Allows the users to monitor system progress and performance, verify information, and tag forms that need verification

Scanned documents from different sources (printers, scanners, fax machines, etc.) often exhibit distortions – including scaling, rotation, and blurring. Specto uses image processing techniques to clean up these images, so they can be processed and analyzed accurately.

Using supervised machine learning Specto can automatically classify documents into specific categories based on client requirements.

Specto can recognize a full form/document by detecting all the page numbers and associated objects such as form fields (e.g. Address, Name, Date), text boxes, and handwriting

Data is automatically extracted from paper or digital documents structured or unstructured using Optical Character Recognition (OCR)

The user can view all the forms that Specto processed and any of the extracted data. Specto automatically assigns a quality score to the form processed and information extracted. If a document has a low-quality score it is sent to a user for review

The user can tag documents to give feedback to the machine learning model. When enough feedback is collected xFact will retrain the model. Over time, the user’s verification of the data makes Specto smarter and allows for rectification of error files, unmatched data, and duplicates

Specto gives the user the ability to export to CSV, JSON, and XML this allows the processed forms from Specto to be loaded into a client database

Each Specto instance creates a storage database, enabling the client to have a history of all the data Specto has processed and the ability to run analytics and reports.

Specto can identify if the form is in the right order and if not, it will intelligently reorder the form if the pages are misaligned or pages are missing.

Automatic engine recovery feature that senses when an engine fails and automatically re-initializes it for the next form.