Overview

One of the Nordics' largest energy providers needed to take full control of its billing data collection. By replacing proprietary legacy systems and third-party services with an automated, cloud-based platform, they secured vendor independence, scalability, and highly accurate real-time billing data.

Challenge

  • Relied on expensive third-party vendors for critical billing data collection, limiting control over data quality and lead times
  • Outdated hardware and proprietary servers created technical silos that were difficult to maintain and impossible to scale
  • Lacked end-to-end traceability for individual meter readings, creating compliance and auditing risks
  • Faced time-consuming manual bottlenecks when validating data and correcting timestamps from various meter types

Solution

We designed and built a fully automated data pipeline that integrated thousands of IoT devices directly with the company's billing and ERP systems.

  • Automated the collection of telemetry data from over 15,000 metering points with high-frequency resolution
  • Developed automated workflows to convert raw data, validate units, and ensure meter readings were cumulative and accurate
  • Implemented a transaction-oriented cloud architecture guaranteeing zero data loss and 10 years of full traceability
  • Integrated the platform with existing billing systems via standardized APIs for seamless, automated invoicing workflows
  • Built automated monitoring and alarm workflows to identify data collection disruptions before they impacted billing

Impact

  • Eliminated reliance on external third-party services, achieving full vendor independence and lowering operational costs
  • Achieved 100% data integrity with full historical traceability, ensuring strict regulatory compliance
  • Minimized the need for manual data corrections and interpolations through automated data validation
  • Delivered a scalable foundation capable of handling real-time data streaming across thousands of new endpoints
  • Streamlined maintenance operations using predictive alarms to dispatch technicians precisely when hardware fails
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