multi-llm model switching
Seamlessly switch between different LLM providers (OpenAI, Claude, Llama, Ollama, HuggingFace, local models) without rebuilding workflows or losing context. Enables vendor-agnostic AI infrastructure with zero lock-in.
document ingestion and rag indexing
Ingest multiple document types (PDFs, Word docs, websites, markdown, text files) into searchable knowledge bases that augment LLM responses with retrieved context. Supports nested folder organization and batch document uploads.
multi-format document support with ocr
Ingest and process documents in diverse formats including PDFs, images with text (via OCR), Word documents, spreadsheets, and web content. Automatically extracts and indexes text for retrieval.
conversation memory and context retention
Maintain conversation history and context across multiple chat turns, allowing the AI to reference previous messages and build on prior discussions. Supports long-form conversations with persistent context.
self-hosted deployment and infrastructure control
Deploy AnythingLLM on your own infrastructure (Docker, Kubernetes, VPS) with complete control over hardware, network, and data location. Enables air-gapped or on-premise deployments.
workspace-based document organization
Create isolated workspaces with separate document collections, LLM settings, and user permissions. Enables multi-project or multi-team setups with granular access control and independent configurations.
conversational ai with document context
Chat with an LLM that automatically retrieves and references relevant documents from your knowledge base to ground responses in your specific data. Maintains conversation history and context across multiple turns.
local-first document processing
Process and index documents locally without sending them to third-party servers, keeping sensitive data within your infrastructure. Supports self-hosted deployment for complete data privacy.
+5 more capabilities