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Run private document chat and AI agents with any LLM in a self-hosted workspace. MIT licensed, supports local models and cloud APIs.
A legal team uploads contracts, NDAs, regulatory filings, and case materials to a private AnythingLLM workspace on their own server. Team members query in plain English and get cited answers without any document contents leaving the organization's infrastructure.
Your document corpus is small and well-organized, and keyword search in a shared drive or document management system already meets the team's needs.
A developer installs the desktop app alongside Ollama running a local LLaMA or Mistral model. They ask questions about a large codebase, internal documentation, or API specs with no internet connection, no API costs, and no file contents leaving the machine.
You need managed infrastructure with SLA guarantees and no server administration.
An IT lead sets up separate AnythingLLM workspaces for sales, engineering, and support in a single Docker deployment. Each department accesses only its own document set with its own LLM and permission settings, managed from a central admin panel.
Your organization requires enterprise-grade SSO and compliance audit trails out of the box.
A product team uses AnythingLLM's embeddable widget to add a documentation assistant to their app. The widget is scoped to a workspace containing the product's own docs, replacing a generic chatbot with one that answers from actual content.
You need analytics dashboards, ticket escalation, and user feedback loops around the chat widget.
Commercial AI chat platforms charge per seat and route your documents through third-party servers, making them costly and risky for teams handling sensitive data. AnythingLLM gives developers and small teams a self-hosted path: pick any LLM provider or run a local model, ingest any document type, and keep everything on infrastructure you control. The multi-user workspace model means the whole team shares the same knowledge base without licensing costs that scale with headcount.
Processes PDFs, Word docs, spreadsheets, and plain-text files, then embeds and indexes them using LanceDB (bundled, no external setup required). Supports 8 additional vector stores including Pinecone, Chroma, Weaviate, Qdrant, and PGVector for teams with existing data infrastructure. Cited answers link back to the source document.
Supports OpenAI, Anthropic, AWS Bedrock, Google Gemini, Azure OpenAI, Groq, Mistral, DeepSeek, and more. Also connects to local models via Ollama, LM Studio, and LocalAI for fully offline operation. Switching providers requires a settings change, not a code change.
Build agents that browse the web, run code, query files, and call external tools without writing any code. Intelligent tool selection reduces token consumption by up to 80% by loading only context relevant to the current query instead of sending all documents on every turn.
Docker deployment supports multiple users, each with their own workspace, document set, and LLM configuration. Admins control which LLM providers each user can access and which document workspaces are visible to them. Available in the Docker version only.
Generates a JavaScript embed snippet that adds a chat interface to any website. The widget connects to a specific AnythingLLM workspace, so the chat is scoped to a defined document set. Useful for documentation assistants, support bots, and internal knowledge bases with a web front end.
Native desktop installer for Mac, Windows, and Linux requires no Docker setup and no external account. The entire stack runs on the local machine, including the database and embeddings. Supports one-click installation of Ollama-compatible local models directly from the UI.
AnythingLLM and Glean both let teams search and query internal documents using AI, but they serve different deployment models and budgets.
AnythingLLM is the stronger choice when data residency requirements, privacy constraints, or budget limits make a managed enterprise AI search tool impractical. It gives teams full control over which LLM provider processes their queries, and all document data stays on the team's own servers. The MIT license means any number of users can run it with no per-seat costs or vendor lock-in.
Glean is worth evaluating when your organization needs deep out-of-the-box integrations with SaaS applications (Google Workspace, Salesforce, Jira), enterprise SSO and compliance audit logging, and fully managed infrastructure with SLA guarantees. For those requirements, the additional cost of Glean may be justified.
A second alternative worth comparing is ChatGPT Enterprise. AnythingLLM matches it on document Q&A capability but runs entirely on your infrastructure, with no document contents sent to OpenAI servers. The trade-off is that AnythingLLM requires self-managed deployment; ChatGPT Enterprise is fully managed with Microsoft-grade uptime guarantees.
# Desktop (Mac, Windows, Linux): download from https://anythingllm.com/download
# Docker (Linux/macOS)
export STORAGE_LOCATION=$HOME/anythingllm && \
mkdir -p $STORAGE_LOCATION && \
touch "$STORAGE_LOCATION/.env" && \
docker run -d -p 3001:3001 \
--cap-add SYS_ADMIN \
-v ${STORAGE_LOCATION}:/app/server/storage \
-v ${STORAGE_LOCATION}/.env:/app/server/.env \
-e STORAGE_DIR="/app/server/storage" \
mintplexlabs/anythingllm
# Open http://localhost:3001 after the container startsNo. The desktop version runs fully offline using local models via Ollama, LM Studio, or LocalAI. Cloud providers like OpenAI or Anthropic are optional; you configure only the providers you choose to use.
The desktop app is the fastest way to get started and works for single-user setups. The Docker version adds multi-user workspaces with per-user permissions, the embeddable website chat widget, scheduled tasks, and the full developer API.
LanceDB is bundled and enabled by default. AnythingLLM also connects to Pinecone, Chroma, Weaviate, Qdrant, PGVector, Milvus, Zilliz, and Astra DB through the settings panel.
The self-hosted version is MIT licensed and free to run with no seat fees, workspace limits, or usage caps. Mintplex Labs also offers a cloud-hosted managed version with its own pricing.
Yes. AnythingLLM supports Azure OpenAI, AWS Bedrock, Google Gemini, and other enterprise providers through its provider configuration panel. You supply the API credentials and endpoint; AnythingLLM routes requests through them.
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