In this session, I will share practical insights from actual production deployments of GenAI applications across multiple industries. Drawing from my experience with AWS, I will demonstrate:

1. Building a Customer Service Solution for Production - You will learn how we:

• Implemented multilingual support through fine-tuned speech models
• Achieved high throughput through strategic infrastructure scaling
• Cut latency using NVIDIA TensorRT-LLM compilation
• Deployed custom containers with Triton Inference Server

2. Automated Cricket Scene Analysis with Vision Language Models - I will show how we:

• Reduced 45-50 minutes of manual processing per game to automated analysis
• Built models to identify replays, bowler run-ups, and scorecard data
• Developed resolution-agnostic, font-adaptive models for varying broadcast qualities
• Optimized performance through Lora and Hyperpod fine-tuning

3. Gen AI-based Data Analyst - I will demonstrate how we:

• Transform natural language queries into SQL and visualization code
• Build conversational analytics assistants for complex data exploration
• Set up secure database connections with proper authentication
• Generate optimized data visualizations through LLM-powered code
• Enable business users to perform sophisticated analytics without SQL knowledge