Hebbia

Best Self Hosted Alternatives to Hebbia

A curated collection of the 3 best self hosted alternatives to Hebbia.

Hebbia is an AI knowledge-work platform that indexes and semantically searches internal documents and data using embeddings and LLMs, enabling teams to analyze content, extract answers, and run research, due diligence and Q&A workflows across enterprise sources.

Alternatives List

#1
Khoj

Khoj

Self-hostable personal AI 'second brain' for chat, semantic search, custom agents, automations and integration with local or cloud LLMs.

Khoj screenshot

Khoj is an open-source personal AI platform that combines chat, semantic document search, custom agents and scheduled automations. It can run locally or as a cloud-hosted service and integrates with local or remote LLMs to answer questions, generate content and automate research.

Key Features

  • Multi-client access: web, desktop, Obsidian, Emacs, mobile (PWA) and chat integrations (e.g., WhatsApp).
  • Model-agnostic LLM support: connect local GGUF models or remote OpenAI-compatible, Anthropic and Google-compatible endpoints; supports on-device and cloud models.
  • Semantic search and embeddings: document ingestion (PDF, Markdown, Word, org-mode, Notion, images) with vector storage and retrieval for fast, contextual search.
  • Custom agents and automations: build agents with distinct personas, tools and knowledge bases; schedule research tasks and email newsletters.
  • Document processing and code tools: built-in extractors, simple code execution sandbox support (local Terrarium or remote sandboxes) and image generation features.
  • Enterprise & self-hosting options: deploy via Docker or pip, use Postgres with pgvector for embeddings, and configure authentication and domains.

Use Cases

  • Personal knowledge management: query a private document corpus and get grounded answers across notes, PDFs and files.
  • Research automation: schedule recurring research queries and receive summarized results by email.
  • Team/private deployments: host a private assistant for a team with custom agents, model selection and on-premise data control.

Limitations and Considerations

  • Some optional integrations require extra setup or external services (e.g., code sandboxes, email providers); self-hosting needs correct environment configuration.
  • A few plugins/integrations may be unmaintained or platform-specific; users should check the chosen connectors and follow the docs for compatibility and maintenance status.

Khoj is designed to be extensible and model-agnostic, emphasizing private data control and flexible deployment. It is suited for individuals and teams who need a searchable, automatable assistant that can run with local or cloud language models.

32.2kstars
1.9kforks
View Details
#2
Onyx Community Edition

Onyx Community Edition

Open-source platform for AI chat, RAG, agents, and enterprise search across your team’s connected knowledge sources, compatible with hosted and local LLMs.

Onyx Community Edition screenshot

Onyx Community Edition is an open-source, self-hostable AI platform that combines a team chat UI with enterprise search and retrieval-augmented generation (RAG). It is designed to work with a wide range of LLM providers as well as locally hosted models, including deployments in airgapped environments.

Key Features

  • AI chat interface designed to work with multiple LLM providers and self-hosted LLMs
  • RAG with hybrid retrieval and contextual grounding over ingested and uploaded content
  • Connectors to many external knowledge sources with metadata ingestion
  • Custom agents with configurable instructions, knowledge, and actions
  • Web search integration and deep-research style multi-step querying
  • Collaboration features such as chat sharing, feedback collection, and user management
  • Enterprise-oriented access controls including RBAC and support for SSO (depending on configuration)

Use Cases

  • Company-wide AI assistant grounded in internal documents and connected tools
  • Knowledge discovery and enterprise search across large document collections
  • Building task-focused AI agents that can retrieve context and trigger actions

Limitations and Considerations

  • Some advanced organization-focused capabilities may differ between Community and Enterprise editions
  • Retrieval quality and permissions mirroring depend on connector availability and configuration

Onyx CE is a strong fit for teams that want an extensible, transparent AI assistant and search layer over internal knowledge. It emphasizes configurable retrieval, integrations, and deployability across diverse infrastructure setups.

17.1kstars
2.3kforks
View Details
#3
Aleph

Aleph

Aleph indexes documents and structured datasets to enable fast search, entity extraction, and cross-referencing for investigative research and OSINT workflows.

Aleph screenshot

Aleph is an investigative data platform for ingesting and indexing large collections of documents and structured datasets, making them searchable and easier to analyze. It is designed to help researchers find people, companies, and connections across many sources, including watchlists and prior research.

Key Features

  • Ingests and indexes documents (such as PDF, Word, and HTML) and structured data (such as CSV and spreadsheets)
  • Full-text search and browsing across datasets and uploaded materials
  • Entity-centric exploration focused on people, companies, and other known entities
  • Cross-referencing and matching entities against watchlists and reference datasets
  • Supports operational workflows for managing data imports and collections

Use Cases

  • Investigative journalism: search leaks, filings, and datasets for names and relationships
  • OSINT research: unify and query diverse sources (documents plus tabular data)
  • Compliance or due diligence research: check entities against internal or external lists

Limitations and Considerations

  • The open-source version is in a sunsetting phase, with official maintenance planned to end after December 2025

Aleph is well-suited for teams that need to turn large, heterogeneous collections of files and tables into a searchable investigative corpus. Its emphasis on entity discovery and cross-referencing makes it particularly useful for research-driven analysis workflows.

2.3kstars
326forks
View Details

Why choose an open source alternative?

  • •Data ownership: Keep your data on your own servers
  • •No vendor lock-in: Freedom to switch or modify at any time
  • •Cost savings: Reduce or eliminate subscription fees
  • •Transparency: Audit the code and know exactly what's running