This company provides the Haystack open source framework and enterprise platform for building custom AI solutions powered by LLMs. They specialize in high-impact applications such as Retrieval Augmented Generation (RAG), AI Agents, and Intelligent Document Processing (IDP). Their technology enables organizations to deploy trusted, sovereign AI solutions with control over data, models, and workflows.
Funding
$45.8M 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
Enterprises face challenges in efficiently developing, testing, and deploying custom applications leveraging large language models (LLMs) due to the complexities of integrating data, optimizing models, and managing infrastructure. Many organizations struggle to move beyond prototyping to production-ready AI solutions.
Solution
deepset provides a platform, built with the Haystack framework, that streamlines the AI application development lifecycle, enabling businesses to rapidly build and deploy custom AI-powered applications and agents. The platform facilitates connecting to diverse data sources, optimizing leading AI models (including GPT-4, Llama-v2, and Claude), and conducting structured experiments. deepset Cloud offers tools for prompt engineering, model fine-tuning, and performance monitoring, allowing teams to iterate quickly and deploy AI solutions with confidence. The platform's architecture supports retrieval-augmented generation (RAG), conversational BI, question answering, and other advanced AI capabilities.
Target Audience
The primary audience includes AI product teams, data scientists, and software developers within enterprises seeking to build and deploy custom AI applications and agents for various use cases.
Features
- Connects to unstructured and structured data sources for enhanced LLM context.
- Offers a library of application templates and building blocks for rapid prototyping.
- Includes a prompt engineering playground and GPU notebooks for model fine-tuning.
- Provides tools for structured experimentation and performance assessment using traditional and model-based metrics.
- Enables one-click deployment to production with REST API access.
- Leverages auto-scaling infrastructure for traffic management.
- Monitors performance metrics such as groundedness, latency, and usage.
- Supports AI Agents, Retrieval Augmented Generation (RAG), Conversational BI (Text to SQL), Question Answering, Vector-Based Search, and Multimodal applications.