deepset

Berlin-based AI company providing the open-source Haystack framework for building production-ready AI applications, with recent expansion into AI agent integration and German-language processing capabilities.

Overview

deepset develops Haystack, an open-source AI orchestration framework that enables developers to build customizable LLM applications. Founded in 2018 by Milos Rusic, Malte Pietsch, and Timo Möller, the company was named a Gartner Cool Vendor in AI Engineering in 2024. With over 4,000 Discord community members and 300+ GitHub contributors, Haystack is used by Global 500 companies including Airbus, Intel, Netflix, and Apple.

In July 2025, deepset became the first IDP vendor to offer comprehensive AI agent integration with the release of deepset-mcp version 0.0.5, an official Model Context Protocol server enabling AI agents in Cursor and Claude Desktop to interact with the deepset platform through 30 specialized tools. By late 2025, the company expanded into German-language processing through a partnership with mixedbread, distributing its deepset-mxbai-embed-de-large-v1 model at $0.01 per million tokens. Early 2026 saw continued ecosystem growth as SingleStore released an open-source integration package connecting their database platform with Haystack.

Haystack has emerged as one of the two dominant players in the RAG framework market alongside LangChain, with deepset positioning it as the production-ready alternative focused on enterprise deployment and maintainability.

Key Features

• Haystack Framework: Open-source AI orchestration framework with modular DAG pipeline architecture
• AI Agent Integration: MCP server with 30 tools for conversational pipeline management through Cursor and Claude Desktop
• RAG Pipelines: Production-ready retrieval-augmented generation with comprehensive evaluation tools
• German Language Processing: Specialized embedding model supporting text and image modalities
• 80+ Integrations: Connects to Hugging Face, Elasticsearch, OpenSearch, OpenAI, Cohere, Anthropic, and enterprise databases
• Document Understanding: Intelligent document processing with text extraction and analysis
• Production Deployment: Serializable pipelines for Kubernetes, Docker, Ray, and serverless environments

Use Cases

AI Agent-Driven Development

Developers use deepset's MCP server to build and manage document processing pipelines through conversational AI interfaces in popular development tools. The integration enables natural language pipeline creation, debugging, and index management, reducing technical barriers for non-technical users while accelerating platform adoption.

Enterprise RAG Production Systems

Organizations deploy Haystack's pipeline-centric architecture for production-grade RAG implementations. Financial services firms and manufacturing companies leverage the framework's maintainable design and built-in evaluation tools to transition from prototype to enterprise-scale document processing systems.

German-Language Document Processing

European organizations utilize deepset's specialized German embedding model for localized document analysis and semantic search. The 1,024-dimension model processes both text and images, addressing regional language requirements in German-speaking markets.

Multi-Database Document Workflows

Enterprises implement Haystack with various database backends including SingleStore, Elasticsearch, and OpenSearch. The modular architecture allows customers to select enterprise infrastructure meeting specific performance and compliance requirements while maintaining consistent document processing capabilities.

Technical Specifications

Resources

• Website
• Haystack Framework
• GitHub Repository
• MCP Server Package
• SingleStore Integration
• Haystack Documentation
• Integrations

Company Information

Headquarters: Berlin, Germany

Founded: 2018

Founders: Milos Rusic, Malte Pietsch, Timo Möller

Employees: 51-200