H2O.ai has announced general availability of the H2O Document AI machine learning service that understands, processes and manages the large volume and types of documents and unstructured text data that businesses and organisations handle every day.
Learning as it goes, thanks to machine learning, the service streamlines processes, reduces costs and discovers new information and insights contained in documents. Organisations can quickly and accurately process documents and unstructured text data to increase productivity and find hidden insights.
H2O Document AI combines intelligent character recognition, natural language processing, computer vision, and layout intelligence for a sophisticated labeling and training workflow and self-service capabilities. It has flexible out-of-the-box document pre- and post-processing and seamlessly integrates with existing business processes and workflows.
Additionally, it not only identifies entities and classifies them, but also understands the document and constituent pages, sections and layout to provide additional context that can help drive decision-making and lead to an improved end-customer experience.
Document data can easily be used to build smart searches on large archives of documents, or it can be loaded into a datastore to be queried, analysed, audited, or used by other applications.
The workflow goes from labeling to training to scoring to low touch integrations and consumption options. It is customisable, extensible, and works in conjunction with H2O AI Cloud so customers can easily scale to additional use cases.
“Our banking, insurance, health, audit, and public sector customers each process billions of documents every year. H2O Document AI enables customers to sieve intelligence across a wide variety of document types not possible before, with unprecedented accuracy and speed,” said Sri Ambati, CEO and Founder of H2O.ai.
Entelechy Asia 