How to build a simplified Corrective RAG assistant with Amazon Bedrock using LLMs, Embeddings model, Knowledge Bases for Amazon Bedrock, and Agents for Amazon Bedrock.

Production-grade RAG system with hybrid retrieval (Qdrant + Elasticsearch + Neo4j), Corrective RAG via LangGraph, feedback-driven reward model, and RAGAS evaluation dashboard

Agentic RAG system with LangGraph, hybrid BM25+FAISS retrieval, cross-encoder reranking, Corrective RAG, FastAPI, RAGAs evaluation, and Docker deployment

adaptive rag, corrective rag and agentic rag examples using langgraph

An engineering-oriented Agentic RAG system built with FastAPI, LangGraph and Qdrant, featuring multi-user document isolation, hybrid retrieval, reranking, corrective retrieval, document-version-aware conversations and streaming Web UI.

Successfully developed a Healthcare AI Clinical Decision Support System, leveraging LangGraph, GPT-4o-mini, and PubMed to deliver real-time patient risk stratification, evidence-based treatment recommendations, and personalized clinical road maps with integrated drug safety validations.

Automated Agentic GitHub PR review bot — GPT-5 agentic system with 3 tools: Corrective RAG (project context), MCP web search (live docs), and ruff linter. Redis-Celery task queue. Structured review comments posted automatically on every PR.

It is a enhanced version of Past Portals with Multi-Modal Input system , C-RAG , Feedback Loop, and Voice-First Conversational AI bot

AutoDocThinker is a production-ready Agentic RAG system that ingests PDFs, DOCX, URLs, and raw text into a Hybrid Search index (ChromaDB + BM25 + RRF + CrossEncoder), then answers natural language queries through four selectable LangGraph workflows — Naive, Advanced, CRAG, and Self-RAG.

Gradio based Chatbot for Medical Queries using CrewAI framework to showcase Corrective-RAG based AgenticAI in python v3.11.0

Corrective RAG pipeline using LangGraph — evaluates retrieval quality and falls back to web search when local docs are insufficient

Context-aware tool for automated BDD test generation and execution using RAG, VectorDB, and LLaMA.

Agentic Corrective RAG over 484 ClinicalTrials.gov oncology protocols. LangGraph CRAG with LLM-as-judge grading + cross-encoder reranker for two-stage retrieval. Three independent refusal gates. PubMedBERT, FAISS, Groq Llama 3.3 70B. Live demo on Streamlit.

Production-grade Corrective RAG system in LangGraph — scores retrieved chunks before generation, falls back to web search when needed, and filters context to sentence level.

Built a multi-agent corrective RAG pipeline with LangChain, ChromaDB, and OpenAI embeddings, including document ingestion, retrieval evaluation, query correction, and context-aware response generation.

Example implementation of a Corrective-RAG workflow for agents using LangChain and LangGraph

Corrective RAG pipeline built with LangGraph StateGraph, Groq LLaMA-3.3-70B, and FAISS. Features LLM-based relevance grading, automatic query rewriting with max-1-retry, and a Streamlit chat interface for real-time document Q&A.

Explainable Corrective RAG platform with retrieval evaluation, adaptive routing, source citations, Streamlit/FastAPI demos, and RAGAS benchmarking.

An intelligent GitHub assistant powered by Corrective RAG (CRAG), built with LangGraph and using MCP, that retrieves and refines information from live GitHub data to deliver accurate answers.