Document submission and processing have always entailed filling heaps of forms, sending scans, and numerous data checks and re-checks – something that requires much time and effort until you opt for OCR-powered AI.
OCR stands for Optical Character Recognition technology that detects an image, breaks it into fields, scans them, and automatically transfers data to respective forms (agreements, applications, CRM bases, etc.).
Imagine that you want to travel abroad. No more long and tedious communication with a travel agent, no more visa applications to fill in, and no more fear of making a mistake and spoiling a form — just scan your passport with OCR, and all your further applications will be automatically populated with necessary data. This technology adopted by major corporations and government agencies can reduce paperwork and alleviate customer stress.
OCR is also used to:
- automatically read bank cards
- instantly recognize passports
- automatically enter invoice details for online payment
- quickly enter data into agreements
- reconcile customer data obtained from different sources
- automatically populate CRM base
- and do many other things
However, the system is not ideal yet, and Dbrain, the technology developer, admits text recognition errors to be its greatest shortcoming, especially when processing photos with sharp folds, or those affected by backlights, or taken by a low-class phone. To solve the problem, Dbrain added two functions to the OCR technology.
- Context analysis. A scanned text is additionally processed by a neural network taught to consider a context and automatically correct errors, similar to how Google corrects mistypes in search requests.
- A human-in-the-loop concept. Text extracted by the system is transmitted, in real time, to skilled experts connected to Dbrain platform, for manual check. Such human-and-machine combination improves recognition accuracy from 85% to 99% in all texts, including handwritten ones. Another remarkable advantage of the manual check is that it solves manuscript-related problems as the algorithm learns to find and correct errors, with recognition quality growing over time.
Users should not worry about their personal data confidentiality, since Dbrain assures personal data to be transmitted in an anonymized form. The algorithm blurs an image and breaks user’s passport into several fields on the client side, with information coming to Dbrain servers in an anonymized form, thus preventing from field-to-person match. Fields are recognized independently from each other and transmitted to a client in an encrypted form over HTTPS, all in less than a second.