I design and build AI-powered applications that turn LLM capabilities into reliable, deployable software.
🤖 Agentic AI Systems: Multi-step workflows, tool-using agents, and stateful AI apps. 📚 RAG Pipelines: Ingestion, embeddings, retrieval, and grounded generation. ⚙️ Backend Systems: Python, FastAPI, PostgreSQL, MongoDB, APIs, and auth. 🌐 Full-Stack Apps: Next.js, TypeScript, and Tailwind for shipping AI products. 🚀 Built to Deploy: From experimentation and evaluation to production.
Real systems, real debugging, real shipping.
AI-powered market intelligence and saturation analysis.
🔍 Researches existing products using web search 📊 Analyzes the competitive landscape 📝 Generates a structured saturation assessment
Stack: Python • LangGraph • LLMs • Web Search • Agentic Workflows 👉 View Repository
Retrieval-Augmented Generation for querying your documents.
📤 Processes uploaded PDFs 🔎 Builds searchable embeddings and retrieves relevant context 💬 Generates grounded answers from the source material
Stack: React • FastAPI • PostgreSQL • PyMuPDF • Embeddings • Vector Search 👉 View Repository
Agentic travel planning application.
🧭 Agent workflows with conversational state 🌍 External information retrieval 🗓️ Personalized itinerary generation
Stack: LangGraph • LLMs • Tavily • MongoDB • Clerk 👉 View Repository
🧬 AI / ML: LangGraph, LangChain, RAG, LLMs, NLP, TensorFlow ⚙️ Backend: Python, FastAPI, REST APIs, PostgreSQL, MongoDB 🎨 Frontend: Next.js, TypeScript, React, Tailwind CSS 🧰 Tools & Infra: Git, GitHub, Docker, Vercel, Render
📢 Question for you: Do you prefer AI projects that go beyond simple chat interfaces? Open an issue or reach out and let me know!