super.AI automates nameplate data extraction for global TIC company with 99.98% accuracy
A global TIC services company manually transcribed key information from asset and equipment nameplate photographs, resulting in a 7% error rate for serial number transcriptions alone and high labor costs that could not scale to meet customer workload.
The company achieved 99.98% data accuracy processing more than 100,000 data points, with an estimated economic impact greater than $5M per year from labor cost savings and enhanced data processing capacity, plus 2X faster customer onboarding.
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Frequently asked questions
What did this team achieve with this AI workflow?
The company achieved 99.98% data accuracy processing more than 100,000 data points, with an estimated economic impact greater than $5M per year from labor cost savings and enhanced data processing capacity, plus 2X fa…
What tools did this team use?
Super.Extract.
What results were reported?
Serial number transcription error rate (before): 7%; Data accuracy achieved: 99.98%; Estimated economic impact per year: greater than $5M per year; Data points processed: 100,000+ (source-reported, not independently verified).
How is this data entry ops AI workflow structured?
Nameplate photographed → Data upload via API → AI extracts nameplate data → Human workers validate output → Results fetched automatically.