Haystack vs PrivateGPT

Haystack is an open-source AI orchestration framework for developers building agents, multimodal applications, advanced retrieval-augmented generation systems and scalable search. Applications are assembled as modular pipelines from components such as retrievers, routers, memory layers, tools, evaluators and generators. Pipelines can run on users’ own infrastructure and be served as REST APIs or MCP servers with Hayhooks. The integrations directory lists 189 options across model providers, vector databases, monitoring tools and community components, including OpenAI, Anthropic, Amazon Bedrock, Elasticsearch, Pinecone and Datadog. A separate Enterprise Platform adds a visual pipeline builder, debugging, templates, indexing, a playground, prompt exploration, deployment and monitoring tools. It can run in managed cloud or self-hosted infrastructure and exposes a REST API. Listed enterprise security and compliance provisions include SOC 2 Type II, ISO 27001, GDPR, HIPAA, CSA Star Level 1, RBAC, audit logs, traces, guardrails and SSO. A free platform trial is available by form request and includes cloud infrastructure for prototypes.

PrivateGPT is a free, open-source API layer for building private AI applications on your own infrastructure. It does not run models itself: it connects to a separate OpenAI-compatible inference server, which can be local or remote. The Messages API supports streaming, asynchronous processing, and token counting. Document workflows include file and artifact ingestion, retrieval with citations, and tools for querying databases and analyzing tabular data. The documented capabilities also include web search and extraction, code execution, custom tools, and MCP connectors. A browser workbench at `/ui` can be used for demos and inspecting API requests, but it stores chats and settings in browser localStorage and has no access control; the documentation describes it as a local demonstrator. PrivateGPT can be installed as a Python package, from source, or with Docker, and runs as a local server. Package installation requires Python 3.11; Python 3.10 and 3.12 or later are unsupported. Platforms include Linux, macOS, Windows, web, API, and self-hosted environments.