Haystack Enterprise Platform vs OpenRAG

Haystack Enterprise Platform is an operational layer for building, evaluating, deploying and governing production AI agents and applications. Teams can assemble and debug agents and retrieval-augmented generation (RAG) pipelines using a visual builder, templates, custom components and retrieval and memory settings. The Playground and Prompt Explorer support comparisons of prompts, retrieval strategies and agent workflows, as well as prototype sharing and feedback. Deployment options include deepset-managed cloud or self-hosting, with serverless autoscaling and a REST API. Governance tools include role-based access, run history, traces, performance monitoring, usage reports and guardrails. The platform lists SOC 2 Type II and ISO 27001 certifications, GDPR and HIPAA compliance, SSO, audit logs, CSA Star Level 1 and pipeline isolation. Listed model integrations include Anthropic, OpenAI, Mistral, Cohere, Gemini and custom models; data-store integrations include PostgreSQL, Snowflake, Qdrant, Weaviate and Pinecone. Pipelines can be exported as Python or YAML, and models and providers can be changed without rewriting code. Studio is free with stated limits; Enterprise pricing is custom and requires contacting deepset.

OpenRAG is a modular framework for building systems that answer questions using documents as their grounding. Its retrieval combines semantic search with BM25 keyword matching and multilingual reranking; answers cite a source document and page, with links to the cited location. Document processing covers listed text, office, email, audio, video, and image formats, with PDF layout awareness, OCR, image captioning, and audio transcription. The product includes an admin console, chat interface, and OpenAI-compatible API, and can connect to user-provided models or a hosted provider. Partition isolation, owner, editor, and viewer roles, plus token or OpenID Connect authentication, are among its access controls. It can run on infrastructure controlled by the deployer, keeping documents, embeddings, and queries within that environment. The self-hosted AGPL-3.0 edition is listed at free. Deployment prerequisites are Docker, Docker Compose, and at least 16 GB of RAM; a CPU-only profile is optional. CSV, ODT, and HTML support, tool calling, agentic RAG, MCP, and encryption in transit and at rest are listed as coming soon.