Fortune 200 manufacturing conglomerate with 156,000 employees, 200+ facilities globally, $67 billion annual revenue
A Fortune 200 manufacturing conglomerate faced $340 million in annual unplanned downtime costs across 200+ facilities. The company needed AI-powered predictive maintenance deployed globally across 14 countries with varying data residency requirements and 40+ equipment manufacturers. Of 134 identified vendors, most had experience only with single-facility deployments and lacked multi-region infrastructure.
The COO's team used Enterprise AI Exchange to filter for vendors with verified enterprise-scale deployments (100+ facilities), multi-region infrastructure in at least 10 countries, SOC 2 Type II and ISO 27001 certification, and proven manufacturing experience. The directory identified five vendors meeting stringent requirements, all with successful global deployments at 100+ facility manufacturers. The team conducted structured evaluation including proof-of-concept pilots at three facilities.
The company successfully deployed predictive maintenance AI across all 200+ facilities within 18 months. Unplanned downtime decreased by 68% (surpassing 60% goal), saving $231 million annually. Equipment maintenance costs declined by 23%. Overall equipment effectiveness improved by 12 percentage points, translating to $89 million in additional production capacity without capital investment.
Pre-verified vendor certifications accelerated evaluation timeline
Human-verified trust scores eliminated redundant due diligence
Proven deployments at comparable scale reduced implementation risk
Verified compliance certifications prevented regulatory failures