💡 Building intelligent AI systems using Python, LangChain, RAG Pipelines, Vector Databases, Multi-Agent Workflows and Large Language Models.
✔ Python Developer
✔ Generative AI Engineer
✔ AI Engineer
✔ Backend Developer
✔ Agentic AI Developer
+ 🤖 Generative AI Engineer
+ 🐍 Python Developer
+ 📖 Published Researcher (Taylor & Francis)
+ 🏆 1st Prize Winner – Python Full Stack Hackathon
+ 💼 Looking for Python / GenAI Opportunities
+ 🌱 Currently Building Production AI Applications
|
|
| Skill | Level |
|---|---|
| 🐍 Python | ████████████ 95% |
| 🤖 Generative AI | ████████████ 95% |
| 🧠 Prompt Engineering | ███████████ 92% |
| 📚 RAG Pipelines | ███████████ 92% |
| ⚡ LangChain | ███████████ 90% |
| 🔥 AI Agents | ██████████ 88% |
| 💾 SQL | █████████ 80% |
| 🌐 Frontend | ███████ 65% |
Python
│
├── LangChain
├── LangGraph
├── OpenAI
├── Claude
├── Gemini
├── FAISS
├── FastAPI
├── Streamlit
├── SQL
└── GitHub
Some of the AI systems and applications I've built.
Fusion Forge is a production-inspired multi-agent AI platform capable of understanding documents, executing Python code, retrieving real-time information, and answering questions using Retrieval-Augmented Generation (RAG).
✅ Multi-Agent Architecture
✅ LangChain Orchestration
✅ RAG Pipeline
✅ FAISS Vector Store
✅ Document Question Answering
✅ Python Code Execution
✅ AI Chat Assistant
✅ YouTube Video Summarization
✅ Web Search Integration
Python
LangChain
FAISS
Streamlit
OpenAI
Claude
Gemini
RAG
- 🔹 Context-aware document understanding
- 🔹 Persistent conversation memory
- 🔹 Autonomous tool selection
- 🔹 Secure Python execution
- 🔹 Production-ready architecture
A Jarvis-inspired autonomous AI assistant capable of interacting using voice, reasoning through tasks, using external tools, and remembering previous conversations.
🎤 Speech-to-Text
🧠 LLM Reasoning
🔧 Tool Calling
📄 Document Retrieval
🌐 Internet Search
🧮 Python Execution
🗂️ Long-Term Memory
🔊 Text-to-Speech
⚡ Autonomous Agent Workflow
Python
LangChain
OpenAI API
Speech Recognition
Memory
TTS
Prompt Engineering
█████████████████░░░░░░░░░░░░
65% Completed
An image-processing application designed to identify counterfeit currency notes using OpenCV and Machine Learning.
✔ Image Processing
✔ Edge Detection
✔ Feature Extraction
✔ Counterfeit Classification
✔ Computer Vision
Python
OpenCV
Machine Learning
NumPy
Book Chapter
📚 Taylor & Francis
📅 2025
📖 DOI: 10.1201/9781003675242-35
🥇 1st Prize — Python Full Stack Hackathon
📖 Published Researcher — Taylor & Francis
🎯 IELTS C1 (Advanced)
🎓 B.Tech Computer Science Engineering
"Building AI systems that solve real-world problems—not just demos."
⭐ If you like my work, consider giving a star to my repositories!