Case Study: Predictive Maintenance AI
Predictive Maintenance helps reduce loss of sales.
Background
Machinery breakdown on rigs was resulting in loss of sales.
A leading Australian Geotech and Resource company was suffering regular loss of sales when key components on their fleet failed. As their daily revenue was bound to the machinery being in operation, any reduction in breakdowns was an increase in total revenue. They had a fleet of over 140 machines with fairly standardised components, supported by accurate maintenance reporting.
Remi AI connected the latest version of the OCR platform, DocIntelligence, into the clients Application pipeline and immediately set up the custom A.I modules to begin training on the most complex documents.
Within 4 days, the A.I modules in DocIntelligence - OCR, Neural Networks, and NLP - had all been trained to between 86%-95% accuracy. This was 6% higher than the APIs the client had tested previously.
These were then brought into production in the applications pipeline.
Approach
A 2 hour process reduced to 2 minutes.
Results
With accuracies as high as 95%, DocIntelligence reduced the time spent extracting data from the applications from an average of 2 hours to under 2 minutes. This allowed the Applications Team to increase the number of applications they were processing by more than 6000%.