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Aurtra (acquired Schneider Electric)

Aurtra provides IoT-based asset management solutions specifically for transformers, utilizing real-time monitoring and data analytics to enhance operational efficiency for industries, utilities, and OEM partners. The platform addresses the challenges of high maintenance costs and unplanned downtime by enabling proactive management and optimization of transformer assets.

Founded 20161300+ followers
Updated 4 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Maintaining transformers, critical assets in electrical grids and industrial facilities, is costly and prone to unplanned downtime. Traditional monitoring methods often lack real-time visibility into transformer health, making it difficult to proactively address potential issues before they escalate into major failures. This can lead to increased maintenance expenses, reduced operational efficiency, and potential safety hazards.

Solution

Aurtra provides an IoT-based asset management platform specifically designed for transformers, enabling real-time monitoring and data-driven insights. By deploying sensors on transformers, Aurtra captures critical operational data, such as temperature, vibration, and oil levels. This data is then transmitted to a cloud-based analytics engine, where machine learning algorithms identify anomalies, predict potential failures, and optimize performance. The platform delivers actionable intelligence to industries, utilities, and OEM partners, empowering them to proactively manage their transformer assets, minimize downtime, and extend equipment lifespan.

Target Audience

Aurtra's primary customers include industries, utilities, and OEM partners that rely on transformers for their operations and seek to improve asset management efficiency and reduce maintenance costs.

Features

  • Real-time monitoring of key transformer parameters via IoT sensors
  • Cloud-based analytics engine with machine learning for predictive maintenance
  • Anomaly detection and fault prediction algorithms
  • Customizable dashboards and alerts for proactive issue management
  • Secure data transmission and storage
  • Integration with existing asset management systems
This profile is AI-generated and may contain inaccuracies.