Enables AI agents to manage virtual clinic data including patients, visits, diagnoses, treatments, lab/radiology orders, and search medical literature and internal knowledge base.
A local knowledge base system based on ChromaDB that supports automatic chunking, vector storage, and efficient similarity retrieval of txt and pdf documents, with MCP protocol support allowing AI assistants to directly access knowledge management functions.
A local Retrieval-Augmented Generation system that enables AI agents to query and retrieve information from document collections using ChromaDB vector search and Ollama LLMs through a FastAPI interface.
Enables LLMs to interact with clinical patient records using tools for document ingestion, structured conversion, patient profiling, record listing, search, and secure Q&A over patient documentation.
A self-evolving RAG system that enables AI agents to autonomously read and write memory, continuously learning and adapting user preferences, daily logs, and knowledge graphs across applications.
A privacy-preserving local RAG system integrated with MCP, enabling natural language queries over ingested documents and a SQLite database through vector search and local database tools.