🌱 Building Full-Stack Applications • 💡 AI Systems & Search Technologies • 🤝 Open Source Contributor
- 💼 Software Developer passionate about building scalable and user-focused applications
- 🤖 Exploring Generative AI, LLMs, RAG Pipelines, and AI Voice Agents
- 🔍 Apache Lucene.NET Committer working on search, indexing, and performance improvements
- 🌐 Building modern applications using Angular, React, ASP.NET Core, and Python
- 📚 Currently learning production-grade AI architecture and distributed systems
- 🤝 Love contributing to Open Source and solving real-world engineering problems
📫 Email: pathannehan28@gmail.com
🌍 Portfolio: https://nehan-portfolio.netlify.app
- 🏅 Apache Lucene.NET Committer
- 🌟 Google Summer of Code 2025 Contributor
- 🚀 Contributed to Apache Lucene.NET with search, replication, and performance improvements
- 🌱 Successfully completed Hacktoberfest 2024
- 🏆 Building production-ready AI applications using modern LLM technologies
A full-stack AI application that transforms personal photos into cinematic visual stories and digital keepsakes, combining multimodal AI, real-time processing, and a modern web experience.
Highlights:
- 📸 Multi-Photo Processing — Upload and process multiple images with real-time progress tracking
- 🎬 AI Story Generation — Generate cinematic memory cards and narratives using OpenAI
- 🎨 Personalized Storytelling — Multiple themes including Nostalgic, Travel, and Family
- ⚡ Real-Time Processing — Live generation updates using Server-Sent Events (SSE)
- 📱 Modern Web Experience — Responsive React interface with dark mode
- 🖼️ Image Processing Pipeline — Image upload, storage, and delivery through ImageKit
- 🔒 Production-Oriented Architecture — FastAPI backend with PostgreSQL persistence
- 🤖 AI-Powered Personalization — Combines user-provided visual context with LLM-generated storytelling
Tech Stack:
React 19 · TypeScript · FastAPI · Python · OpenAI · PostgreSQL · ImageKit · Tailwind CSS · SSE
Repository: https://github.com/NehanPathan/MemoraAi
A production-oriented RAG platform built to solve real-world document intelligence problems, from enterprise knowledge retrieval to specialized Steel & CAD engineering documents.
Highlights:
- 🔍 Hybrid Retrieval — Vector Search + BM25 with Reciprocal Rank Fusion (RRF)
- ⚖️ Intelligent Reranking — Query-aware candidate reranking
- 🧠 Semantic Caching — Efficient handling of repeated queries
- 📄 Document Intelligence — PDF, DOCX, images, CAD drawings, and engineering documents
- 📚 Citation-Aware Generation — Answers grounded in retrieved evidence
- ⚡ Streaming Responses — Real-time responses using SSE
- 🔐 Production Governance — RBAC, document clearance, PII redaction, audit logging, and retention
- 🧪 Evaluation & Quality Gates — Automated evaluation and governance checks
- 🏗️ Two Architectures — Framework-free RAG core alongside LangChain/LangGraph
- 🏭 Real-World Domain — Steel & CAD document intelligence, drawing revisions, engineering entities, and visual understanding
Tech Stack:
Python · FastAPI · PostgreSQL · OpenAI · Anthropic · LangChain · LangGraph · BM25 · Vector Search · RAG · Docker · React · TypeScript · Streamlit
Repository: https://github.com/NehanPathan/RAG-Pipeline-Production-Level-
Apache Lucene.NET Committer contributing to one of the world's leading search libraries by improving performance and search capabilities.
Highlights:
- 🚀 Search Performance Optimizations
- 📖 Smart Chinese Analyzer (SmartCN) Improvements
- ⚡ Dictionary Loading Enhancements
- 🔄 Replication Framework Contributions
- 🌐 ASP.NET Core Integration
- ✅ Unit Testing & Performance Improvements
Repositories:
Working with
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- AI Agents
- Vector Databases
- Prompt Engineering
- Semantic Search
- AI Automation
https://linkedin.com/in/Nehan-Khan-Pathan
🌐 Portfolio
https://nehan-portfolio.netlify.app
🏅 Holopin
https://holopin.me/nehanpathan
⭐ Building software that combines Search, AI, and Open Source to solve real-world problems.