This environment provides a highly performant environment to test the deployment and tuning of different NVIDIA NIMs and Blueprints.

In this lab, we'll be focusing on the programatic steps of Retrieval Augmented Generation (RAG). First, we'll discuss data chunking, how we break down our documents. Then, we'll explore how these chunks become embeddings, numerical representations. Finally, we'll see how a vector database helps us efficiently retrieve this information.

The WWT AI-Powered Predictive Maintenance Assistant uses machine learning and a large language model to predict equipment failures, schedule maintenance, generate instructions, and answer related questions. Through an interactive UI, users explore proactive, data-driven strategies to reduce downtime, extend machine life, and optimize resources, demonstrating AI's transformative potential in manufacturing environments.

The recruitment of patients for clinical trials presents significant challenges for pharmaceutical companies, often delaying drug development, increasing cost, and leaded to study failure. This lab explores how AI applied to anonymized health records enables efficient trial matching—at single, bulk, and multi-trial levels—reducing time, improving accuracy, and enhancing access for researchers, providers, and patients.

Explore the WWT Agentic Network Assistant, a browser-based AI tool that converts natural language into Cisco CLI commands, executes them across multiple devices, and delivers structured analysis. Using a local LLM, it streamlines troubleshooting, summarizes device health, and compares configs, demonstrating the future of intuitive, AI driven network operations.

This lab deploys a real-time speech-to-speech support agent for fictional company AnyTelco, where a customer calls in for help. It uses Amazon Nova Sonic in Amazon Bedrock for natural conversation, with S3/CloudFront and Cognito for frontend/auth. A backend on ECS/NLB streams audio and invokes MCP tools (e.g., DynamoDB customer profiles, Bedrock knowledge bases). All infrastructure is provisioned via AWS CDK.

This lab provides hands-on experience with LiteLLM, an open-source AI gateway that centralizes and manages access to Large Language Models (LLMs). Throughout the five modules, you'll learn how to set up and use LiteLLM to control, monitor, and optimize your AI model interactions.

Primary care and pediatric providers can spend significant time manually cross-referencing multiple sources to construct accelerated catch-up protocols for unvaccinated or under-vaccinated patients. The Pediatric Vaccine Assistant streamlines this workflow, reducing administrative burden and supporting evidence-based care.