Proception.AI Tech Stack

Dexterous humanoid robot hardware and control systems

Robotics Engineering Palo Alto 11–50 employees Privately Held

Proception.AI builds dexterous humanoid robots with embedded control stacks spanning STM32H7, ESP32, Rust, C, and RTOS (FreeRTOS, Zephyr, PREEMPT_RT), paired with simulation (Isaac Sim, MuJoCo) and perception (ROS 2, SLAM, multi-sensor fusion). The tech mix reflects a hardware-first, safety-critical engineering culture—no cloud-only abstractions, heavy real-time and FPGA work. Active projects span mechanical design, motor firmware, robotic hand safety systems, and sensor calibration pipelines. The hiring shape (9 engineers, 1 manufacturing, 1 research) and transition focus toward mass production signals they're moving from prototype validation into scaled manufacturing.

Tech Stack 28 technologies

Core StackRust Python Linux C++ AWS CAD STM32H7 ESP32 C FreeRTOS Zephyr PREEMPT_RT RTOS CAN I2C EtherCAT ROS ROS 2 Isaac Sim MuJoCo C/C++ Azure Jetson Orin MIPI CSI-2 V4L2 FPGA CAN-FD Embedded C/C++

What Proception.AI Is Building

◆Challenges

Scaling data infrastructure
High-performance logging
Inventory management delays
Inefficient assembly workflows
Production inefficiencies

▲Active Projects

Sensor calibration and time-synchronization pipelines
Humanoid robot mechanical system design
Camera system architecture for humanoid robots
Real-time firmware for motor control
Safety-critical systems for robotic hands
Real-time slam and state-estimation for humanoid robots
Multi-sensor fusion pipelines
Neural scene representations
Pilot builds and mass production transition
Visualization tools for multimodal sensor streams

Hiring Activity

Decelerating10 roles · 3 in 30d

Department

Engineering

Manufacturing

Research

Seniority

Mid

Senior

Junior

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About Proception.AI

Proception.AI designs and manufactures humanoid robots capable of fine manipulation tasks. Based in Palo Alto with 11–50 employees, the company operates as a vertically integrated hardware business: mechanical design, embedded firmware, sensor architecture, and control algorithms all in-house. Current operational priorities include sensor fusion and time-synchronization pipelines, real-time state estimation, and the transition from pilot builds to production-ready manufacturing. Internal pain points center on data infrastructure scaling, logging performance, assembly workflow efficiency, and inventory management—typical friction points for hardware startups scaling from low-volume to higher-volume production.

HeadquartersPalo Alto

Company Size11–50 employees

Hiring MarketsUnited States

Frequently Asked Questions

What embedded platforms does Proception.AI use?

STM32H7, ESP32, Jetson Orin, and FPGA-based compute. Real-time firmware runs on FreeRTOS, Zephyr, and PREEMPT_RT Linux. Motor control and sensor I/O use CAN, I2C, EtherCAT, and MIPI CSI-2 protocols.

What is Proception.AI working on?

Sensor calibration, humanoid mechanical design, camera architectures, motor control firmware, robotic hand safety systems, SLAM/state estimation, multi-sensor fusion, neural scene representations, and the transition to mass production.