H2O.ai Announces H2O Document AI to Automate Document Processing

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Leading AI cloud provider H2O.ai, announced the general availability of H2O Document AI, a machine learning service that understands, processes, and manages the large volume and types of documents and unstructured text data that businesses and organizations handle every day. H2O Document AI streamlines processes, reduces costs, and discovers new information and insights contained in documents. H2O Document AI “learns as it goes,” continuously improving processing accuracy using H2O.ai’s latest innovations in machine learning and deep learning to achieve automation across business verticals and use cases not previously possible.

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Core business processes in digital world rely on documents and unstructured or semi-structured data that contain valuable information critical to business operations. The definition of a ‘document’ continues to expand, and includes PDFs, emails, scans, images, paper and web forms, faxes and e-faxes, chats from chatbots, free-form text, and more. 80% of enterprise data is unstructured or in a format that is not machine-readable or readily available. However, traditional AI document processing solutions use Optical Character Recognition (OCR) or Robotic Process Automation (RPA), which are limited by rules-based and template-driven constraints.

Additionally, the OCR and RPA solutions have limited capabilities to self-learn. Not surprisingly, the results from these existing document processing solutions are often lackluster. Without other options, some organizations make do with sub-optimal products/solutions that don’t scale and increase inefficiencies.

Other organizations have not adopted any automation and rely on people to review, process, and act on documents. The manual labor required to process documents is tedious, can be error-prone, and keeps workers from doing more meaningful, impactful, and enjoyable work. In either scenario, using existing automation or no automation, handling documents is expensive and time-consuming—companies spend an average of $20 to file and store a single document, employees spend up to 50% of their time searching for information and can take, on average, 18 minutes to locate a single document.

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