Ramesh Katkuri developed end-to-end Arbitration Post-Hearing capabilities by building containerized microservices and GenAI-based transcript processing modules across the opea-project/GenAIComps and opea-project/GenAIExamples repositories. He implemented LLM-powered entity extraction and summarization workflows using Python, FastAPI, and Docker, enabling structured insight generation from arbitration transcripts. His work included scalable deployment patterns with Docker Compose and flexible hardware configurations for CPU, GPU, and HPU environments. By integrating TGI and vLLM for LLM serving and providing a Gradio-based user interface, Ramesh streamlined post-hearing data extraction and insight delivery, demonstrating depth in system deployment, configuration management, and modern GenAI integration.