super.AI automates nameplate data extraction for global TIC company achieving 99.98% accuracy
A global TIC company's core asset management process required manually transcribing data from equipment nameplate photographs, producing a 7% error rate on serial number transcriptions and an inability to handle growing customer workload in-house.
The automated solution achieved 99.98% data accuracy (a 6x improvement), processed over 100,000 data points, generated more than $5M estimated annual economic impact from labor cost savings and enhanced capacity, and delivered 2x faster customer onboarding.
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Frequently asked questions
What did this team achieve with this AI workflow?
The automated solution achieved 99.98% data accuracy (a 6x improvement), processed over 100,000 data points, generated more than $5M estimated annual economic impact from labor cost savings and enhanced capacity, and…
What tools did this team use?
Super.Extract.
What results were reported?
Data accuracy: 99.98%; Accuracy improvement: 6x; Estimated economic impact: 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 image upload via API → AI nameplate data extraction → AI and human worker validation → Automated result retrieval.