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Track 01 — Boost productivity with AI agents

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Track Overview

Fields Details
Products watsonx Orchestrate
watsonx.governance
IBM Bob
Target Persona Select-t growth partners, Business/Technical Leaders and Select-t clients
Overview sessions 2
Lab sessions 4
Estimated Duration ~6–7 hrs (excluding breaks)

Learning Journey

flowchart LR
    theory["<strong>Overview</strong><br/>What & Why"] --> lab101["<strong>Lab 101</strong><br/>Basics"]
    lab101 --> lab201["<strong>Lab 201</strong><br/>Fundamentals"]
    lab201 --> lab301["<strong>Lab 301</strong><br/>Intermediate"]
    lab301 --> lab401["<strong>Lab 401</strong><br/>Advanced"]

Before You Begin

Overview

Hands-on Labs

Lab 101 - Basics lab

Goal

In this basic, you'll learn core concepts, explore the architecture overview, and complete the foundational setup. You'll understand what watsonx Orchestrate does and why it exists through hands-on experience in your chosen domain. You will use the low-code way of building AI Agents in these labs.

  • AI Powered customer service for retail

    In the logistics and shipping industry, customer satisfaction hinges on quick updates, transparent delivery tracking, and smooth returns. The AI-Powered Customer Service solution enables companies to handle customer queries related to delivery status, shipment tracking, returns, and claims through an intelligent virtual assistant.

    Start Lab

  • AI Powered insurance broker assistant

    In the insurance industry, broker productivity depends on fast access to accurate customer and policy data. Brokers spend significant time switching between systems, manually querying databases, and compiling policy summaries time that could be spent on higher value client interactions.

    Start Lab

  • Vehicle maintenance

    The Vehicle Maintenance Assistant is an AI Agent designed to help car owners identify and understand vehicle issues by interpreting natural language inputs like “My car is shaking” or “Check engine light is on.” It combines real-time telematics data, diagnostic trouble codes (DTCs), and vehicle documentation to offer personalized, accurate diagnostics and actionable guidance such as finding nearby service centers, etc.

    Start Lab

Learning Objectives

By the end of this lab, you will be able to:

  • Building AI Agents with Low-code Agent Builder
  • Building AI Agents with pre-built tools and agents from the Catalog
  • Connections in watsonx Orchestrate
  • Knowledge Bases - Basic RAG
  • Web chat embedding - Basic
  • OpenAPI tools
  • Monitoring & Observability

Lab 201 - Foundational lab

Goal

In this foundational lab, you'll build upon the basics and dive deeper into fundamental concepts. You'll work with more advanced features and learn how to implement practical solutions in your chosen domain.

  • Financial research and analysis

    A smart assistant designed to support financial advisors across their client engagement lifecycle. It autonomously generates personalized investment reports, summarizes meeting outcomes, drafts follow-up communications, and delivers real-time market and financial insights.

    Start Lab

  • Supply chain use case

    This use case demonstrates how AI-powered agents can streamline end-to-end supply chain operations by handling domain-specific tasks and collaborating autonomously to achieve operational efficiency and business continuity.

    Start Lab

Learning Objectives

By the end of this lab, you will be able to:

  • Building AI Agents with Pro-code Agent Builder
  • Multi-agent collaboration with external agents
  • Python tools

Lab 301 - Intermediate lab

Goal

In this intermediate lab, you'll tackle more complex scenarios and integrate multiple components. You'll learn advanced techniques and best practices for building production-ready AI Agents in your domain.

  • Document processing with agentic workflows

    Build a document classification agentic workflow capable of classifying and extracting data from documents such as contracts and invoices. The agent uses document classification and document extraction to automate data processing and minimize manual work.

    Start Lab

  • Self-service KYC Agent

    In the financial services industry, Know Your Customer (KYC) compliance is critical but often time-consuming. The Self-service KYC Agent streamlines customer onboarding by automating identity verification, document validation, and compliance checks.

    Start Lab

  • Flight Booking Assistant

    In the travel and hospitality industry, booking flights involves multiple steps including searching for flights, comparing prices, checking availability, and managing reservations. The Flight Booking Assistant simplifies this process by providing an intelligent interface that helps users find the best flight options, handle booking modifications, and manage travel itineraries efficiently through natural language interactions.

    Start Lab

Learning Objectives

By the end of this lab, you will be able to:

  • Deterministic Agent
  • Agentic AI workflow tool for deterministic flows
  • Long running tasks
  • Human-in-the-loop approvals

Lab 401 - Advanced lab

Goal

In this advanced lab, you'll learn about governing the agents, integrating third party systems such as ServiceNow, Jira to watsonx Orchestrate. You'll learn advanced techniques and best practices for building production-ready AI Agents in your domain.

  • AI Governance & Vendor Risk

    A smart assistant designed to help compliance and procurement teams evaluate third-party vendors with speed and confidence. It autonomously assesses vendor risk, checks policy compliance, generates tamper-evident audit records, and validates agent robustness against adversarial attacks.

    Start Lab

  • IT Asset Manager

    A specialist agent for tracking and managing IT and business assets in ServiceNow. Users can easily create, update, and view asset records, check asset types, model categories, and configuration items, all from one place.

    Start Lab

  • Issue Manager

    Pre-built Jira Issue manager agent that can create, update, retrieve and delete Jira issues.

    Start Lab

Learning Objectives

By the end of this lab, you will be able to:

  • Governing AI Agents in watsonx Orchestrate
  • Pre-built Agents & Tools
  • Monitoring AI Agents

Support

Lab credits and support: