talk2pdf is an AI-powered application that enables seamless, multilingual voice and text interaction with your PDFs. It combines advanced retrieval-augmented generation (RAG), Gemini AI, and speech APIs to support natural, conversational, and voice-based queries in multiple languages, making document exploration simple and interactive.

VerbaVista is an LLM-powered Streamlit app that transforms any YouTube video into structured English notes and an interactive chatbot. It automatically fetches, translates, chunks, and embeds transcripts using Gemini + LangChain, enabling contextual Q&A through a RAG pipeline with Chroma.

A CV Scorerer built with React and FastAPI. Uses Gemini API and Gemini Embeddings.

Graphiti service for manufacturing assets.

Multimodal semantic search for local photo libraries using Gemini Embedding 2 — search by text or image, no captions required.

An intelligent medical document analysis system that uses AI to help users understand and query their medical PDFs through natural language conversations.

A plug-and-play framework for a RAG (Retrieval-Augmented Generation) pipeline using Google's Gemini Embedding 2 model — the first fully multimodal embedding model — to store and query embeddings across text, images, video, and audio.

An AI-driven learning tool using RAG to analyze web, YouTube, and text content. Features a 3D Three.js UI with glassmorphism, powered by Flask, FAISS, and Gemini API. Offers Q&A, summaries, mock tests, and visualizations like mind maps and flowcharts for an engaging educational experience.

🌐 Interact with PDFs using chat or voice in multiple languages, powered by advanced AI for seamless communication and understanding.