Building intelligent systems, products, and automation pipelines.
AI-focused developer with strong foundations in backend systems, machine learning pipelines, and SaaS architecture. I build scalable APIs, real-time analytics platforms, and ML-powered systems with a focus on performance and reliability.
I am an AI and backend-focused developer who enjoys working at the intersection of systems engineering and applied machine learning. My work centers around building practical, production-ready software rather than experimental prototypes.
I focus heavily on reliability, performance optimization, and clean system design. Whether it's designing APIs, automating workflows, or building ML-powered analytics pipelines, I prefer solutions that scale cleanly and are easy to reason about.
I have hands-on experience across SaaS platforms, civic-tech systems, and real-time sentiment analysis tools. Hackathons and fast-paced environments have shaped my ability to ship quickly while maintaining technical discipline.
My long-term interests lie in AI-driven platforms, decision-support systems, and automation-heavy products that reduce operational friction.
CRM workflows were repetitive, slow, and difficult to scale.
Worked on backend-heavy automation systems supporting 200+ client accounts. Designed and optimized REST APIs, improved workflow triggers, and integrated AI-assisted messaging logic. Achieved 35% reduction in repetitive tasks and 42% improvement in responsiveness.
Social media sentiment data is high-volume and noisy.
Built a real-time sentiment analysis pipeline ingesting data from multiple social platforms and visualizing trends through a live dashboard. Processed 10,000+ posts per hour with ~90% accuracy. Runner-Up at GetAnalytix AI Hackathon.
Early-stage products struggle to prioritize scattered user feedback.
Designed a product feedback intelligence platform that collects feedback from users, clusters it using NLP techniques, and surfaces actionable insights for founders and product teams. Focused on signal extraction rather than raw sentiment.
Users struggle to choose outfits matching body type and wardrobe.
Developed a prototype that ingests images of user-owned clothing and recommends outfit combinations using computer vision APIs and rule-based matching logic. Designed as a future-facing AI-powered fashion SaaS concept.
Backend automation for 200+ client accounts. API optimization and workflow scaling. AI-based engagement improvements reducing repetitive tasks by 35%.
Built a real-time sentiment analytics platform processing 10,000+ posts per hour with ~90% accuracy. NLP-based classification using VADER with live dashboard visualization.
Developed a blockchain-backed traceability system with QR-based verification flows for supply chain transparency.
Mumbai University. Coursework in Operating Systems, DBMS, Data Structures, and Graph Theory.
Open to interesting projects, collaborations, and technically challenging problems.