Results-driven AI Engineer with production experience building LLM-powered agents, RAG pipelines, and multi-agent orchestration systems. I've shipped real-world agentic AI at Ecogynize — integrating OpenAI APIs, ChromaDB vector storage, and multi-tenant architectures to power enterprise sustainability platforms.
💡 I prefer shipping code over theoretical discussions. My goal: apply agentic AI to high-stakes, real-world domains like fintech, banking, and investment research.
| What I Built | Impact |
|---|---|
| 🏗️ Production Sustainability Analysis Engine using FastAPI + Python | Served multiple enterprise clients simultaneously with real-time anomaly detection |
| 🧠 LLM Reasoning Pipelines (OpenAI APIs + Prompt Engineering) | Auto-generated natural language insights for flagged system behavior, cutting manual analysis time significantly |
| 🤝 Multi-Agent CrewAI Workflow for carbon emission analysis | End-to-end agentic AI — from data ingestion to actionable output |
| 🔍 RAG Pipeline with ChromaDB + tenant-specific SOP documents | Context-aware, grounded LLM responses for sustainability domain queries |
| 🏛️ Multi-tenant Architecture with complete data isolation | Horizontal scalability across enterprise deployments |
| 📄 Automated PDF Report Generation + Zone-based dashboards | Real-time operational decision support for enterprise clients |
LangGraph · LangChain · Gemini AI · Prompt Engineering
- Built a multi-node LangGraph agent pipeline that classifies emails (professional/personal) and autonomously generates context-aware reply drafts
- Designed classification, drafting, and notification nodes enabling fully automated workflow execution
- Reduced manual email response effort to near zero through end-to-end agentic workflow design
Python · scikit-learn · ML · Pandas · NumPy · HTML/CSS/JS
- Trained and benchmarked multiple ML classifiers (Logistic Regression, Random Forest, SVM, KNN)
- Achieved 10% accuracy improvement through feature engineering and hyperparameter tuning
- Deployed as a full-stack web application enabling real-time health risk predictions
| Degree | Institution | Year | Score |
|---|---|---|---|
| B.Tech – Computer Science | Alliance University, Bangalore | 2025 | 79% |
| Intermediate (12th) | NRI Junior College | 2021 | 92.9% |
| SSC (10th) | Sri Padmavani EM High School | 2019 | 93% |
- 📊 Data Visualization: Empowering Business with Effective Insight (July 2025)
- 🐍 Python Essentials 1 (June 2025)
- 🗄️ SQL and Relational Databases 101 (June 2025)
- 📈 Data Visualization with Tableau (June 2024)
- 🤖 Getting Started with Enterprise-Grade AI (June 2023)
🥉 3rd Place — Technofair 2023 Oral Presentation Competition
Presented a technical project to a panel of industry judges
- 🏦 Agentic AI applications in fintech & banking intelligence
- 📊 LLM-based decision systems for financial risk management
- 🔗 Advanced multi-agent orchestration patterns with LangGraph
"I build AI systems that work in the real world — production-grade, scalable, and impactful."
⭐ Feel free to explore my repositories and reach out for collaborations!