Methods and systems for registering a digital command in a multi-application

This disclosure relates to methods for registering a command in a multi-application network. The methods include: determining a computing operation for the multi-application network; receiving a command associated with the computing operation for a digital request data object; encapsulating, in a registration object: first semantic or syntactic data associated with the first command, a digital path to a first application for executing the first computing operation, and context data associated with the first command; and storing, in a database, the first registration object. In addition, the methods include: receiving a first input; analyzing the first input to determine second semantic or syntactic data; determining the first command associated with the first computing operation; accessing the first registration object based on the determined first command; and accessing, based on the digital path of the first registration object, a first application for the first computing operation.

TECHNICAL FIELD

The present disclosure relates to methods, systems, and computer program products that facilitate the implementation and usage of digital commands in a multi-application network.

BACKGROUND

Integrating and leveraging data from multiple applications and/or domains associated with a multi-application network is needed to facilitate process optimizations as well as efficient data cataloging, data tracking, exception event handling, data contextualization, and/or data storage. In particular, it is increasingly becoming needful to develop and leverage computational tools that efficiently register, activate, and/or deactivate commands within a multi-application network based on data associated with one or more digital request data objects associated with a multi-application network and/or other contextual data associated with the multi-application network, and/or user-specific, or group-specific data of users and/or groups that use the multi-application network.

SUMMARY

The present disclosure is directed to methods, systems/apparatuses, and computer program products that implement the registering of a command in a multi-application network. The methods include determining a first computing operation for the multi-application network. The first computing operation, according to one embodiment, may be associated with a first digital request data object. For example, the first computing operation may comprise: a status check of the digital request data object; a review of at least one exception event associated with the digital request data object; quantitative and/or qualitative analysis of the first digital request data object; etc. The methods may further comprise receiving a first command for the first computing operation associated with the first digital request data object. The methods further include encapsulating, in a first registration object, one or more of: first semantic or syntactic data associated with one or more components of the first command for the computing operation associated with the first digital request data object; a digital path to a first application for executing the first computing operation; and context data associated with the first command for the first computing operation associated with the first digital request data object. The methods also include storing, in a database associated with the multi-application network, the first registration object. In addition, the methods include receiving, a first input associated with a second digital request data object. The first input may comprise textual data and/or auditory or vocal data received using an input device. In one embodiment, the textual and/or auditory data may comprise natural language inputs with associated syntactic and semantic data (e.g., semantic and/or syntactic parameters) characterizing the first input. According to some embodiments, the semantic and/or syntactic data include a logical flow of one or more words comprised in the first input. Furthermore, the semantic and/or syntactic data may include data associated with an arrangement or organization of one or more words or text comprised in the first input. The methods may further include analyzing the first input to determine second semantic or syntactic data associated with the first input. The methods may further include determining the second semantic or syntactic data substantially matches the first semantic or syntactic data. In response to determining if the second semantic or syntactic data substantially matches the first semantic or syntactic data, the method proceeds to identifying the first command associated with the first computing operation. The methods may further include determining the digital path comprised in the first registration object. According to one embodiment, the methods include accessing, the first registration object based on the first command following which the digital path comprised in the first registration object is determined. Based on the digital path comprised in the first registration object, a first application for the first computing operation is accessed following the first computing operation is executed using the first application for the second digital request data object.

According to one embodiment, the methods include receiving a second input associated with a third digital request data object. The method may also include analyzing the second input to determine third semantic or syntactic data associated with the second input. In response to determining that the third semantic or syntactic data does not substantially match the first semantic or syntactic data, the methods proceed to determining or establishing that the second input is not executable for the third digital request data object based on the second input.

These and other implementations may each optionally include one or more of the following features. The first input associated with the digital request data object is a natural language input. In one embodiment, natural language may comprise a human language (e.g., English language, French language, Portuguese language, Chinese language, Japanese language, Korean language, Dutch language, etc.) that is spoken or written. Furthermore, analyzing the first input by the data engine may comprise: resolving the natural language input into one or more data strings; and applying the first semantic or syntactic data to the one or more data strings to generate the second semantic or syntactic data. In some embodiments, the digital request data object can comprise a file, or a document, or a record, or profile data associated with a user request (e.g., a digital request), or profile data associated with a digital service comprised in or associated with the multi-application network. The file, document, record, or profile data associated with the digital request data object, or profile data associated with a service comprised in, or associated with the multi-application network can outline or be associated with one or more of: account data associated with the digital request data object; or parametric data associated with resolving one or more exception events associated with the digital request data object. In addition, encapsulating the first registration object can comprise: mapping one or more metadata associated with the digital command to the context data to generate one or more registration identifiers; and including or incorporating the one or more registration identifiers in the first registration object.

Moreover, the first computing operation comprises a computing operation for determining an exception event associated with the digital request data object. For example, the exception event can indicate a completion status associated with a processing stage of the digital request data object.

In some implementations, the data engine may encapsulate a second registration object such that the second registration object comprises one or more of: fourth semantic or syntactic data associated with the one or more components of a second command; a digital path to a second application for executing a second computing operation associated with the second command; and context data associated with the second command. The second computing operation, for example, may comprise a computing operation for solving, addressing, or managing a detected exception event associated with the digital request data object.

