I bridge the gap between academic research and production-grade AI systems. With a dual background in Physics (IISER) and Data Science (IIT Madras), I build agentic systems that don’t just "chat," but perform complex reasoning, data orchestration, and mathematical solving.

Whether you are looking to build a custom RAG pipeline, optimize GPU-heavy generative workflows, or architect an intelligence layer for sensitive financial data, I provide the end-to-end engineering required to go from MVP to Scale.

Core Services

Agentic AI & LLM Orchestration: Designing multi-agent workflows using LangGraph and LangChain for autonomous task execution and complex decision-making.

Advanced RAG Pipelines: Building high-precision Retrieval-Augmented Generation systems with Multi-Modal support (PDF/Image extraction) and SymPy integration for technical/scientific domains.

Financial Data Engineering: Architecting real-time data layers (WebSockets, SQLite persistence) and "Unified Broker" systems for seamless fintech integrations.

Generative Pipeline Optimization: GPU-optimized video segmentation and generative pipelines for high-performance content teams.

Technical Toolkit

Languages/Frameworks: Python, SQL (Advanced Data Wrangling), React (for AI interfaces).

AI Stack: LangChain, LangGraph, PyTorch, Hugging Face, SymPy, Multi-Modal RAG.

Infrastructure: GPU Optimization, WebSocket Streams, SQLite, Zerodha Kite/IBKR API integrations.

Why Hire Me?

Research-First Approach: My background in Physics allows me to tackle the underlying mathematical logic of AI, not just the wrappers.

Production Experience: I am currently the Research Lead at an AI Lab, meaning I understand the constraints of latency, token cost, and system reliability.

Documentation as a Standard: Every contract includes a comprehensive technical handover and system architecture report, ensuring your team can maintain the system long after the contract ends.