I'm a Software Developer focused on building practical software solutions using React, Python, Flask, SQL, and GenAI technologies. I'm particularly interested in LLM applications, Retrieval-Augmented Generation (RAG), and tool-calling AI agents.

Currently expanding my skills in Data Structures & Algorithms, System Design, FastAPI, Docker, AWS, and AI Engineering.

Apr 2022 – Jul 2023

• Developed and maintained internal web applications using React, HTML, CSS, and JavaScript.
• Collaborated with cross-functional teams to build new features, improve UI responsiveness, and resolve production issues.
• Participated in debugging, testing, and delivering reliable software solutions.

An AI-powered full-stack email intelligence platform that combines NLP, Gemini LLMs, Retrieval-Augmented Generation (RAG), FAISS, and tool-calling AI agents to transform raw emails into structured insights and actionable, policy-grounded responses.

• LLM-based email classification, summarization, and priority scoring
• Named Entity Recognition (People, Organizations, Dates, Locations, Money)
• Action item and deadline extraction
• Company-policy RAG pipeline using Gemini embeddings and FAISS
• Gemini-powered tool-calling agent with multi-step tool execution (email search + company-policy search)
• Search, filtering, sorting & pagination
• Interactive analytics dashboard
• RESTful API architecture
• Full-stack deployment using Render and Vercel

React Frontend
      ↓
Flask REST API
      ↓
Gemini Tool-Calling Agent
      ↓
 ┌────┴─────────────┐
 ↓                   ↓
Email Search      Policy Search
   Tool               Tool
   ↓                   ↓
SQLite               RAG
                       ↓
                 Gemini Embeddings
                       ↓
                     FAISS
                       ↓
                Company Policy

Tech Stack

• Frontend: React, Vite, Axios, React Router, CSS
• Backend: Python, Flask, Flask-SQLAlchemy, Pydantic
• GenAI: Google Gemini API, LangChain, Prompt Engineering, AI Agents, Tool Calling
• RAG: Retrieval-Augmented Generation, Gemini Embeddings, FAISS, Semantic Search, Document Loaders
• NLP / ML: spaCy, Scikit-learn, TF-IDF, python-dateutil
• Database: SQLite

🔗 Repository: https://github.com/kavya608/ai-email-intelligence-platform

🌐 Live Demo: https://ai-email-intelligence-platform.vercel.app

An end-to-end data engineering project that automates job data collection, cleaning, storage, and analysis to identify hiring trends, salary insights, and in-demand technical skills.

• Automated job data collection
• ETL pipeline
• Data cleaning & preprocessing
• SQL database integration
• Hiring trend analysis
• Salary insights
• Interactive data analysis

Tech Stack Python • SQL • Pandas • ETL • Data Analysis

• React
• JavaScript (ES6+)
• HTML5
• CSS3
• Axios

• Python
• Flask
• REST APIs
• SQLAlchemy

• Google Gemini API
• LangChain
• Retrieval-Augmented Generation (RAG)
• FAISS
• AI Agents
• Tool Calling

• SQL
• SQLite
• SQL Server

• spaCy
• Scikit-learn
• TF-IDF
• Pydantic

• Git
• GitHub
• VS Code
• Postman
• Render
• Vercel

• Data Structures & Algorithms
• System Design
• FastAPI
• Docker
• AWS Cloud
• AI Engineering

• Full-Stack Development
• GenAI & AI Agent Applications
• Backend API Development
• Data Engineering
• Automation Tools

⭐ Building software that combines clean engineering, practical GenAI, and intuitive user experiences.