I build AI products for hard, real-world Indian problems — nutrition, civil-services prep, financial compliance, rural mentorship.
Full-stack + data engineer · B.Tech, Mathematics & Data Science, NIT Bhopal
| Project | What it is | Why it matters |
|---|---|---|
| AstralytiQ | No-code forecasting & BI platform — upload sales data, get ARIMA/XGBoost forecasts and dashboards | Cut a 5-hour manual reporting cycle to ~10 minutes across 40+ SKUs |
| Feedline | Food-delivery backend in Spring Boot — modular monolith with a designed migration path to microservices | System design in practice: clean architecture, scalability, real-world domain modeling |
| Release Copilot | AI agent that runs a software release end-to-end: reads the GitHub diff, flags risks, files Jira tickets, deploys to Netlify, publishes a report to Notion | Agentic workflow with every API call flowing through one integration layer |
| NutriSync | Voice-first Flutter nutrition assistant built around Indian dietary patterns | Cultural food intelligence, not a generic calorie counter |
| RegIntel | Compliance intelligence over RBI/SEBI/NPCI circulars — RAG with ChromaDB + Gemini | Turns raw regulatory PDFs into measurable action points with deadlines and owners |
| ShastraLab | Examiner-style evaluation of handwritten and typed UPSC answers | Structured feedback on structure, relevance, and depth for civil-services aspirants |
- Backend-first. Spring Boot and FastAPI services with the unglamorous parts done properly: role-based access, idempotency, audit trails, failure handling.
- Data before models. Forecasting work starts at the ETL layer — ARIMA/XGBoost/LSTM come only after the pipeline is trustworthy.
- AI as a component, not the product. RAG, agents, and LLM features live behind the same engineering discipline as any other service.
Backend — Java · Spring Boot · Python · FastAPI · Node.js Frontend — TypeScript · React · Next.js · Flutter Data / ML — PostgreSQL · MongoDB · Pandas · scikit-learn · ARIMA / Prophet AI systems — LangChain · LangGraph · RAG (Pinecone, ChromaDB) · Gemini API Ops — Docker · GitHub Actions
- Exploring distributed systems and MLOps
- Open to SDE / Data Engineering / ML Engineering roles — reach me at aisenh037@gmail.com