Abstract: This invention generally relates to a process, system and computer code for updating of computer applications based on collecting automation information related to a current application such as processing power, load, footprint, and performance attributes, determining a system automation profile; using an artificial intelligence based modeler for analyzing data, applying the data to an artificial intelligence model for training and predicting performance, adjusting the artificial intelligence model to achieve an updated automation criteria with optimal values, wherein the optimal values provide input to an automation criteria library for storing and updating a prior automation criteria, and exporting the upgraded automation criteria values for incorporation in a computer-to-be-updated, to achieve a reliable automatic update.

Abstract: A system and method of automatically learning new keywords in a document image based on context such as when a never before seen keyword exists surrounded by other key-value pairs. A machine learning based approach leverages subword embeddings and two-dimensional geometric contexts in a gradient boosted trees classifier. Keys may be composed of multi-word strings or single-word strings.

Abstract: An optical character recognition system employs a deep learning system that is trained to process a plurality of images within a particular domain to identify images representing text within each image and to convert the images representing text to textually encoded data. The deep learning system is trained with training data generated from a corpus of real-life text segments that are generated by a plurality of OCR modules. Each of the OCR modules produces a real-life image/text tuple, and at least some of the OCR modules produce a confidence value corresponding to each real-life image/text tuple. Each OCR module is characterized by a conversion accuracy substantially below a desired accuracy for an identified domain. Synthetically generated text segments are produced by programmatically converting text strings to a corresponding image where each text string and corresponding image form a synthetic image/text tuple.

Abstract: This invention generally relates to a process, system and computer code for updating of computer applications based on collecting automation information related to a current application such as processing power, load, footprint, and performance attributes, determining a system automation profile; using an artificial intelligence based modeler for analyzing data, applying the data to an artificial intelligence model for training and predicting performance, adjusting the artificial intelligence model to achieve an updated automation criteria with optimal values, wherein the optimal values provide input to an automation criteria library for storing and updating a prior automation criteria, and exporting the upgraded automation criteria values for incorporation in a computer-to-be-updated, to achieve a reliable automatic update.

Abstract: This invention generally relates to a process, system and computer code for enabling users to create adapters that enable application automation by collecting automation information; locate application controls and tracking changes between an older and a newer version of the application, such changes to include addition of one or more new data fields, removal of one or more data fields, change in data field type (i.e. type of data held in the field); change field layout; and change the underlying technology framework of the application; to present the changes using an exception management model to the user, so user can by way of example provide feedback in a visual instead of programmatic manner; store the changes, so as to make the adapters resilient to application changes and upgrades; and incorporating the changes to upgrade the application.

Abstract: This invention generally relates to a process, system and computer code for updating of computer applications based on collecting automation information related to a current application such as processing power, load, footprint, and performance attributes, determining a system automation profile; using an artificial intelligence based modeler for analyzing data, applying the data to an artificial intelligence model for training and predicting performance, adjusting the artificial intelligence model to achieve an updated automation criteria with optimal values, wherein the optimal values provide input to an automation criteria library for storing and updating a prior automation criteria, and exporting the upgraded automation criteria values for incorporation in a computer-to-be-updated, to achieve a reliable automatic update.

Abstract: This invention generally relates to a process and computer code for enabling users to create adapters that enable application automation processes that allow customers to define compliance boundaries using a rules-based compliance firewall for their service providers and allow service providers to perform automation on customer machines remotely while adhering to customer's compliance requirements.

Abstract: This invention relates to a process, system and computer code to sequence processes to automate based on return on investment or ROI. The process and system divides considers the mix of human and robotic steps to optimize cost, quality and cycle-time of the process; classifying a process based on an entity and corresponding divisional partition, such as one of a group, department or stakeholder, and (2) generating key criteria; categorizing the ROI; applying constraints such as one of (a) cost, (b) quality or cycle-time; comparing one of (a) the human entered data, (b) the robot entered data, (c) the bot acquired data, with respect to one (i) cost, (ii) quality or (iii) cycle-time; queuing one of (a) a human task, (b) a robot task, or (c) a bot constructed task; storing one of (a) tracking process changes, (b process details and constraints in the event of a change.