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The Vision Integration Platform
Complexity, clearly separated
The industrial-grade platform for customized embedded vision systems
The Vision Integration Platform, or phyVIP for short, integrates the complete vision foundation on a production-ready base board. Project-specific customization is handled via a deliberately simple connector board. Scalable AI performance levels provide additional flexibility for different vision requirements. This clear separation of standardized and application-specific components reduces development effort, design risk and time to series production.
Why this separation accelerates series production
Traditional embedded vision projects generate significant complexity at the board level: power supply, camera interfaces, industrial interfaces, security and thermal requirements all need to be considered together from the start. phyVIP shifts this recurring complexity to a fully developed base board. This allows development teams to focus on the application-specific aspects — shortening development cycles and reducing risk on the path to series production.
Easily integrate cameras and interfaces
Up to two phyCAM-M board-level cameras can be directly connected to the base board. The drivers are already included in the Linux distribution.BSP Up to two phyCAM-M board-level cameras can be connected directly to the base board. The required drivers are already included in the Linux BSP, reducing the need for additional software integration. Flexible FFC cables allow free camera positioning, and compatible lenses are also available. All other interfaces are routed via high-density board-to-board connectors. The integrated wide-range power supply from 12 to 36 V DC reduces the need for additional controllers. Special solutions such as PoE can also be implemented via the connector board. This keeps the platform standardized at its core while allowing application-specific flexibility.
Three performance levels for your vision application
phyVIP is designed for embedded vision applications where AI runs directly on the device. Depending on the application's requirements for computing power, interfaces and scalability, the platform is available with NXP i.MX 8M Plus or NXP i.MX 95 processors.
Based on this architecture, phyVIP can be configured in three AI expansion stages: Core, Edge and Max. This makes it possible to select the right combination of processor platform and AI performance — from a compact vision base to a high-performance platform for demanding workloads.
How phyVIP Simplifies Embedded Vision Development
Reduce development effort, cost and complexity by up to 70%
Build series-ready vision systems with a modular Base Board and project-specific Connector Boards
Scale processing performance with NXP i.MX 95 or NXP i.MX 8M Plus
Add optional AI acceleration with Hailo-8 or NXP ARA-240
Frequently Asked Questions
phyVIP is a modular Vision Integration Platform for industrial embedded vision and edge AI applications. The platform combines a production-ready base board with a project-specific connector board. The base board already integrates key functions such as the processor platform, power supply, camera connectivity and industrial interfaces. Customer-specific adaptations are implemented via the connector board. This significantly reduces development effort, hardware complexity and time-to-market.
phyVIP was developed specifically for demanding embedded vision and AI applications. Typical use cases include industrial image processing, quality control, object recognition, robotics, smart cameras, autonomous systems and AI-powered automation. Thanks to its scalable architecture, the platform is suitable for compact edge AI systems as well as more powerful multi-camera or real-time vision applications.
Yes. phyVIP is designed for edge AI, allowing AI models to run directly on the device — without a permanent cloud connection. This reduces latency and enables real-time decision-making. At the same time, sensitive image and process data can remain local within the system, improving data privacy and reliability. Depending on the application, users can choose between different AI performance levels — from the processor-integrated NPU to additional AI acceleration.
The clear separation between the standardized base board and the project-specific connector board significantly reduces development effort and design risk. The base board already contains complex and validated core functions such as processor integration, power supply, high-speed interfaces and camera connectivity. Changes or customer-specific adaptations primarily affect the connector board. This allows new variants to be implemented more quickly without requiring a complete hardware redesign for every project.
Many key hardware functions of an embedded vision system are already developed, tested and integrated in phyVIP. Teams therefore do not need to start from scratch with topics such as power design, camera integration, high-speed routing or the basic system architecture. Instead, they can focus directly on the actual application. This reduces development time, design risk and NRE effort, significantly accelerating the path to a production-ready solution.
