Cloud-connected AI software platform for autonomous mobile robots at scale
Brain Corp operates the control software layer for the world's largest deployed AMR fleet—over 40,000 robots in commercial spaces. The tech stack is deeply embedded: NVIDIA Isaac Sim for simulation, RTOS + ARM Cortex + LiDAR for real-time robot control, GCP + Kubernetes for cloud orchestration, and heavy C/C++ middleware. Current project velocity reveals a company mid-refactor: re-architecting core robotics software, migrating middleware to C++, and shipping simulation-based validation pipelines. This engineering-centric hiring mix (14 of 15 open roles) focused on mid to staff-level engineers signals scaling pressure on reliability and cloud infrastructure.
Brain Corp builds BrainOS, a cloud-connected operating system that powers autonomous mobile robots deployed in retail, logistics, and facility management. The platform abstracts hardware variability across OEM partners while handling perception (LiDAR, sensors), navigation, and fleet telemetry. The company sells to Fortune 500 brands and OEMs who embed BrainOS into their own robot fleets. With 40,000+ robots operating in the field, Brain Corp operates at the intersection of embedded systems, real-time control, and cloud-scale fleet management—a narrow, capital-intensive niche requiring both robotics depth and production operations maturity.
Core embedded: RTOS, Embedded Linux, ARM Cortex, LiDAR, MQTT, C/C++. Cloud: GCP, Kubernetes, Docker. Simulation: NVIDIA Isaac Sim. Development: Python, Go, GitLab CI/CD, Jenkins, pytest, Jira. Hardware design: OrCAD, Allegro, Altium.
Over 40,000 autonomous mobile robots powered by BrainOS are operating worldwide in commercial public spaces including retail, logistics, and facility management.
Brain Corp's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.