About Me
Motivated B.Tech (Artificial Intelligence) graduate with hands-on experience building production-style AI and software solutions. Proficient in Python and SQL, experienced with LLM frameworks, RAG pipelines, vector databases (ChromaDB), FastAPI, and React. Demonstrated impact through internships and projects—reduced manual video-editing effort using automated RAG flows and earned 'Intern of the Month' at Prodigal AI.
Professional Experience
Agentic AI Intern
Worked on Dhanur AI, a cutting-edge video editing automation platform that transforms raw user video into polished YouTube/Shorts-ready content using the Langchain framework.
Key Responsibilities
- •Implemented Retrieval-Augmented Generation (RAG) pipelines integrated with vector databases for intelligent context retrieval
- •Developed automated b-roll selection, filter application, and transition segmentation systems using ChromaDB
- •Reduced manual editing time significantly through intelligent automation, enhancing creator productivity
- •Collaborated with cross-functional teams to deliver production-ready AI features
Key Achievements
- ★Awarded Intern of the Month in April 2025 for exceptional performance and innovation
- ★Successfully reduced manual video editing effort through automated RAG workflows
- ★Implemented production-grade RAG pipelines with vector database integration
Technologies Used
Featured Projects
A showcase of my work in AI/ML, data science, and software development
- •Multi-agent architecture with specialized roles for finance and web research
- •High-performance response times using Groq inference APIs
- •Real-time stock data retrieval and analytics capabilities
- •3-node graph architecture for query generation and execution
- •Interactive Streamlit UI with SQL preview and results
- •Syntactically-correct SQL generation from natural language
- •Data preprocessing and feature engineering for time-series sensor data
- •Random Forest model optimization for accurate RUL predictions
- •Team collaboration in hackathon environment
Technical Skills
Achievements & Education
Recognized for exceptional performance and innovation in developing automated video editing solutions using RAG pipelines and vector databases.
CGPA: 6.98. Relevant coursework: Data Structures, Object-Oriented Programming, Web Development (Node.js, React), Machine Learning, Cloud Computing.
Articles & Insights
Technical articles and insights about AI, RAG pipelines, and multi-agent systems
Get In Touch
Interested in collaborating on AI projects or discussing opportunities? Feel free to reach out!