Abstract: Robotic process automation (RPA) systems with improved user access enable a user to interact with an RPA system by way of a communication platform. The communication platform can support text messaging and/or speech communication with a virtual agent that in turn is able to interface with an RPA system. In this way, a user of the communication platform is able to conveniently interact with the RPA system, such as in a conversational manner. By analyzing and interpreting the conversation, the user's intent or desire can be determined and then carried out by the RPA system. Thereafter, results from the RPA system can be formatted and returned to the user. In one embodiment, to better understand the user's intent or desire from the text messages or natural language communications (i.e., voice or speech communications), artificial intelligence can be used.

Abstract: A robotic process automation system includes a server processor that performs an automation task to process a work item, by initiating a java virtual machine on a second device. A first user session that employs credentials of a first user for managing execution of the automation task is also initiated on the second device. The server processor loads into the java virtual machine, with a platform class loader, one or more modules, such as logging and security, that perform functions common to the sets of task processing instructions. A first class loader a first set of task processing instructions is also loaded. Then each instruction in the first set of task processing instructions is loaded with a separate class loader. The server processor causes execution, under control of the first user session, on the second device, the task processing instructions that correspond to the work item.

Abstract: A server responds to a request to perform a first automation task to process a work item from the plurality of work items, on a first computing device that is separate and independent from the server. The server receives a request from the first computing device to download the first automation task and queries a distribution information file to identify one or more other computing devices that have a copy of the first automation task. The server provides to the first computing device, an identifier for each of one or more other computing devices that has a copy of the first automation task. If the distribution information file does not contain an identification of any other device that has a copy of the first automation task, then the server processor causes the first automation task to be retrieved and to be provided to the first computing device.

Abstract: Automation controls and associated text in images displayed by a computer application are automatically detected by way of region-based R-FCN and Faster R-CNN engines. Datasets comprising images containing application controls, where the application controls include images of application where width is greater than height, width is equal to height and height is greater than width are retrieved and each dataset is processed with the R-FCN and Faster R-CNN engines to generate a software robot configured to recognize corresponding application controls. Text is recognized by an optical character recognition system that employs a deep learning system trained to process a plurality of images 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.

Abstract: A robotic process automation system includes a server processor that performs an automation task to process a work item, by initiating a java virtual machine on a second device. A first user session that employs credentials of a first user for managing execution of the automation task is also initiated on the second device. The server processor loads into the java virtual machine, with a platform class loader, one or more modules, such as logging and security, that perform functions common to the sets of task processing instructions. A first class loader a first set of task processing instructions is also loaded. Then each instruction in the first set of task processing instructions is loaded with a separate class loader. The server processor causes execution, under control of the first user session, on the second device, the task processing instructions that correspond to the work item.

Abstract: A server responds to a request to perform a first automation task to process a work item from the plurality of work items, on a first computing device that is separate and independent from the server. The server receives a request from the first computing device to download the first automation task and queries a distribution information file to identify one or more other computing devices that have a copy of the first automation task. The server provides to the first computing device, an identifier for each of one or more other computing devices that has a copy of the first automation task. If the distribution information file does not contain an identification of any other device that has a copy of the first automation task, then the server processor causes the first automation task to be retrieved and to be provided to the first computing device.

Abstract: Robotic process automation (RPA) tasks for operating on data within a productivity program may be initiated by single user action from within the productivity program. A user device is provided with a plugin program that provides an automation user interface within the productivity program. A request to perform an automation task on data in a productivity file is received along with identification of a software robot to perform the automation task. The request also specifies data from the productivity file. The request is provided to a control room server that controls execution of a plurality of different automation tasks by a plurality of different software robots. Results of the automation task are received from the control room server and are provided to the plugin program, which provides the results of the automation task to the user within a productivity file accessible by the user.

Abstract: A robotic process automation (RPA) system receives task prioritization inputs that specify prioritization for processing of a set of RPA tasks. The tasks are performed in accordance with the specified priorities. The RPA system also receives queue orchestration commands that specify conditions under which tasks processed from a first queue are sent to another queue for subsequent processing. The RPA system also provides service level automation in accordance with specified parameters. Further task prioritization may be specified to provide quality of service performance.

