Case study | Energy

Modernizing Transformer Inspections with AI-Assisted Data Capture

Replacing manual evaluations with a digital inspection platform that automates data capture with AI-assisted OCR and  maintains quality control through human oversight.

Overview

A leading electrical power and distribution provider relied on lengthy, manual transformer evaluations  that slowed inspections and depended heavily on experienced personnel.  10Pearls developed a tablet-based evaluation solution that digitized inspections and significantly accelerated  evaluation  while improving consistency and accuracy.

94% accuracy 
in nameplate extraction
Reduced evaluation time
from days to ~1 hour

Challenge

The organization needed a more efficient and accurate way to conduct transformer evaluations. Existing processes required multiple layers of testing, manual recordkeeping, and on-site involvement from experienced personnel. Evaluators frequently relied on experts to interpret equipment information. Documenting results manually created additional delays and inconsistencies throughout the evaluation process.

Solution

10Pearls created a tablet-based evaluation platform that digitized transformer inspection workflows. Evaluators could capture testing data directly on tablets, replacing manual documentation, and creating a standardized process for recording inspection findings. 

The solution incorporated AI-assisted optical character recognition (OCR) technology to automatically extract information from complex transformer nameplates in approximately 30 seconds with roughly 94% accuracy. Inspection data collected in the field was then routed through an online review portal, enabling reviewers to validate results and maintain quality controls through human oversight at every stage of the evaluation process. The result was a faster, more scalable evaluation workflow that reduced reliance on manual processes while improving consistency and operational efficiency.  

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