Moreover, the first registration object may be activated, by the data engine for execution of the first computing operation based on one or more of: context data associated with the first input; device profile data associated with a first computing device through which the first input was received; and user profile data associated with a user providing the first input. Similarly, the first registration object may be deactivated by the data engine for execution of the first computing operation based on one or more of: context data associated with a second input; device profile data associated with a second computing device through which the second input was received; and user profile data associated with a user providing the second input.

According to one embodiment, the context data may control, confirm, or otherwise regulate: the formatting and/or presentation of analysis operation recommendations associated with the digital request data object based on the one or more user inputs; exception event detection operations associated with one or more of the digital request data object; recommendation of stage-wise progression of operations that resolve exception events associated with the digital request data object; and communicate with one or more APIs coupled to one or more native or non-native or third-party applications that execute workflows based on one or more of a user input (e.g., via a digital assistant), a selected analysis operation recommendation, or the context data (e.g., new or updated context data). In some embodiments, the digital assistant can match one or more keywords in a user input to one or more dynamically configured operations associated with a digital request data object to generate the one or more analysis operation recommendations for selection by the user. Furthermore, based on the context data, the digital assistant can suggest other tasks or data types to the user for selection as the case may require. If the digital assistant makes a suggestion that a user is not interested in, the user can provide other input commands (e.g., natural language input commands) clarifying the context data for the digital assistant to generate pertinent outputs for selection by the user. In such cases, the digital assistant (e.g., powered by an artificial intelligence engine) is able to track and assimilate a trajectory of user inputs leading to an eventual recommendation selection by the user and at a later date provide said recommendations for the same or other set of user inputs associated with the same or different digital request data objects.

In addition, the digital path of the first registration object can comprise a script that is executed to activate the first application (e.g., via an API) during accessing the first application. In some embodiments, the digital assistant is configured to receive: the first input; or the second input; or a third input associated with resolving an exception event of the first digital request data object, or the second digital request data object.

Furthermore, a computing operation result may be generated, by the data engine, in response to executing the first computing operation. The computing operation result may comprise a first set of computing operation recommendations including a second computing operation associated with the digital request data object and which is executed by a second application. In addition, the computing operation result may be displayed on a single user interface that is configured to display a plurality of computing operation results generated from analysis operations executed by the first application or the second application. The single user interface may display the plurality of computing operation results instead of a plurality of interfaces associated with the first application or the second application or a plurality of applications associated with the multi-application network.

In one embodiment the first application comprises an application native to the multi-application network while the second application comprises an application that is non-native to the multi-application network and which is accessible via an application programming interface.

DETAILED DESCRIPTION

Illustrated inFIG.1is a high level diagram of an exemplary system100indicting an implementation of a multi-application network. In the illustrated implementation, the system100may include a cloud server105communicatively coupled to a plurality of network systems130a. . .130nvia a network110. The system100may also include an endpoint device125and cloud storage113communicatively coupled via the network110. While a single cloud server105and a single endpoint device125are illustrated, the disclosed principles and techniques could be expanded to include multiple cloud servers, multiple endpoints, and multiple cloud storage devices.

In some embodiments, the cloud server105may include a computing device such as a mainframe server, a content server, a communication server, a laptop computer, a desktop computer, a handheld computing device, a smart phone, a wearable computing device, a tablet computing device, a virtual machine, a mobile computing device, a cloud-based computing solution and/or a cloud-based service, and/or the like. The cloud server105may include a plurality of computing devices configured to communicate with one another and/or implement the techniques described herein.

The cloud server105may include various elements of a computing environment as described in association with the computing environment200ofFIGS.2and3. For example, the cloud server105may include processing unit202, a memory unit204, an input/output (I/O) unit206, and/or a communication unit208which are discussed in association withFIGS.2and3. The cloud server105may further include subunits and/or other modules for performing operations associated with implementing a digital assistant in a multi-application network, registering a digital command in a multi-application network, generating dynamic context data associated with a digital request data object in a multi-application network, curating data associated with a multi-application network, and generating one or more digital records indicating computing operations and state data within a multi-application network. The cloud server may be locally or remotely operated as the case may require.

Turning back toFIG.1, the cloud server105may include a web server115, a data engine140, and a web and agent resources160. The web server115, the data engine140and the web and agent resources160may be coupled to each other and to the network110via one or more signal lines. The one or more signal lines may comprise wired and/or wireless connections.

The web server115may include a secure socket layer (SSL) proxy145for establishing HTTP-based connectivity150between the cloud server105and other devices or systems coupled to the network110. Other forms of secure connection techniques, such as encryption, may be employed on the web server115and across other systems coupled to the network110. Additionally, the web server115may deliver artifacts (e.g., binary code, instructions, data, etc.) to the data engine140either directly via the SSL proxy145and/or via the network110. Additionally, the web and agent resources160of the cloud server105may be provided to the endpoint device125via the web app165on the web server115. The web and agent resources160may be used to render a web-based graphical interface (GUI)170via the browser155running on the endpoint device125.

