Edge Intelligence to Cloud Systems

AI systems engineered with processors, accelerators, sensors, and neural networks can replace the traditional IT systems and adapt to your business

Vertically Integrated AI Products




Data Connectors

Neural Networks


AI Systems Engineering

AI is no longer a layer of software or application. The AI system architecture has evolved inside-out with the latest advances in semiconductor processors, low level computational libraries, and trained neural networks. Our systems engineering team can solve the most complex engineering problems for delivering your AI products. These hardware and software engineers are equipped with expertise to benchmark enterprise standards, performance, and security at all stages of the AI system life cycle.

AI Studio

ICURO made significant investments with artificial intelligence (AI) hardware in equipping the Silicon Valley AI systems lab in Santa Clara, California with enterprise grade sensors, semiconductor chip sets, edge computing processors, graphical processing units, system on chips, robots, and actuators.

ICURO's AI Studio demonstrates our commitment to people growth initiatives in artificial intelligence. It offers a unique hands-on AI system infrastructure and industry use cases for both software and hardware engineers to become AI system specialists.

Team Up With Our
AI Specialists

The AI specialists at ICURO brings in a unique expertise of fully integrating hardware and software, and data to deliver business growth outcomes. This world’s best hands-on professionals brings both business and technical expertise across all layers of the AI technology stack.

  • Machine learning to define and execution of neural network training, and pruning and optimization techniques for inferencing.
  • Sensor fusion includes sensor hardware and algorithms to fuse LiDAR data, camera images, IMU data using algorithms to perceive the environment and deliver action.
  • Embedded processors that orchestrates and coordinates computations among accelerators.
  • Accelerators to perform highly parallel operations required by AI and enables simultaneous computations.
  • Edge computing architecture includes edge hardware and software stack for sensing and actuation along with reasonable power, communications and security.
  • Mechatronics for the mechanical aspects of actuation, electronics, control units, and robotics.