AnythingLLM - Versatile AI platform with local data privacy
AnythingLLM is a versatile AI application platform available as a desktop app, cloud service, or self-hosted solution. It enables you to intelligently query documents, run local LLMs, and build custom AI Agents without coding. With support for 30+ LLM providers and 8 vector databases, it offers maximum flexibility in data control. The platform prioritizes your privacy through local data storage and is fully open source under MIT license.
AnythingLLM Product Introduction Article
Meet the AI Platform That Puts Privacy First
Imagine this: you've been using cloud-based AI assistants to help process sensitive company documents, but every time you paste confidential information into ChatGPT, a small voice in your head asks—"where does this data actually go?" Or perhaps you're a developer who needs to embed AI capabilities into your product, but the thought of routing your users' data through third-party servers keeps you up at night.
You're not alone. Data privacy concerns around cloud AI services have grown exponentially as more businesses recognize the value of their intellectual property. Meanwhile, enterprise teams struggle with scattered documentation across multiple platforms—Google Docs, Confluence, shared drives, email attachments—making it nearly impossible to find the information they need when they need it.
AnythingLLM was built for exactly these moments. It's a full-stack AI application platform that gives you the power of intelligent document analysis and AI-assisted conversations without compromising on privacy or control.
Whether you prefer the simplicity of a desktop application, the convenience of cloud hosting, or complete control through self-hosted deployment, AnythingLLM adapts to your infrastructure needs. The platform supports over 30 large language model providers and 8 vector databases, giving you the flexibility to choose exactly how your AI stack looks.
With 59,200+ GitHub stars and an active community of developers and enterprise users, AnythingLLM has proven itself as a reliable, privacy-first AI solution. Developed by Mintplex Labs Inc. and released under the MIT open-source license, the project continues to evolve with the latest version v1.11.1 dropping in January 2026.
- Full-stack AI platform with Desktop, Cloud, and Self-hosted deployment options
- Supports 30+ LLM providers including OpenAI, Anthropic, Ollama, and local models
- 8 vector databases: LanceDB, Chroma, Milvus, Pinecone, QDrant, Weaviate, Zilliz, PGVector
- Privacy-first design: 100% local operation, data never leaves your machine
- Open source and free to use (MIT license)
What AnythingLLM Can Do for You
AnythingLLM isn't just another AI chatbot—it's a comprehensive platform designed to transform how you interact with your documents and knowledge bases. Here's what makes it powerful:
Intelligent Document Q&A lets you upload virtually any file type—PDFs, Word documents, spreadsheets, code repositories, or plain text—and then ask questions about them in natural language. The system uses Retrieval Augmented Generation (RAG) technology to find relevant passages and cite sources precisely, so you always know where the answer came from.
Run LLMs Locally means you can leverage models like those served by Ollama, LM Studio, LocalAI, or KoboldCPP directly from your desktop. No API calls to external servers, no data leaving your machine. For users who want the best of both worlds, AnythingLLM also connects to cloud-based LLMs when needed.
Build AI Agents Without Code through the visual Agent Flow builder. Define custom Agent Skills, connect tools like web scrapers and API connectors, and create automated workflows—all without writing a single line of code. The system also supports full MCP compatibility for advanced integrations.
Collaborate with Your Team through multi-user workspaces with complete data isolation. Administrators get granular controls over permissions, and white-label options let companies customize the interface entirely.
Embed AI into Your Products with the ready-made chat widget and developer APIs. Whether you're building an internal tool or a commercial product, AnythingLLM provides the building blocks you need.
- Complete privacy: Data stays on your machine or your own servers
- Full control: Self-host everything or choose cloud convenience
- Flexible LLM choice: Use any model—local, cloud, or both
- Open source: Transparent, auditable, and free to modify
- Developer-friendly: Robust APIs and embedding options
- Self-hosted requires technical setup: Docker knowledge needed for full deployment
- Desktop version limitations: Some advanced features only available in Cloud/Enterprise plans
- Local model hardware demands: Running large local LLMs needs capable hardware
Who Is Using AnythingLLM?
AnythingLLM serves a diverse range of users—from individual developers to Fortune 500 enterprises. Here are the most common scenarios where it shines:
Enterprise Knowledge Management is perhaps the most popular use case. Companies import all their internal documentation—policy manuals, technical specs, meeting notes, onboarding materials—into AnythingLLM to create a centralized, searchable knowledge base. Employees ask questions in plain language and get instant answers with source citations. The days of "I think that document is on John's computer" are over.
Privacy-Sensitive AI Applications are ideal for healthcare providers, legal firms, financial institutions, or any organization handling sensitive data. Since Everything runs locally, you get AI assistance without the compliance headaches of sending protected information to third-party cloud services.
Developer API Integration attracts engineers building AI-powered products. The comprehensive API and embeddable chat widget let you focus on your product rather than reinventing the AI infrastructure. One tech startup used AnythingLLM to add document Q&A to their customer support platform in under a week.
Team Collaboration works beautifully with the multi-user workspace feature. Marketing teams share access to brand guidelines and campaign assets. Product teams centralize roadmaps and feature requests. Each workspace maintains strict data isolation, so sensitive projects stay private while the whole team benefits from shared knowledge.
Document Analysis and Summarization helps anyone dealing with lengthy reports, research papers, or legal contracts. Upload a 50-page PDF and ask "what are the key risks mentioned in section 3?"—AnythingLLM pulls the relevant information instantly.
