A deep learning approach to document processing
Germany and Poland-based process automation startup Hypatos has raised $US11.8 million in a seed round of funding. It is working to apply deep learning tech to power a wider range of back-office automation, with a focus on industries with heavy financial document processing needs, such as the financial and insurance sectors.
Hypatos is applying language processing AI and computer vision tech to speed up financial document processing for business use cases such as invoices, travel and expense management, loan application validation and insurance claims handling via -- touting a training data set of more than 10 million annotated data entities.
It says the new seed funding will go on R&D to expand its portfolio of AI models so it can automate business processing for more types of documents, as well as for fuelling growth in Europe, North American and Asia. Its customer base at this point includes Fortune 500 companies, major accounting firms and more than 300 software companies.
While there are plenty of business process automation plays, Hypatos says its use of deep learning tech supports an "in-depth understanding" of document content -- which in turn allows it to offer customers a "soup to nuts" automation menu that covers document classification, information capturing, content validation and data enrichment.
It dubs its approach "cognitive process automation" (CPA) versus more basic applications of business process automation with software robots (RPA), which it argues aren't so contextually savvy -- thereby claiming an edge.
As well as document processing solutions, it has developed machine learning modules for enhancing customers' existing systems (e.g. ECM, ERP, CRM, RPA); and offers APIs for software providers to draw on its machine learning tech for their own applications.
"All offerings include machine learning pipeline software for continuous model training in the cloud or in on-premise deployments," it notes in a press release.