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Hybrid RAG with three retrievers—Lexical (BM25), Semantic (embeddings), and Hybrid (Reciprocal Rank Fusion) — parallel retrieval, Llama 3 generation, and side-by-side evaluation with reproducible notebooks.
MedSage is a multimodal healthcare assistant that combines LLMs, vector search, and real-time reasoning to deliver fast, reliable medical insights. It supports symptom analysis, medical document Q&A, universal file RAG, multilingual interactions, and emergency SOS with live location.
An AI-powered Fashion Assistant built using Retrieval-Augmented Generation (RAG). Combines semantic search, reranking, and LLM-based reasoning to deliver intelligent fashion recommendations, product discovery, and 24/7 customer support.
SementicCore: A transformer-based text embedding model trained with contrastive learning (SimCSE approach) for generating high-quality sentence embeddings.
Production RAG system for automated enterprise support using Vertex AI embeddings, Neo4j knowledge graphs, and LangChain/LangGraph agentic workflows. Achieves 95%+ accuracy through semantic search, multi-hop reasoning, and confidence-based escalation with comprehensive evaluation frameworks.
DigiBrain is a second brain web platform that stores links (tweets, YouTube videos, documents, etc.) enriched with metadata such as title, description, and tags. The system integrates an AI assistant that retrieves contextually relevant content using embeddings and a vector database.