The data engine140may either be implemented on the cloud server105and/or on the endpoint device125. The data engine140may include one or more instructions or computer logic that are executed by the one or more processors such as processors such as the processors discussed in association withFIGS.2and3. In particular, the data engine facilitates executing the processing procedures, methods, techniques, and workflows provided in this disclosure. Some embodiments include an iterative refinement of one or more data models (e.g., learning model, large language model) associated with the multi-application network disclosed via feedback loops executed by one or more computing device processors and/or through other control devices or mechanisms that make determinations regarding optimization of a given action, template, or model.

In some embodiments, the data engine140may access an operating system180of the endpoint device125in order to execute the disclosed techniques on the endpoint device125. For instance, the data engine140may gain access into the operating system180in order to data processing operations including security operations that scan a security posture of the endpoint device125by scanning a system configuration185, a file system190, and/or system services195of the endpoint device125. The plug-in175of the web browser155may provide needed downloads that facilitate operations executed by the operating system180, the data engine140, and/or other applications running on the endpoint device125.

The network110may include a plurality of networks. For instance, the network110may include any wired and/or wireless communication network that facilitates communication between the cloud server105, the cloud storage113, and the endpoint device125. The network110, in some instances, may include an Ethernet network, a cellular network, a computer network, the Internet, a wireless fidelity (Wi-Fi) network, a light fidelity (Li-Fi) network, a Bluetooth network, a radio frequency identification (RFID) network, a near-field communication (NFC) network, a laser-based network, a 5G network, and/or the like.

The network systems130a. . .130nmay include one or more computing devices or servers, services, or applications the can be accessed by the cloud server105and/or the endpoint device125and or the cloud database113via the network110. In one embodiment, the network systems130a. . .130ncomprises third-party applications or services that are native or non-native to either the cloud server105and/or the endpoint device125. The third-party applications or services, for example, may facilitate executing one or more computing operations associated with resolving an exception event associated with a digital request data object. As further discussed below, the digital request data object may comprise a document or a file outlining one or more of: account data associated with a client request; or parametric data associated with resolving one or more exception events associated with the digital request data object. According to some implementations, the applications or services associated with the network systems130a. . .130nand/or associated with the cloud server105, and/or the endpoint device125must be registered to activate or otherwise enable their usage in the multi-application network. In such cases, the applications and/or services may be encapsulated in a registration object such that the registration object is enabled or activated for use by the data engine140based on one or more of: context data associated with a first user input; device profile data associated with a first interface through which the first user input was received; and user profile data associated with the user providing the first user input. On the flip side, the applications and/or services may be encapsulated in a registration object such that the registration object is deactivated or blocked from usage by data engine140based on one or more of: context data associated with a second user input; context data associated with a second input; device profile data associated with a second interface through which the second input was received; and user profile data associated with a user providing the second input. The first and second user inputs may both be textual or auditory and may comprise a natural language input.

Returning toFIG.1, the cloud storage113may comprise one or more storage devices that store data, information and instructions used by the cloud server105and/or the endpoint device125. The stored information may include information about users, information about data models (e.g., learning model, an artificial intelligence model, etc.), information about a digital assistant associated with the multi-application network, information associated with a digital request data object, information about analysis operations executed by the data engine140, etc. In one embodiment, the one or more storage devices mentioned above in association with the cloud storage113can be non-volatile memory or similar permanent storage device and media. For example, the one or more storage devices may include a hard disk drive, a CD-ROM device, a DVD-ROM device, a DVD-RAM device, a DVD-RW device, a flash memory device, solid state media, or some other mass storage device known in the art for storing information on a more permanent basis. While the cloud storage113is shown as being coupled to the cloud server105and the endpoint device125via the network110, the data in the cloud storage113may be replicated, in some embodiments, on the cloud server105and/or the endpoint device125. That is to say that a local copy of the data in the cloud storage113may be stored on the cloud server105and/or the endpoint device125. This local copy may be synched with the cloud storage113so that when there are any changes to the information in the cloud storage113, the local copy on either the cloud server105or the endpoint device125is also similarly updated or synched in real-time or in near-real-time to be consistent with the information in the cloud storage113and vice versa.

Turning back toFIG.1, the endpoint device125may be a handheld computing device, a smart phone, a tablet, a laptop computer, a desktop computer, a personal digital assistant (PDA), a smart device, a wearable device, a biometric device, a computer server, a virtual server, a virtual machine, a mobile device, and/or a communication server. In some embodiments, the endpoint device125may include a plurality of computing devices configured to communicate with one another and/or implement the techniques described in this disclosure. It is appreciated that according to some implementations, the endpoint device may be used by a user to access a digital assistant associated with the multi-application network for executing a plurality of operations associated with digital request data object. The data engine140may use the assistant to communicate with the user and to execute a plurality of analysis operations as further discussed below.

The local storage103, shown in association with the endpoint device125, may include one or more storage devices that store data, information, and instructions used by the endpoint device125and/or other devices coupled to the network110. The stored information may include various logs/records or event files (e.g., exception event data associated with a digital request data object), security event data, etc. The one or more storage devices discussed above in association with the local database103can be non-volatile memory or similar permanent storage device and media. For example, the one or more storage devices may include a hard disk drive, a floppy disk drive, a CD-ROM device, a DVD-ROM device, a DVD-RAM device, a DVD-RW device, a flash memory device, solid state media, or some other mass storage device known in the art for storing information on a more permanent basis.

