Meta

Meta's Reality Labs had an aggressive hardware roadmap with 7 new product introductions per year involving risky, first-of-its-kind AR/VR technology. The team faced aggressive schedules with limited engineering resources and remote manufacturing partners that slowed down iteration cycles. They needed to eliminate guesswork by identifying and prioritizing challenges and providing possible root causes.

Meta deployed Instrumental across seven programs with 60+ imaging stations capturing images and videos at key assembly steps. Instrumental's Discover AI proactively finds anomalies in hardware images, enabling engineers to focus on solving challenges rather than searching for them. Visual search and AI-enabled measurements accelerate root cause analysis. The platform is now integral to workflow across Product Design, DFX, Quality, Systems Industrial Engineering, and Battery teams with 186 users.

Instrumental saved Meta over 900 engineering weeks annually and delivered a 6X return on investment. Engineers could get a much earlier jump on issues before functional tests failed, avoiding the need for additional Design of Experiments and test units. The platform became integral across multiple teams including Product Design, Quality, and Systems Industrial Engineering, serving 186 active users.

• AI-powered defect discovery enables engineers to identify issues before functional test failures, dramatically saving time
• A single manufacturing data platform can scale across many concurrent NPI programs with hundreds of users
• Proactive anomaly detection eliminates the need for costly experimental builds to determine root causes