Private Deployment satisfies organizations with strict IT policies requiring on-premise infrastructure. Banks, government agencies, and defense contractors can run EverythingLLM entirely behind their firewalls with zero external connectivity.
- Individual users: Start with the free Desktop version to explore features
- Small teams (5 or fewer): Basic Cloud plan at $50/month gets you hosted convenience
- Large organizations: Pro or Enterprise plans provide SLA guarantees and dedicated support
- Maximum control: Self-hosted via Docker is free and runs anywhere
Getting Started in Minutes
One of AnythingLLM's greatest strengths is how quickly you can go from zero to productive. Here's how:
Desktop Installation is the fastest path. Visit anythingllm.com/download, grab the installer for your OS (MacOS, Windows, or Linux), and run it. No account required, no configuration needed. The moment it launches, you can start importing documents and chatting with them.
Docker Self-Hosted is the route for teams with technical resources who want full control. With Docker installed, a single command gets you up and running:
docker run -d -p 3001:3001 \
-v anythingllm_root:/home/node/app/backend/data \
mintplexlabs/anythingllm
Connect to http://localhost:3001 and you're in. You can configure which LLM provider and vector database to use through the intuitive admin interface.
Cloud Sign-Up takes you to useanything.com where you can choose the Basic ($50/month) or Pro ($99/month) plan. Custom subdomains, managed vector databases, and team collaboration features come ready out of the box.
Your First Conversation follows this simple flow: import a document → create a workspace → start chatting. Within 5 minutes of installing, you'll have a working AI assistant that knows your documents inside out.
System Requirements are modest for basic usage: any modern computer handles the Desktop app. For running larger local LLMs, 16GB RAM minimum is recommended, with 32GB providing a smoother experience.
Start with the Desktop version to explore features and understand your needs. Once you're comfortable, evaluate whether Cloud hosting or self-hosting better matches your privacy requirements and technical capabilities.
Finding the Right Plan for Your Needs
AnythingLLM offers three deployment models designed for different use cases and budgets:
| Plan | Price | Best For | Key Features |
|---|---|---|---|
| Desktop | Free | Individual users | Full local AI capabilities, no account needed, privacy-first |
| Self-Hosted (Docker) | Free | Technical teams | Complete control, custom deployment, own infrastructure |
| Cloud Basic | $50/month | Small teams (≤5) | Private instance, custom subdomain, 3 team members, managed vector DB |
| Cloud Pro | $99/month | Growing teams | Private instance, 72-hour SLA support, unlimited workspaces |
| Cloud Enterprise | Contact sales | Large organizations | Custom SLA, dedicated support, on-premise installation support |
The Desktop version provides the complete AnythingLLM experience without any cost—ideal for personal use, experimentation, or small-scale deployments where data stays on one machine.
Self-hosted via Docker remains completely free and is perfect for developers or IT teams comfortable managing their own infrastructure. You get all the same features, just running on your servers.
The Cloud plans add managed hosting, professional support, and team collaboration features. Basic at $50/month suits small teams wanting convenience without technical maintenance. Pro at $99/month is built for organizations needing reliability guarantees. Enterprise opens custom arrangements including on-premise installations for organizations with strict data residency requirements.
- Personal exploration: Desktop is free and ready now
- Small team wanting managed hosting: Start with Basic
- Need reliability guarantees: Pro delivers SLA peace of mind
- Maximum control + support: Enterprise has you covered
Frequently Asked Questions
Is AnythingLLM actually free?
Yes. The Desktop application and Docker self-hosted deployment are completely free and open source under the MIT license. Cloud hosting plans start at $50/month for teams wanting managed infrastructure.
How do I get started?
Download the Desktop version from anythingllm.com/download and run the installer. Everything works out of the box—no configuration needed. Alternatively, deploy via Docker or sign up for Cloud at useanything.com.
Where are my documents stored?
Desktop version stores all data locally in the application directory on your machine. Self-hosted deployments store data in whichever vector database you configure (MongoDB, PostgreSQL, Pinecone, etc.). Cloud plans use managed vector databases with enterprise-grade backup.
How is this different from ChatGPT's PDF plugin?
Several key differences: Everything runs locally so your data never touches external servers. You can self-host entirely on your infrastructure. It supports more document formats and vector databases. Multi-user workspaces enable team collaboration. Being open source means complete transparency into how your data is handled.
Which LLMs does AnythingLLM support?
Over 30 providers including OpenAI, Anthropic (Claude), Azure OpenAI, AWS Bedrock, Ollama, LM Studio, LocalAI, Mistral, Groq, Cohere, Hugging Face, and Google Gemini. It also works with any llama.cpp compatible local model.
How does AnythingLLM protect my privacy?
By default, all data stays on your machine. The Desktop version requires no account. Telemetry is optional and can be disabled. You choose which LLM and vector database handle your data—whether running locally or in your own cloud environment.
What vector databases are supported?
Eight options: LanceDB, Chroma, Milvus, Pinecone, QDrant, Weaviate, Zilliz, and PGVector. Each offers different trade-offs in performance, scalability, and deployment complexity.
What happens if I need help?
Desktop and self-hosted users get community support through Discord. Cloud Basic users receive email support. Pro users get 72-hour SLA response times. Enterprise customers receive dedicated support with custom SLAs and optional on-site assistance.
AnythingLLM
Versatile AI platform with local data privacy
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