Semantic image clustering using CLIP and GPT-powered metadata in a Next.js + MongoDB stack

A MongoDB Atlas-powered solution for performing vector searches on insurance-related images

Mongodb vector search to find similar movies based on plot.

AI-powered semantic search and Q&A system using MongoDB Atlas vector search, OpenAI embeddings, and LangChain agents to retrieve and summarize MongoDB documentation. Developed as part of the MongoDB University - MongoDB Skills course.

OpsMind Ai is a Context-Aware Corporate Knowledge Brain that uses RAG (Retrieval Augmented Generation) to intelligently answer employee queries from large-scale SOP documents. It ensures accurate, source-cited responses by retrieving relevant knowledge chunks from a vector database and eliminating hallucinations

Pharmacy e-commerce solution where users can navigate through range of suggested medicines (based upon search history and medical report). Users can make orders via mocked payment gateway. Orders tracked by user and admin. Also platform shares the reasonable amount of analytics to admin and users. For more detail & tech stack- checkout readme

A minimal end‑to‑end Retrieval‑Augmented Generation (RAG) app

A simple RAG with Mongodb vector index search and OpenAI

.NET 10 API for generating and semantically searching movie plot embeddings using Ollama and MongoDB Atlas Vector Search

Implementation of a Retrieval-Augmented Generation (RAG) system using MongoDB Atlas Vector Search to enhance LLM-powered applications through semantic information retrieval. Developed as part of the MongoDB University - MongoDB Skills course.