Open-source Hebbia alternatives

Onyx is an open-source AI platform that acts as a knowledge and context layer for teams and their AI agents. It connects to more than 50 applications, pulls in documents along with their metadata and permissions, and builds an internal representation so that LLMs can answer questions grounded in what your company actually knows.

The project argues that this indexed approach gives more reliable, lower-latency and cheaper context than approaches that have an agent search many tools iteratively through MCP. Features include agentic RAG on a hybrid index, a Deep Research mode for multi-step reports, custom agents with their own knowledge, instructions and actions, and live web search through providers such as Serper, Google PSE, Brave and SearXNG. Sandboxes and skills extend what models can do, and the chat interface works with every major LLM.

Onyx emphasizes data sovereignty through flexible self-hosted deployments, with a single-command deploy option. The code is written in Python and Next.js, and the license is listed as 'Other' on GitHub, so check the terms for the enterprise features. It suits organizations that want a private, ChatGPT-style assistant connected to internal documents.

SWIRL is an AI search and retrieval-augmented generation tool that works without moving your data. Instead of copying content into a vector database, it queries your sources live with each user's own permissions, re-ranks the results, and can generate an answer with citations using the language model of your choice. The Community edition in this repository is released under the Apache-2.0 license.

Connectors reach many business applications, and the project's tagline refers to more than 100 apps. The approach avoids building ETL pipelines, standing up a vector store, or maintaining a second copy of data that needs security and audit controls, since permissions are enforced at the source. The stack is Python and Django, and a Docker quick start gets an instance running in about two minutes.

A separate SWIRL Enterprise edition adds a three-pass reranker, canonical answers, an MCP server for agents, and managed support. The Community edition is free to self-host. It suits IT and data teams wanting enterprise search across many systems while keeping data in place.

Open Semantic Search is a research tool aimed at journalists, researchers and analysts who need to search, browse, analyze and explore large collections of documents, going well beyond simple keyword search. It combines a semantic search engine with a full text mining and text analytics platform.

It includes an ETL framework for processing documents, covering crawling, text extraction, text analysis, named entity recognition for persons, organizations and locations, and OCR for images and embedded images inside PDFs. On top of that data pipeline, it provides metadata management through thesauri and ontologies using the SKOS standard, and search user interfaces and applications supporting full-text search, faceted search, exploratory search and knowledge graph search. Its topics specifically mention OSINT and investigative journalism as use cases.

Open Semantic Search can be built as a Debian or Ubuntu package, as a desktop search appliance for VirtualBox, or as a set of Docker images using the project's docker-compose configuration, which starts all the needed services together. It is written in Shell and Python, documented with MkDocs, and released under the GPL-3.0 license.