The other elements of the endpoint device125are discussed in association with the computing environment200ofFIGS.2and3. For example, elements such as a processing unit202, a memory unit204, an input/output (I/O) unit206, and/or a communication unit208may execute one or more of the modules of endpoint device125and/or one or more elements of the cloud server105shown inFIG.1. The endpoint device125may also include subunits and/or other computing instances as provided in this disclosure for performing operations associated with digital request data object and/or the multi-application network.

FIGS.2and3illustrate exemplary functional and system diagrams of a computing environment200, according to some embodiments of this disclosure, for implementing a digital assistant in a multi-application network, registering a digital command in a multi-application network, generating dynamic context data associated with a digital request data object in a multi-application network, curating data associated with a multi-application network, and generating one or more digital records indicating computing operations and state data within a multi-application network. Specifically,FIG.2provides a functional block diagram of the computing environment200, whereasFIG.3provides a detailed system diagram of the computing environment200.

As seen inFIGS.2and3, the computing environment200may include a processing unit202, a memory unit204, an I/O unit206, and a communication unit208. The processing unit202, the memory unit204, the I/O unit206, and the communication unit208may include one or more subunits for performing operations described in this disclosure. Additionally, each unit and/or subunit may be operatively and/or otherwise communicatively coupled with each other and to the network110. The computing environment200may be implemented on general-purpose hardware and/or specifically-purposed hardware as the case may be. Importantly, the computing environment200and any units and/or subunits ofFIGS.2and/or3may be included in one or more elements of system100as described in association withFIG.1. For example, one or more elements (e.g., units and/or subunits) of the computing environment200may be included in the cloud server105and/or the endpoint device125and/or the network systems130a. . .130n.

The processing unit202may control one or more of the memory unit204, the I/O unit206, and the communication unit208of the computing environment200, as well as any included subunits, elements, components, devices, and/or functions performed by the memory unit204, I/O unit206, and the communication unit208. The described sub-elements of the computing environment200may also be included in similar fashion in any of the other units and/or devices included in the system100ofFIG.1. Additionally, any actions described herein as being performed by a processor may be taken by the processing unit202ofFIGS.2and3alone and/or by the processing unit202in conjunction with one or more additional processors, units, subunits, elements, components, devices, and/or the like. Further, while one processing unit202may be shown inFIGS.2and3, multiple processing units may be present and/or otherwise included in the computing environment200or elsewhere in the overall system (e.g., system100ofFIG.1). Thus, while instructions may be described as being executed by the processing unit202(and/or various subunits of the processing unit202), the instructions may be executed simultaneously, serially, and/or otherwise by one or multiple processing units202on one or more devices.

In some embodiments, the processing unit202may be implemented as one or more computer processing unit (CPU) chips and/or graphical processing unit (GPU) chips and may include a hardware device capable of executing computer instructions. The processing unit202may execute instructions, codes, computer programs, and/or scripts. The instructions, codes, computer programs, and/or scripts may be received from and/or stored in the memory unit204, the I/O unit206, the communication unit208, subunits, and/or elements of the aforementioned units, other devices, and/or computing environments, and/or the like.

In some embodiments, the processing unit202may include, among other elements, subunits such as a content management unit212, a location determination unit214, a graphical processing unit (GPU)216, and a resource allocation unit218. Each of the aforementioned subunits of the processing unit202may be communicatively and/or otherwise operably coupled with each other.

The content management unit212may facilitate generation, modification, analysis, transmission, and/or presentation of content. Content may be file content, exception event content, content associated with a digital request data object, content associated with a registration object (e.g., a registration data object associated with registering a command or an application for use by the digital assistant), media content, security event content, or any combination thereof. In some instances, content on which the content management unit212may operate includes device information, user interface data, image data, text data, themes, audio data or audio files, video data or video files, documents, and/or the like. Additionally, the content management unit212may control the audio-visual environment and/or appearance of application data during execution of various processes (e.g., via web GUI170at the endpoint device125). In some embodiments, the content management unit212may interface with a third-party content server (e.g., third-party content server associated with the network systems130a. . .130n), and/or specific memory locations for execution of its operations.

The location determination unit214may facilitate detection, generation, modification, analysis, transmission, and/or presentation of location information. Location information may include global positioning system (GPS) coordinates, an internet protocol (IP) address, a media access control (MAC) address, geolocation information, a port number, a server number, a proxy name and/or number, device information (e.g., a serial number), an address, a zip code, and/or the like. In some embodiments, the location determination unit214may include various sensors, radar, and/or other specifically-purposed hardware elements for the location determination unit214to acquire, measure, and/or otherwise transform location information.

The GPU216may facilitate generation, modification, analysis, processing, transmission, and/or presentation of content described above, as well as any data described herein. In some embodiments, the GPU216may be utilized to render content for presentation on a computing device (e.g., via web GUI170at the endpoint device125). The GPU216may also include multiple GPUs and therefore may be configured to perform and/or execute multiple processes in parallel.

