From Raw Files to
AI Search in Minutes.

Use Mixedbread as a fully-managed AI search engine—or pick only the parts you need, from embedding & reranking models to document parsing.

Integrates with Google Drive, SharePoint, Notion, Slack, and your tools

Trusted by developers worldwide with over

Models Used by the Best

The Complete AI Search Stack

Everything you need to build production-ready AI search and RAG applications. Transform raw data into intelligent search experiences that power AI agents, chatbots, and knowledge systems—without the complexity.

Vector Stores

Make your data AI and agent ready. Build production search engines in minutes, not months. No chunking, no tuning, no infrastructure—just upload your data and get state-of-the-art multimodal search that works across 100+ languages.

Q4 2023 financial statements
ESC
3 Results found in multiple formats
2023 Q4 Earnings Report - Acme Inc.PDF, English, 42 pages
2023年第4季度财务报告 - Acme Inc.Video, Chinese, 10 minutes
Q4 2023 Consolidated Financials - Acme Inc.XLSX, English, 4 sheets
Embeddings & Reranking

MTEB leaderboard models with 50M+ downloads. Get state-of-the-art accuracy for semantic search and RAG with models that outperform OpenAI—while staying open-source and cost-effective.

Reranking Model PerformanceBEIR (Relative)
mxbai-rerank-large-v2100%
cohere-rerank-3.596.3%
bge-reranker-v2-gemma96.3%
voyage-rerank-294.9%
Document Parser

Turn documents into structured data. Extract text, tables, and layouts from PDFs, images, and complex documents. Get clean, AI-ready content without manual preprocessing.

FINANCIAL DOCUMENTS

Enterprise Deployment

Deploy Mixedbread anywhere. On-premises, VPC, or cloud—with enterprise-grade security and , , and compliance. Scale to millions of documents with full data sovereignty and control.

System StatusAll Systems Operational
Vector Stores
99.99% Uptime
Embedding Models
99.99% Uptime
Document Parsing
99.99% Uptime
Reranking Models
99.99% Uptime

Industry-Leading Open Source Models

Our models outperform closed-source alternatives while staying open to everyone through Hugging Face.

Total Model Downloads on
Hugging Face

Languages supported by
mxbai-rerank-v2

Lower costs with
mxbai-embed-large-v1 and Binary Quantization

Monthly Model Downloads on
Hugging Face

Ship Search in 4 Lines

Skip months of infrastructure setup. Deploy production-ready multimodal semantic search and RAG with simple REST APIs. Better performance as building it in-house—100x faster.

DocumentationAPI Reference