Abhinav Yadav

I’m an AI Engineer Intern building practical, production-minded AI systems—especially LLM-powered agents, conversational interfaces, and automated workflows. I focus on turning models into reliable products that actually help users complete tasks end-to-end.

In my internship, I developed an autonomous AI BDR agent using LangChain, Groq, OpenAI APIs, and Tavily to automate lead discovery, research, qualification, and personalized outreach. I also built an AI-powered RSS intelligence platform using LLMs for real-time querying, contextual retrieval, and summarization.

I integrated Stripe subscriptions, Supabase authentication, webhooks, and Resend while troubleshooting backend issues involving databases, APIs, authentication, and email delivery—strengthening overall system reliability. I enjoy connecting AI features with the infrastructure details that make them dependable.

Through my projects, I’ve shipped a Flask + PyTorch plant diagnosis platform with a custom CNN achieving 93.06% classification accuracy, and I reduced prediction latency by 35% through optimization. I also built a Natural Language to SQL engine (Gemini 1.5 Pro + schema-aware SQL generation) with a Streamlit interface for real-time execution and visualization.