Key results
The company
nybl
nybl.aiEnterprise AI platform for predictive analytics and industrial automation.
Result highlights
- 50% inspection cost reduction
- 20% reduction in repair costs
- 30% decrease in inspection time
- 50% reduction in safety incidents
- 20% increase in grid uptime
The story
A science-based AI technology company in the Middle East serving energy and utility clients, including a national grid operator managing 400,000 kilometers of power infrastructure.
Manual inspections of remote and hazardous assets were slow, expensive, and prone to human error due to a shortage of skilled technicians. The company needed a scalable automated solution that could also guarantee model reliability and compliance with industry regulations.
The organization embedded IBM Maximo Visual Inspection and watsonx.governance into its platform to automate fault detection and continuously monitor model health. This architecture was validated through a 1,000-kilometer pilot on high-voltage lines before scaling to monitor the full national network. The system uses deep learning to identify defects while simultaneously tracking model bias and drift to ensure compliance.
Scope & timeline
- Expansion to 400,000 km infrastructure