Precision insight at network scale

Autonomous close-quarter inspection of electricity grid assets, delivering repeatable engineering-grade condition data

Autonomous close-inspection for resilient power networks

Electricity grid owners and operators face growing pressure to maintain ageing assets as demand, network complexity and regulatory expectations increase.

Helicopters remain essential for wide-area situational awareness and emergency response, and ground teams are critical for maintenance and fault repair. However, neither approach delivers repeatable, component-level inspection across networks. While drones can provide this level of detail, conventional drone deployment has proven difficult to scale safely and consistently at national level.

sees.ai provides centrally controlled, Level-4 autonomous close-quarter inspection of transmission and distribution assets - including spans and towers. The system is designed to support inspection programmes across large networks, capturing secure, repeatable condition data that complements existing inspection programmes and supports long-term asset management.

Scalable close inspection supporting long-term electricity grid asset planning

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Autonomous close-quarter inspection and data capture on network assets

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Central control room enabling multiple concurrent inspection operations

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Component-level engineering-grade data capture on assets

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Structured and repeatable datasets optimised for AI/ML processing

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Longitudinal insights supporting condition monitoring and maintenance planning

Inspections are enabled by a centrally controlled autonomous system designed for operation on high-voltage networks

Unlike conventional drone approaches that rely on pre-mapped environments or prior site surveys, the system operates in real time, adapting to asset geometry, surrounding structures and changing conditions such as vegetation encroachment. This enables close-quarter inspection without separate pre-flight surveys.

Operations are conducted Beyond Visual Line of Sight (BVLOS), allowing long sections of the network to be inspected from a limited number of launch locations. This reduces land access requirements and supports inspection programmes across transmission and distribution networks.

The capability is delivered as one integrated inspection system, with safety and security oversight across aircraft, operations and data capture. Outputs are structured and platform-agnostic, enabling integration into existing processing, analytics and visualisation environments.

Designed for long-term programmes, the system integrates with existing operational, regulatory and asset management frameworks.

How autonomous close-inspection supports National Grid operations

What our customers say...

  • The post-QA imagery is of excellent quality. The flight patterns, viewing angles and span samples provide the level of detail needed, particularly for identifying issues that would normally only be found once a circuit has returned to service, by having this information it helps create a snapshot of the system post installation and can also help reduce circuit downtime.”

    K Westlake, Senior Project Manager, Strategic Infrastructure, National Grid

  • By handling non-intrusive inspection tasks, this [sees.ai] technology enables our highly skilled lineworkers to focus more efficiently on the complex, hands-on work that requires human expertise, and will form an important part of how we continue to manage our assets and deliver a safe and reliable network..”

    K Fairhurst, OHL Operations Director, National Grid

Customers & partners

National Grid
Nats
Vodafone
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Microsoft-Logo
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Marshall

Why sees.ai

Built for national-scale transmission and distribution networks.
Designed to complement existing helicopter surveys and ground-based inspection programmes.
Safe, repeatable highly autonomous close-quarter inspections.
Centralised operations reducing on-site constraints.
Consistent, repeatable structured data supporting longitudinal asset condition assessment and analytics.
Proprietary, full-stack system operated under a single safety and security framework.

Get in touch

Whether you are exploring new inspection approaches or looking to scale existing programmes, sees.ai is happy to share how centrally controlled autonomous close-inspection fits within a wider grid strategy.

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