Digitization & Cognitive Process Automation of the Electronic proof of delivery (EPOD) process completely
Enter your heading descriptiImages of incoming documents like LR receipt, Invoices and Weighment Slips from the EPOD application are picked up by DataFindr-Transit. These images are analyzed using AI powered techniques such as Computer Vision or Computer Machine Reading to extract a host of data and intelligence that is vital for paperless process automation, faster billing cycle and providing host of other value added services to transporters that allows for capture and validation of data. In case of an erroneous data input DataFindr-Transit is configured to send out automated alerts.
How DataFindr-Transit works
DataFindr-Transit will connect to your existing IT infrastructure and continually fetch images of the positions of a tank/container anywhere in a facility.
DataFindr-Transit’s recognition engine extracts data from the images.
It also processes the data to understand and analyse the passage of the tank/container through the yard.
It then passes on the data to your ERP systems using secure APIs.
How does DataFindr-Transit achieve near-100% accuracy?
Multiple algorithms for region-of-interest detection
There are multiple algorithms working simultaneously on region-of-interest identification thus ensuring 100% detection.
Before extraction, DataFindr accommodates inconsistencies in data placement, such as printed matter being slightly outside the box or line.
De-noising systems from simple Otsu methods to deep learning-based segmentation algorithms improve DataFindr’s extraction quality.
Dual algorithmic journeys for building quorum
It builds quorum using two or more algorithms for every field. Each algorithm has different deep learning bases and maths for feature extraction methods, number of layers, loss functions etc.
Claim your POC
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