Cybord

Cybord provides a visual AI analytics solution for the electronics manufacturing industry, aiming to ensure the quality, authenticity, and traceability of electronic components. The company was founded in 2018 by Dr. Eyal Weiss, who now serves as the Chief Technology Officer. The idea for Cybord originated from a crisis Dr. Weiss experienced in a major defense project, where a single counterfeit three-cent capacitor caused significant issues, highlighting the widespread problem of faulty components. Dr. Weiss has over 20 years of experience in technology development and R&D management, including a role at the Soreq Nuclear Research Center. He is joined by CEO Oshri Cohen, who brings over two decades of management experience in operations and supply chain from high-tech multinationals like Nvidia.

The company's core business revolves around its AI-powered software platform that analyzes 100% of electronic components on the assembly line. This platform targets Original Equipment Manufacturers (OEMs) and Electronics Manufacturing Services (EMS) providers globally. By leveraging a massive database of over four billion component images, its machine learning models inspect parts for authenticity, damage, and compliance in real-time as they are being placed on printed circuit board assemblies (PCBAs). This process helps to prevent counterfeit or defective components from being used, addressing a multi-billion dollar problem for the industry and reducing the risk of costly product recalls. The business model appears to be software-as-a-service (SaaS), providing clients with access to its analytics platform and data.

Cybord's product suite includes several key offerings. The Kingfisher solution inspects incoming reels of components before they enter the production line, allowing manufacturers to securely source parts from various suppliers. The Aquila and Osprey solutions provide quality assurance and traceability during the assembly process itself. In March 2025, the company launched its Real-Time Interception (RTI) solution, which identifies and rejects faulty components with 99.9% accuracy before they are placed on the board. This technology is integrated into pick-and-place machines from manufacturing partners like Fuji America and Siemens. The company has secured significant funding, including a $4 million Seed round in March 2022 and an $8.7 million Series A round in September 2024, to accelerate its growth and global expansion.

Keywords: electronic component verification, visual AI analytics, supply chain security, counterfeit component detection, printed circuit board assembly, PCBA inspection, electronics manufacturing, component traceability, quality assurance, machine learning, deep learning, hardware security, OEM solutions, EMS providers, real-time interception, component authentication, manufacturing analytics, defect prevention, production line optimization, hardware reliability