The resource allocation unit218may facilitate the determination, monitoring, analysis, and/or allocation of computing resources throughout the computing environment200and/or other computing environments. For example, the computing environment may facilitate a high volume of data (e.g., data associated with a digital request data object or a registration object), to be processed and analyzed. As such, computing resources of the computing environment200used by the processing unit202, the memory unit204, the I/O unit206, and/or the communication unit208(and/or any subunit of the aforementioned units) such as processing power, data storage space, network bandwidth, and/or the like may be in high demand at various times during operation. Accordingly, the resource allocation unit218may include sensors and/or other specially-purposed hardware for monitoring performance of each unit and/or subunit of the computing environment200, as well as hardware for responding to the computing resource needs of each unit and/or subunit. In some embodiments, the resource allocation unit218may use computing resources of a second computing environment separate and distinct from the computing environment200to facilitate a desired operation. For example, the resource allocation unit218may determine a number of simultaneous computing processes and/or requests. The resource allocation unit218may also determine that the number of simultaneous computing processes and/or requests meet and/or exceed a predetermined threshold value. Based on this determination, the resource allocation unit218may determine an amount of additional computing resources (e.g., processing power, storage space of a particular non-transitory computer-readable memory medium, network bandwidth, and/or the like) required by the processing unit202, the memory unit204, the I/O unit206, the communication unit208, and/or any subunit of the aforementioned units for safe and efficient operation of the computing environment while supporting the number of simultaneous computing processes and/or requests. The resource allocation unit218may then retrieve, transmit, control, allocate, and/or otherwise distribute determined amount(s) of computing resources to each element (e.g., unit and/or subunit) of the computing environment200and/or another computing environment.

The memory unit204may be used for storing, recalling, receiving, transmitting, and/or accessing various files and/or data during operation of computing environment200. For example, memory unit204may be used for storing, recalling, and/or updating exception event information as well as other data associated with, resulting from, and/or generated by any unit, or combination of units and/or subunits of the computing environment200. In some embodiments, the memory unit204may store instructions, code, and/or data that may be executed by the processing unit202. For instance, the memory unit204may store code that execute operations associated with one or more units and/or one or more subunits of the computing environment200. For example, the memory unit may store code for the processing unit202, the I/O unit206, the communication unit208, and for itself.

Memory unit204may include various types of data storage media such as solid state storage media, hard disk storage media, virtual storage media, and/or the like. Memory unit204may include dedicated hardware elements such as hard drives and/or servers, as well as software elements such as cloud-based storage drives. In some implementations, memory unit204may be a random access memory (RAM) device, a dynamic random access memory (DRAM) device, a static random access memory (SRAM) device, flash memory, read only memory (ROM) device, and/or various forms of secondary storage. The RAM device may be used to store volatile data and/or to store instructions that may be executed by the processing unit202. For example, the instructions stored by the RAM device may be a command, a current operating state of computing environment200, an intended operating state of computing environment200, and/or the like. As a further example, data stored in the RAM device of memory unit204may include instructions related to various methods and/or functionalities described herein. The ROM device may be a non-volatile memory device that may have a smaller memory capacity than the memory capacity of a secondary storage. The ROM device may be used to store instructions and/or data that may be read during execution of computer instructions. In some embodiments, access to both the RAM device and ROM device may be faster to access than the secondary storage.

Secondary storage may comprise one or more disk drives and/or tape drives and may be used for non-volatile storage of data or as an over-flow data storage device if the RAM device is not large enough to hold all working data. Secondary storage may be used to store programs that may be loaded into the RAM device when such programs are selected for execution. In some embodiments, the memory unit204may include one or more databases310(shown inFIG.3) for storing any data described herein. For example, depending on the implementation, the one or more databases may be used as the local record repository103of the endpoint device discussed with reference toFIG.1. Additionally or alternatively, one or more secondary databases (e.g., the public record repository113discussed with reference toFIG.1) located remotely from computing environment200may be used and/or accessed by memory unit204. In some embodiments, memory unit204and/or its subunits may be local to the cloud server105and/or the endpoint device125and/or remotely located in relation to the cloud server105and/or the endpoint device125.

Turning back toFIG.2, the memory unit204may include subunits such as an operating system unit226, an application data unit228, an application programming interface (API) unit230, a content storage unit232, data engine140, and a cache storage unit240. Each of the aforementioned subunits of the memory unit204may be communicatively and/or otherwise operably coupled with each other and other units and/or subunits of the computing environment200. It is also noted that the memory unit204may include other modules, instructions, or code that facilitate the execution of the techniques described. For instance, the memory unit204may include one or more modules such as a data engine discussed in association withFIG.4.

The operating system unit226may facilitate deployment, storage, access, execution, and/or utilization of an operating system utilized by computing environment200and/or any other computing environment described herein. In some embodiments, operating system unit226may include various hardware and/or software elements that serve as a structural framework for processing unit202to execute various operations described herein. Operating system unit226may further store various pieces of information and/or data associated with the operation of the operating system and/or computing environment200as a whole, such as a status of computing resources (e.g., processing power, memory availability, resource utilization, and/or the like), runtime information, modules to direct execution of operations described herein, user permissions, security credentials, and/or the like.

