Case Study
February 5, 2026

Retail Tech Leader Achieves 92% AI Accuracy, 28% Fewer Escalations, and 50% Faster Onboarding with Agentic AI-led Field Service

Field Services
Retail

Field service leaders know the hidden cost of complexity: skilled technicians spending valuable time searching for information, validating parts, and escalating routine issues. As installed bases grow and service expectations rise, these inefficiencies compound fast.

This case study shows how a global digital solutions provider partnered with iOPEX to deploy a field-ready Agentic AI platform that eliminated search friction, reduced expert dependency, and measurably improved technician productivity and repair speed. 

Within just months, the organization eliminated up to 30 minutes per day previously lost to manual part-number lookups and document searches. Requests for expert assistance dropped by 28%, reducing weekly helpdesk calls from 519 to 372. Among high-frequency users, productivity increased by 14%, unlocking nearly one additional task per technician per day within four months.

On-site repair duration fell by 15 minutes per visit, directly improving customer uptime while lowering service costs.

Download the case study to see how Agentic AI can eliminate field service friction, scale technician expertise, and turn everyday service operations into a sustained productivity advantage.

Text LinkRetail Tech Leader Achieves 92% AI Accuracy, 28% Fewer Escalations, and 50% Faster Onboarding with Agentic AI-led Field Service
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