Large Apparel Manufacturer (unnamed)

A large apparel manufacturer with 70,000 workers relied on floor supervisors to manually track work stoppages and their root causes, including mechanical failures, material shortages, and idle employees. This approach was slow, incomplete, and subject to bias, leaving management wanting earlier and more thorough detection of assembly line issues.

Infolytx deployed a computer vision system that analyzed existing factory surveillance footage using enhanced machine learning models to monitor assembly lines in real time. The system alerted floor supervisors via a mobile app when work stoppages were detected, with fine-tuning driving enthusiastic adoption among supervisors.

Monitored lines showed a 15% productivity increase compared to unmonitored lines after adjusting for external factors. The client expanded the engagement, inviting Infolytx into key client meetings and signing on for additional work and proofs of concept.

• Existing surveillance infrastructure can be repurposed for AI-driven monitoring without major new hardware investment.
• Fine-tuning and supervisor buy-in are critical to adoption of AI augmentation tools on the factory floor.
• Comparing monitored vs. unmonitored lines is an effective method for isolating and quantifying AI-driven productivity gains.