Samarth S Shetty - AI Automation | ContraWork by Samarth S Shetty
Samarth  S Shetty

Samarth S Shetty

I build AI agents, RAG pipelines & backends.

Ready for work

Samarth is ready for their next project!

Cover image for Job seekers lose time and money to fake listings every day. ...
Job seekers lose time and money to fake listings every day. This agent catches them before they do. Built a LangGraph-based AI agent that takes any job posting URL or description, aggregates intelligence from Reddit threads, Glassdoor reviews, Google results, and company pages, then analyzes red flags and returns a clear verdict — scam, suspicious, or legitimate. Uses Tavily for live web search, LangGraph for multi-step reasoning, and FastAPI for the backend. Deployed and live. Built to show what a real agentic pipeline looks like in production — not a chatbot, but a reasoning system that investigates and decides.
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Cover image for Video creators waste hours manually
Video creators waste hours manually transcribing and captioning their content. CAPGEN eliminates that entirely. Built a full-stack AI web app that takes any video upload, extracts the audio, transcribes it using Groq Whisper, and generates accurate subtitles — with the user choosing caption position (top, middle, or bottom). Live on Render with real users. Zero downtime since launch. Built for YouTube Shorts creators who need fast, accurate captions without expensive editing software.
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Cover image for Agricultural Disease Detection System
Description: Built
Agricultural Disease Detection System Description: Built a ResNet-50 based CNN model to detect and classify diseases in crops from images. Achieved high accuracy on agricultural datasets. Research was published as an IEEE paper and resulted in an approved patent in 2024. Skills: Python, Computer Vision, Deep Learning Tools: ResNet-50, OpenCV, NumPy
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Cover image for AI Resume Screener
Description: Built an
AI Resume Screener Description: Built an AI-powered resume screening tool that ranks candidates against a job description. Users upload multiple PDFs, and the app analyses each using OpenAI API and returns ranked candidates with match scores and reasoning. Built with Python and FastAPI. Skills: Python, OpenAI API, Prompt Engineering Tools: FastAPI, Docker
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