Abstract: Key/Value pairs, each comprising a keyword string and an associated value, are extracted automatically from a document image. Each document image has a plurality of pixels with each pixel having a plurality of bits. A first subset of the plurality of bits for each pixel represents information corresponding to the document image. The document image is processed to add information to a second subset of the plurality of bits for each pixel. The information added to the second subset alters the appearance of the document image in a manner that facilitates semantic recognition of textually encoded segments within the document image by a Deep Neural Network (DNN) trained to recognize images within image documents. The DNN detects groupings of text segments within detected spatial templates within the document image. The text segments are mapped to known string values to generate the keyword strings and associated values.

Abstract: A robotic process automation system operates to generate a plurality of bots, each bot comprising one or more configurable commands arranged to perform assigned tasks. A processor is configured to execute instructions that when executed cause the processor to provide to a user a plurality of recorders to permit the user to create one or more bots for storage in data storage. The instructions implement a plurality of recorders to permit capture of user interaction in a variety of application environments. A secure recording mode is selectable by an administrator of the robotic process automation system, for preventing display to a user of an entire screen of information generated by an application while the user is generating a bot. The administrator can employ the robotic process automation system permit display to the user of only selected fields of information, along with associated labels.

Abstract: A robotic process automation system includes a server processor that performs an automation task to process a work item, by initiating a java virtual machine on a second device. A first user session that employs credentials of a first user for managing execution of the automation task is also initiated on the second device. The server processor loads into the java virtual machine, with a platform class loader, one or more modules, such as logging and security, that perform functions common to the sets of task processing instructions. A first class loader a first set of task processing instructions is also loaded. Then each instruction in the first set of task processing instructions is loaded with a separate class loader. The server processor causes execution, under control of the first user session, on the second device, the task processing instructions that correspond to the work item.

Abstract: Computerized RPA methods and systems that increase the flexibility and lower the cost with which RPA systems may be deployed are disclosed herein. In one embodiment, an RPA system and method avoids the need for preinstalled RPA software on a device employed by a user to create and/or execute software robots to perform RPA. In another embodiment, an RPA system and method provides a capability to execute software robots that may have been encoded in one or more programming languages to execute on an operating system different than that employed by a server of the RPA system.

Abstract: Computerized RPA methods and systems that increase the flexibility and lower the cost with which RPA systems may be deployed are disclosed herein. In one embodiment, an RPA system and method avoids the need for preinstalled RPA software on a device employed by a user to create and/or execute software robots to perform RPA. In another embodiment, an RPA system and method provides a capability to execute software robots that may have been encoded in one or more programming languages to execute on an operating system different than that employed by a server of the RPA system.

Abstract: Methods and systems that detect and define virtual objects in remote screens which do not expose objects. This permits simple and reliable automation of existing applications. In certain aspects a method for detecting objects from an application program that are displayed on a computer screen is disclosed. An image displayed on the computer screen is captured. The image is analyzed to identify blobs in the image. The identified blobs are filtered to identify a set of actionable objects within the image. Optical character recognition is performed on the image to detect text fields in the image. Each actionable object is linked to a text field positioned closest to a left or top side of the actionable object. The system automatically detects the virtual objects and links each actionable object such as textboxes, buttons, checkboxes, etc. to the nearest label object.

Abstract: A robotic process automation system with improved security in the form of a credential vault includes data storage for storing bots. The data storage also stores credentials in encrypted form where the credentials are not associated with any of the plurality of bots. The credentials include standard credentials and user specific credentials. A processor is operatively coupled to the data storage and is configured to execute instructions that when executed cause the processor to provide to an administrator a control console. The instructions implement a standard credential generator and a user specific credential generator, to generate a user specific credential template useable by a user to enter credentials specific to the user. The instructions also implement a configurable locker that is stored in encrypted form in the data storage to associate a set of users as a group and to provide selected standard credentials to the group.

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: 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.