The application data unit228may facilitate deployment, storage, access, execution, and/or utilization of an application used by computing environment200and/or any other computing environment described herein. For example, the endpoint device125may be required to download, install, access, and/or otherwise use a software application (e.g., web application165) to facilitate implementing a digital assistant in a multi-application network, registering a digital command in a multi-application network, generating dynamic context data associated with a digital request data object in a multi-application network, curating data associated with a multi-application network, and generating one or more digital records indicating computing operations and state data within a multi-application network. As such, the application data unit228may store any information and/or data associated with an application. The application data unit228may further store various pieces of information and/or data associated with the operation of an application and/or computing environment200as a whole, such as status of computing resources (e.g., processing power, memory availability, resource utilization, and/or the like), runtime information, user interfaces, modules to direct execution of operations described herein, user permissions, security credentials, and/or the like.

The API unit230may facilitate deployment, storage, access, execution, and/or utilization of information associated with APIs of computing environment200and/or any other computing environment described herein. For example, computing environment200may include one or more APIs for various devices, applications, units, subunits, elements, and/or other computing environments to communicate with each other and/or utilize the same data. Accordingly, API unit230may include API databases containing information that may be accessed and/or utilized by applications, units, subunits, elements, and/or operating systems of other devices and/or computing environments. In some embodiments, each API database may be associated with a customized physical circuit included in memory unit204and/or API unit230. Additionally, each API database may be public and/or private, and so authentication credentials may be required to access information in an API database. In some embodiments, the API unit230may enable the cloud server105and the endpoint device125to communicate with each other. It is appreciated that the API unit230may facilitate accessing, using the data engine140, one or more applications or services on the cloud server105and/or the network systems130a. . .130n.

The content storage unit232may facilitate deployment, storage, access, and/or utilization of information associated with performance of associated with a multi-application network and/or framework processes by computing environment200and/or any other computing environment described herein. In some embodiments, content storage unit232may communicate with content management unit212to receive and/or transmit content files (e.g., media content, digital request data object content, command content, input content, registration object content, etc.).

As previously discussed, the data engine140facilitates executing the processing procedures, methods, techniques, and workflows provided in this disclosure. In particular, the data engine140may be configured to execute computing operations associated with the disclosed methods, systems/apparatuses, and computer program products.

The cache storage unit240may facilitate short-term deployment, storage, access, analysis, and/or utilization of data. In some embodiments, cache storage unit240may serve as a short-term storage location for data so that the data stored in cache storage unit240may be accessed quickly. In some instances, cache storage unit240may include RAM devices and/or other storage media types for quick recall of stored data. Cache storage unit240may include a partitioned portion of storage media included in memory unit204.

The I/O unit206may include hardware and/or software elements for the computing environment200to receive, transmit, and/or present information useful for performing the disclosed processes. For example, elements of the I/O unit206may be used to receive input from a user of the endpoint device125. As described herein, I/O unit206may include subunits such as an I/O device242, an I/O calibration unit244, and/or driver246.

The I/O device242may facilitate the receipt, transmission, processing, presentation, display, input, and/or output of information as a result of executed processes described herein. In some embodiments, the I/O device242may include a plurality of I/O devices. In some embodiments, I/O device242may include a variety of elements that enable a user to interface with computing environment200. For example, I/O device242may include a keyboard, a touchscreen, a button, a sensor, a biometric scanner, a laser, a microphone, a camera, and/or another element for receiving and/or collecting input from a user. Additionally and/or alternatively, I/O device242may include a display, a screen, a sensor, a vibration mechanism, a light emitting diode (LED), a speaker, a radio frequency identification (RFID) scanner, and/or another element for presenting and/or otherwise outputting data to a user. In some embodiments, the I/O device242may communicate with one or more elements of processing unit202and/or memory unit204to execute operations associated with the disclosed techniques and systems.

The I/O calibration unit244may facilitate the calibration of the I/O device242. For example, I/O calibration unit244may detect and/or determine one or more settings of I/O device242, and then adjust and/or modify settings so that the I/O device242may operate more efficiently. In some embodiments, I/O calibration unit244may use a driver246(or multiple drivers) to calibrate I/O device242. For example, the driver246may include software that is to be installed by I/O calibration unit244so that an element of computing environment200(or an element of another computing environment) may recognize and/or integrate with I/O device242for the processes described herein.

The communication unit208may facilitate establishment, maintenance, monitoring, and/or termination of communications between computing environment200and other computing environments, third party server systems, and/or the like (e.g., between the cloud server105and the endpoint device125and or the network systems130a. . .130n). Communication unit208may also facilitate internal communications between various elements (e.g., units and/or subunits) of computing environment200. In some embodiments, communication unit208may include a network protocol unit248, an API gateway250, an encryption engine252, and/or a communication device254. Communication unit208may include hardware and/or other software elements.

The network protocol unit248may facilitate establishment, maintenance, and/or termination of a communication connection for computing environment200by way of a network. For example, the network protocol unit248may detect and/or define a communication protocol required by a particular network and/or network type. Communication protocols used by the network protocol unit248may include Wi-Fi protocols, Li-Fi protocols, cellular data network protocols, Bluetooth® protocols, WiMAX protocols, Ethernet protocols, powerline communication (PLC) protocols, and/or the like. In some embodiments, facilitation of communication for computing environment200may include transforming and/or translating data from being compatible with a first communication protocol to being compatible with a second communication protocol. In some embodiments, the network protocol unit248may determine and/or monitor an amount of data traffic to consequently determine which particular network protocol is to be used for establishing a secure communication connection, transmitting data, and/or performing malware scanning operations and/or other processes described herein.

