Best Self Hosted Alternatives to Onyx

AnythingLLM is a full-stack AI application for building a private ChatGPT-like experience around your own documents and content. It supports local and hosted LLMs, integrates with multiple vector database backends, and organizes content into isolated workspaces for cleaner context management.

Key Features

• Retrieval-augmented generation (RAG) to chat with PDFs, DOCX, TXT, CSV, codebases, and more
• Workspace-based organization with separated context and optional document sharing
• AI agents, including a no-code agent builder and MCP compatibility
• Supports local and commercial LLM providers (including Ollama and llama.cpp-compatible models)
• Multiple vector database options (default local-first setup, with external backends available)
• Multi-user deployment with permissions (Docker deployment)
• Embeddable website chat widget (Docker deployment)
• Developer API for integrations and automation

Use Cases

• Internal knowledge base chat for teams (policies, runbooks, product docs)
• Private document Q&A for sensitive datasets and client files
• Building agent-assisted workflows that reference curated business content

AnythingLLM is a strong choice when you want a configurable, privacy-conscious AI application that can run locally or on a server, while staying flexible about which LLM and vector database you use.

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.

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.