
Mixedbread
Mixedbread.ai provides instant access to cutting-edge embedding models. Access via API or our SDKs for seamless integration.
Date | Investors | Amount | Round |
---|---|---|---|
$855k | Seed | ||
Total Funding | 000k |
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Based in Berlin, Germany, Mixedbread AI operates as a developer of an AI-based, open-source platform focused on information retrieval and discovery. The company was founded in 2023 by Aamir Shakir and a co-founder, stemming from their experience building an on-premise search engine for consultants and lawyers. They identified a significant challenge in hosting embedding models and a knowledge gap for developers entering the complex field of information retrieval.
Mixedbread provides a complete AI search stack designed to help developers build production-ready AI search and Retrieval-Augmented Generation (RAG) applications. The core of their business is to transform raw, unstructured data from various formats like PDFs and images into intelligent, AI-ready search experiences. This technology powers applications such as AI agents and chatbots. The company's platform includes tools like Vector Stores for creating AI-powered search indexes, as well as embedding and reranking models. Their open-source models have garnered over 50 million downloads on Hugging Face. The business model appears to be centered around providing these tools as a fully-managed AI search engine, with options to use individual components. Deployment is flexible, offering on-premises, VPC, or cloud solutions with a focus on enterprise-grade security and data sovereignty.
The company's target audience includes developers, researchers, and businesses seeking to implement advanced search functionalities, content recommendation systems, or automate content moderation. Mixedbread has secured a total of $6.35 million in funding over two rounds. A pre-seed round in January 2024 brought in $900,000, followed by a seed round of $5.5 million. This positions the company as a venture capital-backed entity.
Keywords: information retrieval, AI search, open-source models, Retrieval-Augmented Generation, embedding models, vector search, unstructured data, natural language processing, enterprise AI, developer tools