AI Systems Engineering


A Fully Integrated AI Solution Stack




Data Connectors

Neural Networks


AI Systems Engineering

From validating your AI models to building a product, our systems engineering services can work with your team to solve the most complex engineering problems in AI. Our multi-skilled team takes a collaborative approach to navigate the issues of standards, interfaces and data security to deliver solutions at any part of the system life-cycle.

  • Validate use cases
  • Build Proof-of-concept
  • Modular AI Solutions
  • AI Product design & development
  • Adaptive Testing frameworks

Bringing Hardware And Software Together With A Team Of AI Specialists

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.

The fully integrated AI system architecting, designing, and development includes machine learning, machine vision, sensor fusion, edge intelligence, robotics, embedded processors, and cybersecurity.

Team Up With AI Specialists To Deliver Business Growth

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.

Case Studies By Industries

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