Building AI products and full-stack systems, from idea to shipped.
CS engineer · Shipped two AI products solo.

I build AI-assisted products and the backend systems behind them — RAG pipelines, LLM evaluation, async processing, and full-stack apps that ship. I've interned on production RAG/LLM infra and React/Web3 frontends, and independently designed, built, and shipped two AI products end to end.

PostGit Turns a developer's GitHub commit history into shareable social posts — proof of work, packaged for distribution. Built and run as a product, so the codebase is closed-source.

Docminos AI platform that generates institution-formatted DOCX reports from structured input, built around modular content generation and reusable templating. Also run as a product, with the code kept private.

Design-Sight Full-stack AI product that analyzes design mockups and generates UI/UX critique using computer vision.

claim-processing-langgraph — Agentic workflow orchestration for claims processing, built on LangGraph.

My Legal Consultant — Domain-focused legal guidance app for practical, everyday use.

Lead-Intent-Scoring-Service — Backend service for scoring and ranking lead intent.

• Ship in vertical slices — working end-to-end before polishing
• Reach for AI where it changes the outcome, not as a checkbox
• Keep systems modular enough to hand off or extend
• Treat UX and backend structure as equally important, not backend-first

From first commit to shipped product — this is the whole arc.