Industries we focus on
Four strategic markets where architecture, integration, cybersecurity and lifecycle management determine whether Edge AI reaches real operation. These are our focus areas and opportunities, not a list of completed projects.
Challenge
Charging infrastructure is becoming a large, distributed and connected system, exposed to growing cybersecurity and regulatory requirements.
Edge AI opportunity
Local intelligence for charging control, energy optimisation and vehicle-to-infrastructure connectivity, managed securely across the fleet of devices.
Areas of application
- EV charging infrastructure
- Intelligent charging and distributed control
- Vehicle-to-infrastructure connectivity
- Energy management and optimisation
- Cybersecurity and regulatory readiness
Challenge
Moving AI from pilots to the plant floor requires secure, manageable computing that integrates with existing OT systems.
Edge AI opportunity
Local AI inference for machine vision, predictive maintenance and industrial automation, deployed and updated as part of one governed system.
Areas of application
- Industrial Edge AI
- Machine vision
- Predictive maintenance
- Industrial IoT
- OT/IT integration
- Secure and manageable industrial computing
Challenge
Distributed energy assets need monitoring, control and optimisation close to where energy is generated and stored.
Edge AI opportunity
Edge AI for local energy intelligence, asset monitoring and optimisation across distributed infrastructure.
Areas of application
- Distributed power generation
- Energy storage and microgrids
- Local energy intelligence
- Energy asset monitoring and optimisation
- Edge AI for distributed energy infrastructure
Challenge
Agricultural environments are remote, distributed and often poorly connected, which makes cloud-only AI impractical.
Edge AI opportunity
Machine vision and local AI at the edge for precision agriculture, crop monitoring and automation in connected agricultural environments.
Areas of application
- Precision agriculture
- Machine vision and local AI
- Distributed sensing
- Remote monitoring
- Edge computing in connected agricultural environments