Final-year B.Tech (AIML) student at REVA University with deployed AI system experience across agricultural forecasting and urban intelligence platforms. Proficient in Python, TypeScript, and JavaScript (ES6+); experienced building REST API architectures, multi-tenant SaaS systems, and full-stack AI applications. Actively expanding into agentic AI frameworks (LangChain, LlamaIndex), RAG pipeline design, LLM integration, and Docker-based deployment. Passionate about autonomous software engineering, multi-agent systems, intelligent search, and AI-driven solutions with real-world engineering impact.
Architected and deployed a production multi-tenant SaaS platform with 67 routes and 20+ REST API endpoints, applying full-stack software architecture and distributed data design principles. Designed modular TypeScript/React UI components consuming backend APIs end-to-end; integrated AI-powered features with structured PostgreSQL/Supabase schema supporting intelligent data retrieval across tenant contexts.
Built a real-time AI language processing platform integrating backend LLM APIs for dynamic multi-language text input/output — applying knowledge-centric AI application and intelligent retrieval patterns aligned with agentic system design.
Led development of a live urban intelligence platform integrating multiple heterogeneous real-world data sources via REST APIs into a unified analytics engine — applying distributed data ingestion, software architecture, and pipeline reliability practices.
Co-developed and deployed an AI agricultural price forecasting platform, integrating ML prediction models into a Flask REST API backend with full cloud deployment — demonstrating end-to-end AI system lifecycle from model integration to production. Designed scalable API contracts and data pipeline architecture for AI model serving; implemented iterative validation and testing workflows under academic supervision.