I design and build AI-driven software systems that convert real-world workflows into automated, data-driven experiences.
My focus is on building systems that go beyond UI and operate at the level of:
- intelligent decision-making
- workflow automation
- scalable backend architecture
- AI-powered software systems (LLMs, RAG, Agentic AI)
- Intelligent document processing & semantic search
- Backend architecture (REST APIs, Firebase, scalable services)
- Android development (cloud-connected applications)
- Full Stack SaaS applications
- Data-driven analytics and recommendation systems
A production-oriented machine learning platform that transforms clinical and lifestyle data into cardiovascular risk predictions, explainable insights, personalized guidance, historical tracking, automated reports, and real-time notifications.
- 🧠 ML-based cardiovascular risk prediction using Scikit-Learn, XGBoost & CatBoost
- 📊 Risk probability and Low/High Risk classification
- 🔍 SHAP-powered explainable AI to identify factors influencing predictions
- 💡 Personalized health insights and recommendations
- 📈 Historical risk tracking and prediction history
- 📄 Automated health/risk report generation
- 📧 Email notifications for prediction results
- 🔄 DVC-based data versioning and MLflow experiment tracking
- 🐳 Dockerized application with production deployment on Render
Python • Flask • Scikit-Learn • XGBoost • CatBoost • SHAP • Pandas • NumPy • MLflow • DVC • Docker
🚀 https://ai-cardiovascular-risk-assessment-webapp.onrender.com/
A production-grade AI system that transforms resumes into structured career intelligence.
- Resume ingestion & parsing engine
- AI-based skill extraction (LLM pipeline)
- ATS scoring system (multi-factor evaluation)
- Job-role matching engine
- Real-time job market integration
- Career roadmap generation engine
Transforms static resumes into:
dynamic career decision systems
An AI recruitment platform that automates resume screening, ATS evaluation, candidate ranking, skill-gap analysis, resume optimization, and hiring decision support using a multi-LLM architecture.
- 🎯 AI-powered ATS scoring and resume evaluation
- 📄 Intelligent resume parsing and content extraction
- 🔍 Semantic skill matching against job descriptions
- 🏆 Candidate ranking and recruiter leaderboard
- 📊 Strength, weakness and skill-gap analysis
- ✍️ AI resume optimization and rewriting
- 🤖 AI recruiter analysis and hiring recommendations
- ⚡ Multi-LLM orchestration using Gemini, OpenRouter & Groq
Python • Streamlit • Google Gemini • OpenRouter • Groq • Pandas • NumPy • Plotly • PyMuPDF • pdfplumber • python-docx
🚀 Live Demo:
https://ai-resume-screener-m4hmtfdj4mai8jyygqxhb8.streamlit.app/
💻 GitHub:
https://github.com/mohapatranirjhala-stack/AI-Resume-Screener
A Kotlin-based Android finance application that combines real-time expense tracking with AI-powered financial intelligence, helping users understand spending patterns, manage budgets, achieve savings goals, and make smarter financial decisions.
- 🤖 AI-powered spending insights, predictions, financial reports & conversational assistance
- 💰 Expense tracking, budgeting and personalized savings goals
- 📊 Interactive spending analytics and category-wise visualizations
- 🔥 Firebase Authentication & Cloud Firestore for secure real-time data
- 📄 Automated PDF financial reports
- ⚡ Gemini + Groq integration for AI-powered financial intelligence
Kotlin • Android • Firebase • Firestore • Google Gemini • Groq • Retrofit • OkHttp • MPAndroidChart • Coroutines
💻 GitHub: https://github.com/mohapatranirjhala-stack/AI-Powered-Expense-Tracker-Android
📦 APK: https://github.com/mohapatranirjhala-stack/AI-Powered-Expense-Tracker-Android/releases/latest
An AI-powered document intelligence system that transforms PDFs into searchable knowledge bases, enabling users to extract insights, summarize content, and interact with documents through contextual AI.
- 📑 PDF text extraction and document summarization
- 🔍 Semantic search using FAISS vector database
- 🧠 Retrieval-Augmented Generation (RAG) for context-aware answers
- 💬 Conversational chat with uploaded documents
- 🖼️ OCR support for scanned/image-based PDFs
- 📊 Document comparison and intelligent insight extraction
- ⚡ LLM-powered question answering using Groq
Python • Streamlit • LangChain • FAISS • Hugging Face Embeddings • Groq • OpenRouter • OCR
💻 GitHub:
https://github.com/mohapatranirjhala-stack/AI-Document-Intelligence
- Build systems, not screens
- Design for scalability and automation
- Use AI as a decision layer, not a feature
- Think in workflows, not components
💬 Open to Software Engineering & AI Roles
I’m actively seeking Software Engineering, AI Engineering, and Full Stack Development opportunities where I can contribute to building scalable products involving:
- Generative AI & LLM Applications
- Retrieval-Augmented Generation (RAG)
- AI-powered Document Intelligence
- Backend & Distributed Systems
- Full Stack SaaS Platforms
- Android & Cloud-connected Applications
“Systems over features. Execution over ideas.”