Self-Evolving RAG System with ChromaDB for continuous knowledge updates (6x daily), designed to overcome Large Language Model data cutoff limitations.

Turn any LLM into a self-extending knowledge agent powered by a graph-structured memory - complete with PDF-to-graph ingestion, budget-aware optimisation, and dual-engine orchestration.

🧮 PINN Enterprise Platform - AI-Powered Physics Simulations with CopilotKit-style Research Canvas UI. Complete serverless architecture with RAG-powered code generation, 3D visualization, and global edge deployment.

An AI-powered crypto analytics platform integrating forecasting, sentiment, and on-chain intelligence, built with FastAPI, MCP protocol, and MLflow in a monolithic architecture.

Terminal-based platform where specialized AI experts (Legal, Tech, Business) engage in real-time debates and collaborative problem-solving to provide multi-perspective analysis for complex decisions.

Enterprise-grade AI voice assistant with RAG-powered customer support, real-time phone integration, and advanced conversation management

DiagnoAI: Medical RAG Assistant - Educational AI system for healthcare information retrieval using multi-source medical knowledge and advanced search. FOR LEARNING AND RESEARCH ONLY.

An AI-powered cognitive health analytics platform that monitors burnout risk through intelligent activity classification and metabolic insights. Uses RAG-based LLM analysis to detect cognitive decline patterns and provide personalized wellness recommendations.

AI-powered research assistant with voice interaction, multimodal RAG, and intelligent routing. Explore academic papers effortlessly using LLMs & ChromaDB.

A production-ready, multi-provider Enterprise RAG (Retrieval-Augmented Generation) system with a FastAPI backend and React frontend, featuring robust RBAC, document versioning, intelligent session management, and support for both local and cloud LLM providers.

RAG-Chat-Assistant is a complete Retrieval-Augmented Generation (RAG) system packaged as a sleek web app. Built with a Flask backend, it enables users to drag and drop documents (PDFs, Word, TXT) and chat with an AI assistant that understands their content. It processes files by chunking and embedding them with Google Gemini models, stores embeddin

Multi-agent AI system combining RAG, web search, fact-checking, and synthesis to produce well-cited research reports. Demonstrates agentic design patterns in action.

🚀 Complete AI Development Toolkit Template - Add RAG, MCP, and AI assistance to any project in 2 minutes

A multilingual Retrieval-Augmented Generation (RAG) system built for an assessment. It features text processing, intelligent document chunking, semantic search with multilingual embeddings, and conversation memory management. Leverages FastAPI, LangChain, and ChromaDB for efficient knowledge base querying.

Production-ready intelligent knowledge management system built with LlamaIndex. Enables organizations to query, analyze, and extract insights from multiple data sources (documents, databases, APIs) through natural language using advanced RAG capabilities, multi-tenant architecture, and specialized query engines: SQL generation /intelligent routing.

Production-ready RAG system starter kit with local LLM inference, hybrid search, and intelligent document processing - deploy AI that learns from your knowledge base in minutes.

Everything about RAG system, its references links & technical documentations