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a production-oriented multi-agent AI system in n8n where users can simply chat to analyze public GitHub repositories and receive structured technical summaries via Email or Google Docs.

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A Streamlit project for Multi-Document Research Paper Summarization using LLM (BART) and TextRank.

A tool to scan a folder and create summaries and key data extractions from all files using an LLM. Currently supporting text and PDF formats with OpenAI LLMs, Future plans include expanding file format support and integrating additional LLM providers including Local LLMs.

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Browse Google Drive and view Docs with AI-powered summaries and multi-document chat

Multi-doc Summarizer is a Streamlit-based web application that allows users to upload documents in various formats (PDF, DOCX, PPTX, TXT) and generate concise summaries using Google's Gemini API.

A Notion-inspired collaborative workspace powered by Next.js ,Cloudflare Workers, and AI. Features real-time editing, collaboration, authentication,generative AI features like chat-to-doc and multi-language summaries and seamless UI using Shadcn and Tailwind.

Doc Fusion is an ML-powered system for multi-document summarization of PDFs and LaTeX. It combines extractive and abstractive techniques with transformer models, semantic search via Milvus, and Gemini LLM to generate concise, academic-grade LaTeX summaries.

Summarization Engine using Google Gemini API and LangChain. Converts long clinical or compliance documents like discharge notes or transcripts into concise, multi-paragraph summaries using MapReduce or Refine chains, with support for PDF/text input and chunking for large docs.

Invoice extraction pipeline for medical records PDFs. It uses Docling for PDF-to-Markdown conversion with OCR, splits multi-invoice docs, applies regex and Gemini AI for structured data extraction (e.g., numbers, dates, totals), validates outputs, and saves JSON results with logging summaries

A lightweight LLM-based tool for document analysis. Upload PDFs or text files and ask questions to get AI-powered insights, summaries, and key information. 🚀 Features: ✅ Upload & analyze documents ✅ AI-powered Q&A & summarization ✅ Fast & user-friendly 🔧 Tech: Python, LangChain, OpenAI API, Streamlit 💡 Future: Multi-doc support, advanced NLP.

An Investment Due Diligence RAG assistant that uses an LLM-based routing agent for multi-source reasoning across public docs, internal notes, and models/tables. It routes each question to the right sources, retrieves with FAISS, and returns a grounded answer, highlights conflicts and delivers a summary of risks and follow‑ups for stakeholders.