Retrieval-Augmented Generation (RAG) is an AI framework that enhances Large Language Models (LLMs) by integrating them with information retrieval systems, allowing them to access and utilize external knowledge bases for more accurate and relevant responses.
Our Aim is to create a RAG System with COMPLETE data privacy which can run on your local systems. This will accept any kind of files and Databases to query. Image your local file searching transforming to a bot which can answer any questions from files on your system.
Run entirely on your local system, ensuring your data never leaves your premises.
Process and query any type of files and databases in your system.
Get accurate, context-aware answers from your document repository.
Advanced indexing and retrieval systems for efficient data management
State-of-the-art LLMs optimized for local deployment
Enterprise-grade security measures for data protection