The API gateway250may allow other devices and/or computing environments to access the API unit230of the memory unit204associated with the computing environment200. For example, an endpoint device125may access the API unit230of the computing environment200via the API gateway250. In some embodiments, the API gateway250may be required to validate user credentials associated with a user of the endpoint device125prior to providing access to the API unit230to a user. The API gateway250may include instructions for the computing environment200to communicate with another computing device and/or between elements of the computing environment200.

EXEMPLARY EMBODIMENTS

Processing or analyzing data in a multi-application network may involve the use of a plurality of technologies or applications associated one or more domains, sectors, processing stages, and/or workflow stages or sub-stages associated with a digital request data object. According to one embodiment, the digital request data object comprises a file, or a document, or a record, or profile data associated with a user request, or profile data associated with a digital service comprised in or associated with the multi-application network. It is appreciated that the file, the document, record, profile data associated with a user request, or profile data associated with a service comprised in, or associated with the multi-application network outlines or is associated with one or more of: account data associated with the digital request data object; or parametric data associated with resolving one or more exception events associated with the digital request data object. According to one embodiment, the multi-application network may: connect a plurality of users via one or more computer networks such as those discussed above in association withFIGS.1,2, and3; include computational capabilities that improve user experience; include one or more analysis operations comprising workflows/logic associated with one or more applications; and include a machine learning or an artificial intelligence engine or module drives context identification associated with a digital request data object and allows further customized interrogation of the multi-application network based on identified context. In some embodiments, the disclosed multi-application network is scalable, and can condense multiple user interfaces into a single user interface based on the digital context associated with a given digital request data object to allow optimized and otherwise seamless generation of analysis data or computing results associated with the processing stages associated with the digital request data object. Moreover, the analysis data, computing results, or context or intent data associated with the digital request data object may be displayed on a single interface thereby negating the laborious process of a user navigating between a plurality of applications and/or interfaces associated with a plurality of applications generating the analysis data, computing results, or context data. This may be achieved by the user interacting with a digital assistant of the multi-application network such that the digital assistant automatically evaluates user inputs (e.g., textual or audio natural language inputs) and intelligently engages applications associated with the multi-application network to execute the needed process for the various processing stages associated with resolving one or more exception events associated with the digital request data object. For example, the digital assistant may comprise or be associated with an artificial or machine learning engine which adapts to, or intelligently uses the user inputs by leveraging context data associated with one or more of: a user profile; the user inputs; one or more digital request data objects; or an exception event associated with the one or more digital request data objects.

The exception event, for example, may comprise a disruption in processing a digital request data object at a particular processing stage based on the digital request data object's failure to meet certain requirements or criteria at said stage. For example, some of the requirements may include: a lack of additional input from a user associated with the digital request data object; profile data of the user associated with the digital request data object; a lack of analysis data or computing results data from other applications associated with the multi-application network; a time threshold required to process the digital request data object; profile data associated with a device on which the digital request data object is being processed; credential data associated with a user of the multi-application network; lack of context data associated with the digital request data object; lack of client profile data associated with a client corresponding to the digital request data object.

According to one embodiment, the multi-application network provides users with a functionality to operate on one or more requests (e.g., digital requests data objects) regardless of status (e.g., exception event status) of said requests in a user-friendly and context-enabled machine learning user interface. The multi-application network can provide a user with relevant data based on a digital context within which the user is interacting or communicating with the digital assistant of the multi-application network. In one embodiment, the multi-application network can generate a context-specific interface based on the type of inquiry or operations associated with inputs being received so that a user does not need to actively navigate to multiple user interfaces or access relevant data processing applications that interpret or otherwise analyze data at a given processing stage of a digital request data object. In some embodiments, an application programming interface (API) such as those discussed in conjunction withFIGS.2and3facilitates the selection of relevant programs or digital logic for processing data associated with the digital request data object based on the digital context.

According to some embodiments, the multi-application network enables automating exception event detection associated with one or more digital request data objects with little to no user intervention using APIs that access and process stage-specific or domain-specific applications associated with the digital request data object. Results from such processes may be presented together with one or more recommendations on possible operations or workflows to execute to resolve and or track an identified exception on a single graphical user interface associated with the multi-application network. According to one embodiment, an identified exception of the digital request data object indicates a digital event, a digital disruption, a data anomaly, or data condition that needs to be resolved or satisfied for a stage-wise progression of the digital request data object, for example, to move the digital request data object to a different processing stage associated with the digital request data object. In one embodiment, the multi-application network can improve efficiency of operations, computing or otherwise, within the multi-application network by decreasing:1) the cognitive load for teams (e.g., Agile team) using the multi-application network,2) back-office (full-time equivalent FTE) operations associated with the multi-application network by at least 25%, and3) user training time associated with the multi-application network by at least half of the time required to train users without the multi-application network.
Furthermore, the multi-application network can increase cross-domain data fungibility or cross-specialty data fungibility or cross-stage data fungibility associated with the digital request data object.

