A travel assistant made to answer travel related queries. It responds using data retrieved from both Pinecone and Neo4j. Currently only works for Vietnam

EduPilot is an intelligent course assistant built for Indiana University students. It answers questions across four graduate courses — AML, ADT, STAT, and LLM — using a seven-stage multi-agent RAG pipeline that retrieves directly from course lecture slides and materials, cites every claim and verifies its own answers, and refuses to hallucinate.

This is a production deployed RAG system that answers medical questions grounded in verified clinical documents — not hallucinations.

A Retrieval-Augmented Generation (RAG) pipeline built to query and analyze state-level energy policies.

Built a multi-agent AI Assistant using LLMs, LangChain, and LangGraph with RAG-based document retrieval. Enabled context-aware Q&A over PDFs using Pinecone vector DB. Implemented FastAPI backend with JWT authentication for scalable, secure AI interactions.

RAG pipeline to query and analyze software engineering case studies

Built a RAG Pipeline ...

Multimodal RAG architecture integrating Pinecone vector store and Gemini LLM for querying text and images from documents.

In this project, I made a resume scoring system. And it not only scores candidates based on Job Description & Resume but it can also have user profiles and their personal hiring preferences. So a particular user can filter Resume in bulk according to their personal preference. It also learns user preferences with time and evolves for each user.

Four different types of Chatbots- one with a single pdf as context; one with a multiple docs of different types of docs as context; one with a enterprise knowledge; another with no pre context just like chatgpt and others;

AI credit-card recommender (RAG) with Mistral & AI credit-card recommender (RAG) with Mistral & Pinecone — semantic search, comparisons & FastAPI 🚀💳🔎

Provides the precautions, causes, remedies for the health upset given as input. Chatbot like interface.