Autonomous & Robotics

Autonomous system and robotics developers use various workflows to create their perception, planning, and control models. These workflows typically involve collecting, processing, and storing massive amounts of data so that data scientists can build datasets for training and validating their models. As these workflows are utilized, customers encounter bottlenecks that prevent them from using their resources. These bottlenecks usually manifest as slow data processing, leading to backlogs that force teams to select subsets of data for processing, potentially missing essential edge cases that help improve system performance. 

Larger cloud providers excel at one thing: hyperscale. However, they struggle to handle the large volumes of data generated by autonomous systems and robotics. Multiple cameras, LiDAR’s, Radars, bus-collected data, and other sensor outputs create massive data challenges if the necessary compute acceleration devices cannot manage the volume of data.  A more custom-tailored approach is required to eliminate bottlenecks and achieve the full performance needed to process data in a timely manner. This is where Cirrascale comes in. With in-house expertise in data collection and analysis for autonomous systems and robotics, we understand where the risks lie and how to mitigate them. Additionally, our cloud is structured differently, so you never experience hidden fees. Large providers often squeeze you with extra fees and charges to get your data out of their storage clouds, leading to a sense of lock-in because the cost of extracting data becomes prohibitively expensive. With us, you won’t face that issue, as we don’t charge any ingress or egress fees.