nothumansearch

R2R ingests documents, images, audio, and other content into a self-hosted knowledge base, then exposes hybrid search, cited RAG, knowledge graphs, and a multi-step research agent through a REST API. Python and JavaScript clients handle document management and retrieval. It can run in a lightweight mode or a fuller Docker deployment, and normally requires an API key for the selected language model.

Skald packages document ingestion, chunking, embeddings, vector storage, retrieval, and cited chat behind a configurable API. Teams can tune search, reranking, models, and query rewriting, then evaluate the resulting RAG setup through the same platform and access it from several language SDKs. It can run as a hosted service or through Docker in your own environment; a fully local deployment also requires self-hosted LLM inference and embeddings.

Ask about a topic and last30days searches recent discussions across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the wider web, then synthesizes cited findings using signals such as votes, comments, or market odds. It can fall back to web-only research without keys, while richer sources require your own API credentials, browser sessions, or helper tools, and it runs in many Agent Skills hosts or as a Claude Desktop MCP bundle.

Onyx is a self-hosted AI workspace for teams that want to use different LLMs through one interface and ground answers in organizational knowledge. It can index application data through more than 50 connectors or connect agents to external systems through MCP, with additional support for research workflows and code execution. Lite mode keeps a smaller chat-and-agents stack, while the standard deployment adds vector and keyword indexes plus background synchronization workers for a fuller knowledge workflow.