Abstract: A system includes a memory and a processor. The memory stores a queue that includes a sequence of slots, each of which is configured to store a request. The processor receives, from a user device, a request for information. In response, the processor stores the request in an end slot of the queue. The processor collects values for parameters associated with the system. The processor determines, based on the request and the collected values for the parameters, an estimate of a time to generate a response to the request. Generating the response includes identifying an application for use in generating the response, generating, based on a set of videos of processes previously performed using the application, instructions for interfacing with the application to generate the response, and executing the instructions to interface with the application. The processor further transmits, to the user device, the estimate of the time.

Abstract: Apparatus and methods for intelligently monitoring multiple bots for failure or predicted failure and notifying a user through a proximate Internet-of-Things (“IoT”) device are provided. A program may receive configuration files for each IoT device and access to monitor each bot. The program may monitor each bot through a resiliency scanner module. The program may generate a report about a failure or predicted failure of a bot. The program may activate a self-healing engine to attempt to heal the bot. The program may activate an event-stream engine. The event-stream engine may determine which IoT device to transmit a report and notify the user through that IoT device to the failure or predicted failure. The user may respond through the IoT device or another device.

Abstract: A device configured to identify automated process instructions for a network device. The automated process instructions include instructions for performing a series of actions on the network device. The device is further configured to identify a first time instance for executing the automated process instructions that does not occur within a time interval associated with a first system update for the network device and to execute the machine-executable code at the first time instance to perform the series of actions on the network device.

Abstract: Aspects of the disclosure relate to upgrading an application within a simulated version of an enterprise system to detect and correct potential errors as a result of the upgrade. A computing platform may create a simulated version of the enterprise system by receiving metadata associated with the enterprise system, and converting the metadata into system parameters. Virtual parameters may be created by the computing system based on upgrading an application within the simulated version of the enterprise system. The computing system may determine errors caused by the application upgrade within the simulated version of the enterprise system based on differences between the system parameters and the virtual parameters. The computing platform may determine actions to correct the errors and input the results and feedback into an AI engine to further refine the accuracy and reliability of the computing platform over time.

Abstract: A system includes a memory and a processor. The memory stores a set of videos each of which is associated with an application of a set of applications and depicts a process performed using the application. For each video, the processor generates metadata associated with the depicted process, and stores the metadata within a collection of metadata in the memory. The processor receives a request for information from a user. In response, the processor identifies an application of the set of applications for use in generating a response to the request. The processor generates, based on the collection of metadata, instructions for interfacing with the first application to generate the response. The processor executes the instructions to interface with the first application to generate the response, and transmits the response to the user.

Abstract: A device configured to identify automated process instructions for a network device. The automated process instructions include instructions for performing a series of actions on the network device. The device is further configured to identify a first time instance for executing the automated process instructions that does not occur within a time interval associated with a first system update for the network device and to execute the machine-executable code at the first time instance to perform the series of actions on the network device. The device is further configured to detect a second system update for the network device while executing the machine-executable code, to pause the execution of the machine-executable code at a breakpoint at a second time instance after detecting the second system update, and to resume execution of the machine-executable code after the breakpoint at a third time instance after the second system update is complete.

Abstract: Systems, computer program products, and methods are described herein for implementing parametric optimization analysis for resource selection. The present invention is configured to determine a first set of requirements associated with a resource exchange agreement; identify one or more non-fungible tokens (NFTs) for one or more categories of past resource exchange agreements based on at least the first set of requirements; extract, from the one or more NFTs, one or more resource descriptors associated with one or more past resource exchange agreements in the one or more categories; predict, using a machine learning subsystem, an optimal resource valuation model for one or more resources that meet the first set of requirements using the one or more resource descriptors and the first set of requirements; and transmit control signals configured to cause a first end-point device to display the optimal resource valuation model.

Abstract: A system includes a memory and a processor. The memory stores a set of videos each of which is associated with an application of a set of applications and depicts a process performed using the application. For each video, the processor generates metadata associated with the depicted process, and stores the metadata within a collection of metadata in the memory. The processor receives a request for information from a user. In response, the processor identifies an application of the set of applications for use in generating a response to the request. The processor generates, based on the collection of metadata, instructions for interfacing with the first application to generate the response. The processor executes the instructions to interface with the first application to generate the response, and transmits the response to the user.

Abstract: Aspects of the disclosure relate to an intelligent resource evaluation engine. A computing platform may monitor the plurality of RPA machines to detect parameter information. The computing platform may store the parameter information along with corresponding RPA machines as a key value pairs in a database. The computing platform may identify first current parameter information for a first RPA machine using the key value pairs. The computing platform may input the first current parameter information into an intelligent resource evaluation model, which may output first machine selection information for the first RPA machine. Based on identifying that the first RPA machine is sufficient to execute the first robotic automation process, the computing platform may send direct the first RPA machine to execute the first robotic automation process.

