Free AI tools for RAG over your documents

Self-hosted chat UI with built-in RAG over local documents, connects to Ollama or any OpenAI-compatible API with zero data leaving your server.

Requires Docker and a local or private LLM. not a no-code option for non-technical teams.

Mature Python/JS framework for building RAG pipelines, composable loaders, splitters, vector stores, and retrieval chains with full production flexibility.

Code-first. requires Python experience. More boilerplate than visual builders like Dify or Flowise.

Upload PDFs directly in ChatGPT Plus and query them in chat, quickest zero-setup option for one-off document Q&A without building a pipeline.

File uploads are session-scoped. not a scalable or programmable RAG solution for production apps.

Handles ingestion, indexing, and retrieval with strong anti-hallucination scoring.

Proprietary platform limits customization of the retrieval pipeline.

RenderTargetPool supports devtools workflows.

Premium needed for priority support.

Provides efficient vector similarity search with semantic embedding storage.

When you need traditional keyword or full-text search.

Provides efficient vector similarity search with semantic embedding storage.

When you need traditional keyword or full-text search.

Provides efficient vector similarity search with semantic embedding storage.

When you need traditional keyword or full-text search.

LearningResources provides tutorials and courses for electronics design. You learn PCB design, schematic capture, and simulation.

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