Navarik announced today completion of phase one research and development for their machine learning data extraction project. Traditionally, the extraction of raw data from paper inspection documents has been time-consuming and manually intensive. With the use of leading edge machine learning technology Navarik will significantly improve the accuracy and efficiency of this process.
Company specific terminology, unique trade settling data points and fragmented documentation are some of the key industry issues being addressed through this data extraction project. Current and future Navarik customers will benefit from improved efficiency in their workflow process as the tool is trained to improve accuracy over time.
“We’re excited to have completed the initial requirements and research phase of this project and to be moving forward with testing the tool” said Richard Halldearn, Chief Technology Officer at Navarik. “Machine learning has the potential to improve the way in which commodities are moved around the world”.
Phase two of the project will include testing the tool on a wide variety of inspection documentation including the extraction of data from hand written notes, an ability which has not been available in the past.
For more information about Navarik’s machine learning data extraction project please email us at email@example.com