Businesses and enterprises have lots of unstructured data - especially documents and image scans. These documents span a wide range of types, formats, and contain embedded knowledge. However, the value is mostly hidden & inaccessible . This leads to misclassification of categories, resulting in additional staff resources, slowing down referral processing time as well as increased patient wait times for referral documents including clinical notes, insurance information and patient medical history.
Organizations can focus on quicker time to value for data scientist users and business consumers with powerful and flexible product features in H2O Document AI. Decreases these inefficiencies providing cost savings, in addition to improving customer satisfaction and organization operational efficiency
Enables solutions and ecosystems that emphasize continuous learning to optimize document understanding, scalable processing, and timely management. This solution allows the enterprise to go beyond OCR-based template methods and RPA-based memorization efforts which are not scalable as variety and volumes change. Document AI frees up employees to do higher value work activities and provides relief to users/analysts/managers by increasing efficiencies and reducing process redundancies.