Abstract: A system includes a memory, a display, and a processor. The processor determines that the display is displaying an element associated with an application. The element includes at least one of a graphical user interface and a web browser. In response to determining that the display is displaying the element, the processor records a video of the display, which depicts a process performed using the element, to obtain a first set of information from the application. The processor extracts, from the video, metadata associated with the process depicted in the video. The processor generates, based at least in part on the extracted metadata, a set of instructions for interfacing with the application. When executed by the processor, the set of instructions are configured to cause the processor to interface with the application to obtain the first set of information. The processor further stores the set of instructions in the memory.

Abstract: A system includes a memory and a processor. The memory stores a set of videos each of which is associated with an application of a set of applications and depicts a process performed using the application. For each video, the processor generates metadata associated with the depicted process, and stores the metadata within a collection of metadata in the memory. The processor receives a request for information from a user. In response, the processor identifies an application of the set of applications for use in generating a response to the request. The processor generates, based on the collection of metadata, instructions for interfacing with the first application to generate the response. The processor executes the instructions to interface with the first application to generate the response, and transmits the response to the user.

Abstract: A system includes a memory and a processor. The memory stores a queue that includes a sequence of slots, each of which is configured to store a request. The processor receives, from a user device, a request for information. In response, the processor stores the request in an end slot of the queue. The processor collects values for parameters associated with the system. The processor determines, based on the request and the collected values for the parameters, an estimate of a time to generate a response to the request. Generating the response includes identifying an application for use in generating the response, generating, based on a set of videos of processes previously performed using the application, instructions for interfacing with the application to generate the response, and executing the instructions to interface with the application. The processor further transmits, to the user device, the estimate of the time.

Abstract: A system for determining transactions eligible for currency transaction report (CTR) exemption using a quantum computing algorithm is described. The system may further leverage a distributed computing architecture for manual review and filing of CTRs and/or approving a CTR exemption as determined by the quantum computing algorithm.

Abstract: A system for determining transactions eligible for currency transaction report (CTR) exemption using a quantum computing algorithm is described. The system may further leverage a distributed computing architecture for manual review and filing of CTRs and/or approving a CTR exemption as determined by the quantum computing algorithm.

Abstract: A device configured to identify automated process instructions for a network device. The automated process instructions include instructions for performing a series of actions on the network device. The instructions include machine-executable code partitioned into a plurality of code segments using breakpoints where each breakpoint temporarily pauses the execution of the machine-executable code between a pair of code segments. The device is further configured to identify a first time instance for executing the automated process instructions that does not occur within a time interval associated with a system update for the network device. The system update is configured to modify one or more settings on the network device. The device is further configured to execute the machine-executable code at the first time instance to perform the series of actions on the network device.

Abstract: A system for classifying tasks based on workflow patterns detected on workflows through a real time video feed that shows steps being performed to accomplish a plurality of tasks. Each task is associated with a different set of steps. The system accesses a first set of steps known to be performed to accomplish a first task on the webpages. The first set of steps is represented by a first set of metadata. The system extracts a second set of metadata from the video feed. The second set of metadata represents a second set of steps to perform a second task. The system determines whether the second set of metadata corresponds to the first set of metadata. If it is determined that the second set of metadata corresponds to the first set of metadata, the system classifies the second task in a class to which the first task belongs.

Abstract: A device configured to identify automated process instructions for a network device. The automated process instructions include instructions for performing a series of actions on the network device. The device is further configured to identify a first time instance for executing the automated process instructions that does not occur within a time interval associated with a first system update for the network device and to execute the machine-executable code at the first time instance to perform the series of actions on the network device. The device is further configured to detect a second system update for the network device while executing the machine-executable code, to pause the execution of the machine-executable code at a breakpoint at a second time instance after detecting the second system update, and to resume execution of the machine-executable code after the breakpoint at a third time instance after the second system update is complete.

Abstract: A device configured to identify automated process instructions for a first network device. The automated process instructions include instructions for performing a series of actions on the first network device. The device is further configured to identify a first time instance for executing the automated process instructions that is before a time interval associated with a system update for the first network device, to identify a second time instance corresponding with a start time of the time interval associated with the system update for the first network device, and to identify a third time instance corresponding with an end time of the time interval associated with the system update for the first network device.

Abstract: A device configured to identify automated process instructions for a network device. The automated process instructions include instructions for performing a series of actions on the network device. The instructions include machine-executable code partitioned into a plurality of code segments using breakpoints where each breakpoint temporarily pauses the execution of the machine-executable code between a pair of code segments. The device is further configured to identify a first time instance for executing the automated process instructions that does not occur within a time interval associated with a system update for the network device. The system update is configured to modify one or more settings on the network device. The device is further configured to execute the machine-executable code at the first time instance to perform the series of actions on the network device.

Abstract: Various systems, methods, and computer program products are provided for dynamically generating an API. The method includes extracting metadata from a command recording of a system API. The command recording of the system includes a starting breakpoint and an ending breakpoint for one or more repetitive processes. The method also includes determining one or more API parameters for an API to be generated based on the extracted metadata. The method further includes dynamically generating the API based on the API parameters. The method still further includes causing an authentication of the credentials relating to the API via robotic process automation.