Symbotic's software continuously learns from the data its robots generate — up to 10 terabytes a day — to get smarter over time. It uses this data to find patterns, improve how robots are assigned tasks, and push performance updates back out to the fleet, similar to how a smartphone app improves through software updates driven by usage data.

Every robot, sensor, and robotic cell in the system continuously transmits operational data — including movement patterns, task outcomes, and environmental conditions — to Symbotic's cloud infrastructure. Proprietary machine learning algorithms process this data to identify inefficiencies, recognize patterns, and generate optimized behaviors that are pushed back to the fleet as software updates. The system also enables what Symbotic calls "dynamic storage" — merchandise is spread throughout the storage structure opportunistically, like data on a hard drive, creating more options for the routing and optimization algorithms to exploit. This approach has delivered measurable gains: in FY2025, SymBots showed a 25% increase in miles driven and transactions completed per robot per day compared to the prior year.