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Customer Support Triage (Extended) Lab

Ready to Build on Your Own?

This is a self-contained, self-led lab that you can complete independently. Work through the guide at your own pace using your own Boomi account. No workshop event or instructor required!

Business Situation​

Customer support teams face an overwhelming volume of incoming support cases daily, with agents spending countless hours manually reading case descriptions, researching similar issues, drafting responses, and determining appropriate routing based on case urgency and sentiment. This reactive approach leads to slower response times, inconsistent service quality, and frustrated customers waiting for resolutions to their issues.

Traditional support workflows struggle to keep pace with growing case volumes while maintaining the personalized attention customers expect. Support agents are bogged down with repetitive tasks—looking up product documentation, checking previous case histories, and manually categorizing cases—leaving little time for complex problem-solving and meaningful customer interactions.

Challenges​

  • Manual processing of support cases creates bottlenecks and delays in response times
  • Inconsistent quality of responses across different support agents and teams
  • Difficulty in accurately categorizing and routing cases based on urgency and sentiment
  • Time-consuming research required to generate informed, accurate responses
  • Lack of automated workflows to update CRM systems with case insights and proposed resolutions
  • Inability to scale support operations without proportionally increasing headcount

Solution​

Build an intelligent Customer Support Insights Agent that automates the entire support case triage workflow. The agent monitors for new support cases, analyzes case content, researches relevant information, generates proposed responses, adds insights as private comments in the CRM system, performs sentiment analysis, and intelligently routes cases—all without human intervention.

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This activity was adapted from the following Boomi & AWS Advanced Workshop: https://workshops.aws/card/boomi.

Use Case​

In this lab, you'll build a Customer Support Insights Agent that transforms your support operations through intelligent automation.

Your solution will:

  1. Monitor for new customer support cases in your CRM system (simulated in this lab)
  2. Automatically investigate and research each support case issue using AI-powered analysis
  3. Generate proposed responses and resolutions based on case content and historical knowledge
  4. Add proposed responses as private comments directly within CRM support cases for agent review
  5. Perform sentiment analysis to detect customer emotion (positive, negative, neutral) and determine appropriate case routing
No CRM Required

This lab simulates CRM interactions using secure API endpoints—no actual CRM system access is required. You'll learn the complete pattern that can be adapted to any CRM platform.

Business Outcomes​

  • Accelerated Response Times: Automatically generate proposed responses in seconds instead of minutes or hours
  • Improved Support Quality: Consistent, well-researched responses based on comprehensive case analysis
  • Intelligent Case Routing: Automated sentiment analysis ensures urgent or negative-sentiment cases are prioritized appropriately
  • Increased Agent Productivity: Support agents focus on high-value interactions while AI handles repetitive research and drafting
  • Seamless CRM Integration: AI-generated insights flow directly into existing support workflows without disrupting agent processes
  • Scalable Operations: Handle growing case volumes without proportionally increasing support team size

Key Performance Indicators (KPIs)​

  • Average Response Time Reduction: Measure the decrease in time from case creation to first proposed response generation
  • Case Resolution Rate: Track the percentage of cases resolved using AI-generated proposed responses with minimal agent modifications
  • Sentiment-Based Routing Accuracy: Monitor how effectively sentiment analysis correctly identifies and routes high-priority negative-sentiment cases
  • Agent Time Savings: Calculate the hours saved per agent by automating research, response generation, and CRM updates
  • Customer Satisfaction Scores: Measure improvements in CSAT scores as faster, more consistent responses improve customer experience

Workshop Structure​

This lab is divided into five progressive parts that build a complete end-to-end intelligent support automation solution.

Part 1: Build your Tooling​

Set up the secure foundation for AI-powered support by creating a Web Service Listener and API Tool that expose your product data to agents safely.

  • Create governed APIs and endpoints for secure data access
  • Build reusable, low-code components that accelerate agent development

Part 2: Build your Agent​

Assemble your AI agent by defining its goals, tasks, and instructions, then validate its logic through interactive testing.

  • Define agent profile, goals, and natural language instructions
  • Configure tools and test agent responses interactively

Part 3: Complete and Deploy​

Add guardrails for responsible AI use, build integration workflows to update CRM cases, and deploy your fully functional agent.

  • Apply guardrails to protect sensitive data
  • Create integration tools that let agents launch automated workflows
  • Test and deploy your production-ready agent

Part 4: Use Agents in Processes​

Connect your agent to real-world workflows by configuring Control Tower, building integration processes that simulate new support cases, and extracting agent responses for CRM updates.

  • Authenticate and govern every AI interaction from day one
  • Run headless workflows that handle triage end-to-end automatically
  • Experience the unified platform where AI seamlessly connects to integration

Part 5: Sentiment Analysis​

Extend your agent with sentiment analysis capabilities to detect customer emotion, intelligently route cases, and drive immediate operational efficiency.

  • Add sentiment analysis tasks that evaluate customer tone
  • Automatically route cases based on sentiment scores (positive, negative, neutral)
  • Close the loop with complete automation from case arrival to resolution
Ready to Get Started?

Let's build your Customer Support Insights Agent! Click Next below to begin with the prerequisites.