Samsara (NYSE:IOT) is focused on digitizing the world of operations. We help customers across many industries—including food and beverage, utilities and energy, field services and government—get information about their physical operations into the cloud, so they can operate more safely, efficiently and sustainably. Our sensors collect billions of data points per day and on-device processing is instrumental to our success. We’re constantly developing, improving and deploying ML models at the edge. We’ve found that the traditional development process—where ML scientists create models and hand them off to firmware engineers for embedded implementation—is slow and often produces difficult-to-resolve differences between the original model and the embedded implementation. In this talk, we’ll present an alternative development process that we’ve adopted with good results. In this process, firmware engineers develop a general framework that ML scientists use to design, develop and deploy their models. This enables quick iterations and fewer confounding bugs.