
Reduction Per Year
In Inspection Costs
More Images Analyzed Per Hour
Versus Manual Review
The next generation of infrastructure inspections are virtual.
Grid Vision® powered by eSmart Systems provide Inspection Management for transmission and distribution utilities globally. By leveraging Collaborative-Artificial Intelligence (AI), Grid Vision enables a condition-based approach to overhead line inspections and provide departments with full visibility of the grid’s general health and maintenance needs.
By utilizing Grid Vision, our customers have realized the following benefits:
- Reduced failure rates
- Increased safety
- Reduced costs
- Extended asset life
Grid Vision Insight
Inspection data aggregated to actionable-analytics.
Grid Vision Insight aggregates imagery, metadata and observations into a comprehensive view from executive level to specific component drill-downs in a web-based visualization tool. By making inspection data accessible to the broader organization, utilities can focus on:
- Maintenance investments on high priority assets
- Enhance asset management
- Increase the efficiency of field visits
- Improve planning
Why Us?
Grid Vision Inspect enables a truly virtual and digital inspection process and delivers
automation from day one through the 30+ AI models that are already trained on over 3 million global images. Human experts have also logged tens of thousands of hours of operational virtual inspections utilizing Grid Vision, providing invaluable feedback to continually enhance time saving features that allow inspectors to focus on the highest-value activities.
- Mature world-leading AI
- Built for scale
- Collaborative-AI
- Unique asset-centric approach
- Global partner ecosystem
- Hardware-agnostic
Collaborative-AI
Continuously Improved Inspections
Our approach to AI is what is often referenced to as Collaborative AI. Our AI and the users of Grid Vision work together in our software. The users give continuous feedback to our AI which then improves and brings more value to the Grid Vision software.
This approach includes all our users, which leads to a strong self-reinforcing effect that continuously improves our AI, a network effect that benefits all our customers.