Prasad Komara

I’m an Applied GenAI & AI Engineer with 2+ years of experience building production-grade AI systems, including RAG pipelines, agent-assisted workflows, and multimodal knowledge assistants. I focus on translating real-world business problems into reliable models that improve decision-making, user experience, and operational efficiency.

At TERV PRO (Aug 2024–Present), I built and deployed a RAG-based conversational AI system handling 5,000+ student queries, enabling 24/7 guidance on learning paths and placement preparation. I also implemented semantic retrieval pipelines using OpenAI embeddings + Qdrant to significantly improve answer relevance and reduce incorrect responses.

I develop end-to-end AI workflows that turn raw content into knowledge. I built a video-to-knowledge pipeline by transcribing 100+ hours of content using Whisper, followed by cleaning, chunking, and metadata tagging for better downstream retrieval and responses.

I’ve driven measurable performance gains through AI-driven automation—improving resume–job matching accuracy by ~50% and reducing manual screening effort by 3.1× using AI-based resume ingestion, matching, and recommendation workflows. I enjoy designing scalable, low-latency AI services that hold up in production.