Zach Rattner, CTO and Co-Founder of Yembo, discusses the use of synthetic data to automate sensor processing tests, particularly in the context of Yembo's AI-powered virtual home inspections, which serve moving and insurance companies. The company utilizes computer vision algorithms to analyze client-submitted home videos, emphasizing the importance of high-quality video capture for optimal AI performance. Rattner explains how Yembo employs real-time user tips and motion monitoring through device accelerometers and gyroscopes to ensure quality video capture, highlighting the challenges of implementing motion data in production-grade applications due to device and browser inconsistencies. Despite these challenges, Yembo uses automated Cypress tests to verify and iterate new features, reducing reliance on manual testing and fostering rapid development. The approach includes recording motion data from various devices to create synthetic test scenarios, thereby ensuring Yembo's algorithms function correctly in diverse conditions.