
Target Markets
- AI/ML developers and engineers
- Software developers building LLM applications
- Enterprises implementing AI solutions
- Startups building on GPT-4 and other LLMs
- Data scientists
- Applied AI researchers
- Retrieval-augmented generation (RAG) applications
- LLM application memory and knowledge management
- Semantic search systems
- AI-powered search and retrieval
- Long-term memory for AI applications
- Custom data retrieval for LLMs to prevent hallucinations
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