$2500 worth of human effort saved every month

About the Client

  • A major Shipping company spent thousands of dollars on data entry for their Bills of Lading.
  • Format variability and excessive content (at least 5 text fields and multiple tables) made this process tedious.
  • With each Bill of Lading requiring 5,000+ keystrokes, data accuracy took a hit. And even with a (manual) maker checker, accuracy continued to remain a pain point.


  • We trained Neutron using samples of the various formats and then initiated the data extraction process.
  • With ML at its core, Neutron learned and got better.
  • 6 months post-deployment, the client saw 90% accuracy in data identification and extraction.


With key resources now focused on revenue-generating activities along with significantly faster processing, the client enjoyed a substantial positive impact on their bottom line.

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