A faster, lower-risk foundation for autonomous systems

Developing an autonomous machine requires more than a navigation algorithm. Perception, localisation, behaviour, software architecture, hardware interfaces, diagnostics, deployment and operational support must work together as one coherent system. NAC brings these capabilities together through a modular autonomy architecture and a consistent engineering approach. Proven modules and development tools provide a reliable starting point, while customer-specific functionality can be added where it creates genuine application value. This gives customers the flexibility of custom engineering with the efficiency and robustness of a reusable autonomy platform. 

Proven building blocks, tailored to your application 

NAC is not a fixed, one-size-fits-all product. It is a platform where we combine your industry specific requirements, our experience and prebuilt packages into one capable, effective foundation.

Its modular architecture allows Nobleo to select, modify andconfigure for each application. Customer-specific processes remain central, while proven autonomy functionality is built using proven software modules and established engineering methods. 

Accelerating development without compromising flexibility 

Starting every autonomous system from an empty codebase creates avoidable development effort and integration risk. At the other extreme, a closed off-the-shelf product can limit flexibility and make customers dependent on a single supplier. NAC provides a balanced alternative: a high-quality reusable software foundation combined with application-specific engineering. This allows development teams to focus their effort on the functionality that differentiates the customer’s machine, rather than repeatedly rebuilding common autonomy capabilities. 

Working with NAC helps customers: 

• Reduce time-to-market by starting from reusable autonomy components and development tooling. 

• Lower technical risk through an established architecture, defined interfaces and proven engineering practices. 

• Improve robustness by avoiding unnecessary reinvention of common software functionality. 

• Retain flexibility through a modular architecture that can be adapted to different machines, sensors and applications. 

• Avoid unnecessary lock-in by using maintainable software structures and widely adopted technologies such as ROS 2, C++ and Python. 

• Scale more effectively from initial development and simulation to hardware integration, deployment and fleet operation.