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WWT in the AI space
Data is the foundation of applied AI. When activated through AI solutions like machine learning, computer vision and generative AI (GenAI), it becomes a powerful tool to automate tasks, generate insight and refine experiences. At WWT, we help clients harness the exponential nature of data to build intelligent systems that enhance decision-making, optimize operations and spark innovation.
We're only beginning to see what's possible. As AI technologies continue to advance, we partner with clients to explore the right use cases, build scalable solutions and accelerate outcomes. Whether it's discovery, design or deployment, our experts bridge business and technology to make AI real, repeatable and responsible.
AI & Data Workshops
Below is a compilation of the AI workshops we provide. The purpose of these workshops is to help OG&E make informed decisions faster. Each is led by our subject matter experts tenured practitioners who can help you turn your goals into tangible outcomes.
FinOps for AI Workshop
A structured discovery session that assesses your organization's AI spend maturity across 6 capability areas — spanning 18 of the FinOps Foundation's 22 capabilities, applied to AI as its own scope across cloud AI services, direct API providers, SaaS AI licenses, and on-prem AI hardware. For each capability area, we discuss where you are today using a Crawl, Walk, Run framework, then identify where to focus for the highest impact.
Gen AI Use Case Discovery Workshop
Unlock generative AI's potential with a unified vision and strategic roadmap. This workshop aligns business and tech leaders, prioritizing impactful use cases and eliminating guesswork, paving the way from concept to execution. Discover where AI can truly transform your organization.
Hands-on learning in the ATC
Below you will find a list of labs that are hosted in our Advanced Technology Center (ATC). Our ATC labs are geared towards building foundational knowledge across a range of OEM's technologies, letting engineers experience the breadth of the IT landscape all for free!
The First Token: An Introduction to Speculative Decoding
Why does a large language model write one token at a time, and how can a small drafter make it faster without changing the answer? Explore a real recorded run on an NVIDIA L40S through bets, interactive blocks and a head-to-head race. No GPU reservation needed: start anytime, finish in about 30 minutes.
AI-Driven Network Operations with Catalyst Center and MCP
This lab gives you hands-on experience using an AI assistant to query and troubleshoot a pre-configured Cisco SD-Access fabric in natural language. You'll see how MCP (Model Context Protocol) tool calls connect the assistant to Catalyst Center and live devices. You'll then use it to assess the impact of a planned interface outage, verifying every answer against tool evidence rather than trusting the assistant's confidence.
NetBox MCP Server - Query the Source of Truth
Give your AI assistant direct access to your source of truth. In this hands-on lab, you'll connect an AI client to a live NetBox instance using the NetBox MCP server, then query devices, IP addresses, and sites in plain English. Learn how MCP tools turn natural-language questions into accurate, real-time infrastructure answers.
Hermes Agent - Operation Storm Watch
Run Hermes Agent as an on-call operations team for a storefront outage. Fan out parallel investigators, adjudicate a risky change with a Mixture-of-Agents board, execute the fix under a goal contract with machine-verified proof, and review the agent run afterward.
Intro to Agentic Design Patterns
In this lab you build two agent architectures from scratch in Python, with no framework hiding the mechanics: an orchestrator that routes work to specialized workers, and a ReAct loop that reasons, acts, and observes until it has an answer. You'll expose the strengths and weaknesses of these architectures first hand. You'll leave understanding how each pattern works under the hood, and gain a feel for how and where these patterns are best applied.
LLM Powered Clinical Trial Matcher
The recruitment of patients for clinical trials presents significant challenges for pharmaceutical companies, often delaying drug development, increasing cost, and lead 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.
NVIDIA Blueprint: Enterprise RAG
NVIDIA's AI Blueprint for RAG is a foundational guide for developers to build powerful data extraction and retrieval pipelines. It leverages NVIDIA NeMo Retriever models to create scalable and customizable RAG (Retrieval-Augmented Generation) applications.
This blueprint allows you to connect large language models (LLMs) to a wide range of enterprise data, including text, tables, charts, and infographics within millions of PDFs. The result is context-aware responses that can unlock valuable insights.
By using this blueprint, you can achieve 15x faster multimodal PDF data extraction and reduce incorrect answers by 50%. This boost in performance and accuracy helps enterprises drive productivity and get actionable insights from their data.
NVIDIA Run:ai Researcher Sandbox
This hands-on lab provides a comprehensive introduction to NVIDIA Run:ai, a powerful platform for managing AI workloads on Kubernetes. Designed for AI practitioners, data scientists, and researchers, this lab will guide you through the core concepts and practical applications of Run:ai's workload management system.