Client & Background

ProMach Solutions manufactures heavy industrial machinery (packaging lines, conveyor systems) for factories across North America. Their after-sales support had become a major cost center: machine operators and plant managers frequently called for help with error codes, spare parts, maintenance scheduling, and diagnostics.

Problem Statement
ProMach’s support team faced:

• Large volumes of repetitive spare-parts questions (“Which part do I need?”, “Is it in stock?”, “What’s delivery lead time?”)
  
• Diagnostic calls that required technical decision-making: operators didn’t always know how to report error codes, and calls were inefficient
  
• Maintenance coordination was labor-intensive, involving multiple back-and-forth calls
  
• Serving global customers meant support had to scale across languages and time zones
  

Solution via Implement Artificial Intelligence

1. Spare-Parts Voice Agent
   
   • We created an AI agent connected to ProMach’s ERP / parts database, allowing it to answer questions about part numbers, inventory, and lead times in real time.
     
2. Diagnostics Flow
   
   • We built a decision-tree dialog based on machine error codes and operator manuals: when a caller reports an error code, AI asks follow-up questions (“Is the red light blinking? What’s the code number?”), then walks them through checks.
     
3. Maintenance Scheduling
   
   • The AI is integrated with ProMach’s dispatch system: once a maintenance need is identified, the AI proposes available technician slots, confirms with the client, and logs it all without human intervention.
     
4. Multilingual and Global Support
   
   • We trained and deployed the AI in multiple languages, supporting ProMach’s international customers and enabling 24/7 support coverage.
     

Results & ROI

• The AI now handles about 50% of spare-parts calls, freeing human staff for more complex or strategic tasks.
  
• Diagnostic resolution time (before escalation) dropped by ~40%, because AI pre-screens and triages issues.
  
• Maintenance scheduling became 30% more efficient, with fewer coordination errors and quicker appointment setting.
  
• Global support scaled: ProMach reduced reliance on local-language human agents by supporting common inquiries via AI during off-hours.
  
• Customer satisfaction from after-sales support improved, as faster initial response and accurate part information enhanced the customer experience.
  
• Field technicians reported fewer unnecessary site visits, because the AI filtered out non-urgent or misdiagnosed issues before dispatch.
  

Insights & Strategic Recommendations

• Integrating voice AI with critical backend systems (ERP, scheduling) unlocks the most value.
  
• Diagnostic flows benefit from structured decision trees built from domain expertise and manuals.
  
• Language support is not just translation — domain-specific phrasing (industrial jargon) must be trained.
  
• Ongoing refinement: review call transcripts monthly, refine flows, and adjust escalation thresholds.
  

How IAI – Implement Artificial Intelligence Added Value

With the help of Implement Artificial Intelligence help, ProMach:

• Reduced support costs and headcount burden
  
• Increased first-call self-resolution via automated diagnostics
  
• Scaled global support without hiring a proportional number of staff
  
• Improved on-site service efficiency by reducing unnecessary dispatches