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Robust.AI builds collaborative warehouse robots (Carter) engineered around computer vision, perception, and real-time autonomy—the stack leans heavily on embedded C/C++, Linux, and GCP with robotics-grade tooling (STM32, CAD, LabVIEW). The project list and pain-point pattern reveal an organization focused on fleet reliability at customer sites: debugging autonomy failures, reducing downtime, and validating perception under real-world warehouse variability dominate near-term work. Hiring skews senior and engineering-heavy, indicating they're scaling operational depth rather than headcount.
Tech Stack 32 technologies
Core StackC++ Python Linux Solidworks FMEA C STM32 USB I2C UART RS485 CMake C/C++ LabVIEW TestStand CAD Google Workspace Yocto Buildroot Ubuntu GCP
What Robust.AI Is Building
◆Challenges
- Reducing robot downtime
- Maintaining robot fleet uptime
- Root cause analysis of incidents
- Reducing robot failure rates
- Robust perception for real-world variability
- Balancing product needs with long-term innovation
- Integrating perception into robotic systems
- Validating system behavior under real-world constraints
- Debugging issues across autonomy stack
- Improving test observability
▲Active Projects
- Next generation warehouse robotic systems
- Expansion of systems at early-stage customer sites
- Deploying robotic fleets in warehouses
- Providing training to customer teams
- Commissioning and debugging robotic systems
- Robot reliability testing program
- Safety and compliance roadmap
- State-of-the-art computer vision for robotics
- Robust perception for real-world variability
- Best practices for data collection and model deployment
Hiring Activity
Steady15 roles · 5 in 30d
Department
Seniority
Company intelligence