The disclosed technology beneficially provides a broad set of functionalities by developing, delivering, and releasing distributed and stand-alone solutions for inter-domain, inter-stage data management through the use of a single multi-application network. Furthermore, the disclosed methods and systems provide a conversational architecture to facilitate interactions between a user and the multi-application network using a digital assistant. In particular, the multi-application network can receive natural language queries/inputs associated with a digital request data object from a user, analyze said natural language queries and provide workflow recommendations as well as other responses associated said natural language queries. In some embodiments, the multi-application network can generate intent/context data indicating a digital context associated with the natural language queries and/or associated with a given digital request data object to generate one or more workflow recommendations and/or link a user query/input to one or more digital request data objects and/or applications. It is appreciated that the multi-application network can maintain a digital context associated with a given digital request data object based on one or more of a digital request of a client, a user input from a user, or a digital request data object associated with the user input. According to some embodiment, the multi-application network can curate data based on a profile of a user (e.g., a digital profile of a user), a digital profile of the digital request data object, a digital profile of a computing device being used by the user, location data of a user, and other security protocols associated with the user and/or the digital request data object. It is appreciated that the multi-application network may facilitate implementing a digital assistant, executing registration operations for digital commands, executing context awareness operations, executing operations associated with curating data, and executing operations associated with generating analysis reports or receipts responsive to executing one or more computing operations associated with a digital request data object and/or registration object associated with registering a command.

Digital Command Registration

Within the multi-application network, one or more commands (e.g., digital commands or computing commands) can be registered within a database of the multi-application network to facilitate computing operations associated with a plurality of digital request data objects. According to one embodiment, the one or more commands have an associated registration object that comprises: an encapsulation of semantic and/syntactic data associated with the one or more commands; and/or command definitions associated with the one or more commands; and/or path data to one or more applications associated with the one or more commands; and/or context data associated with the one or more commands; and/or API data that connects to one or more applications that execute the one or more commands. According to one embodiment, the registration object may have an associated set of suggested or contextual set of actions or computing operations together with one or more keywords or key terms or key phrases associated with the one or more commands. It is appreciated that the operations required to register a command comprise a micro-service (e.g., computing service) that facilitates scalability of delivering the commands across multiple development teams and organizations. The commands to be registered together with related web components can be registered and subsequently displayed using a digital assistant of the multi-application network such as the digital assistant discussed above.

Furthermore, a data manager (e.g., stored in a memory device of the multi-application network) can enable the various operations associated with registering a digital command and also coordinate the various operations of the digital assistant. Once registered, a given command can use one or more of syntactic and/or semantic aspects of a command or input from a user together with contextual data associated with said input and/or associated with a digital request data object to retrieve or otherwise generate a set of computing operations that are recommended to a user for selection. In one embodiment, the commands to be registered may be developed (e.g., modularly developed) and independently introduced into the multi-application network for execution. Furthermore, the commands may be linked or otherwise be tied to one or more application that are native (e.g., comprised in the multi-application network) or non-native (external to the multi-application network) to the multi-application network via one or more application programming interfaces. For example, a non-native application associated with a given command may have a registration object that enables the linking of the command to at least one application that executes a computing operation associated with the command. In some cases, the command associated with the registration object may be linked (e.g., using a digital path comprised in the registration object) to an application using for example, a JavaScript associated with the registration object that is configured within a customized client-specific, or a user-specific, or a group-specific, or an institution-specific digital platform such as the Apigee system that handles resources such as API's associated with the multi-application network.

FIGS.4A and4Bshow exemplary flowcharts for methods, systems/apparatuses, and computer program products that implement the registering of a command in a multi-application network such as the multi-application network ofFIG.1. It is appreciated that a data engine stored in a memory device (e.g., memory unit204ofFIGS.2and3) may cause a computer processor to execute the various processing stages ofFIGS.4Aand,4B.

At block402, the data engine may determine a first computing operation for the multi-application network. The first computing operation, according to one embodiment, may be associated with a digital request data object. For example, the first computing operation may comprise: a status check of the digital request data object; a review of at least one exception event associated with the digital request data object; quantitative and/or qualitative analysis of the digital request data object; etc. The data engine may, at block404, receive a first command for the first computing operation associated with the digital request data object. At block406, the data engine may further encapsulate in a first registration object, one or more of: first semantic or syntactic data associated with one or more components of the first command for the first computing operation associated with the first digital request data object; a digital path to a first application for executing the first computing operation associated with the first digital request data object; and context data associated with the first command for the first computing operation associated with the first digital request data object. The data engine may then store in a database associated with the multi-application network, at block408, the first registration object. In addition, the data engine may receive using a digital assistant of the multi-application network, at block410, a first input associated with the digital request data object. The first input may comprise textual data and/or auditory or vocal data received using an input device. In one embodiment, the textual and/or auditory data may comprise natural language inputs with associated syntactic and semantic data (e.g., semantic and/or syntactic parameters) characterizing the first input. According to some embodiments, the semantic and/or syntactic data include a logical flow of one or more words comprised in the first input. Furthermore, the semantic and/or syntactic data may include data associated with an arrangement or organization of one or more words or text comprised in the first input.

Turning back toFIG.4A, the data engine may analyze, at block412, the first input to determine second semantic or syntactic data associated with the first input. The data engine may, at block414, determine, that the second semantic or syntactic data substantially matches the first semantic or syntactic data. In response to determining that the second semantic or syntactic data substantially matches the first semantic or syntactic data, the data engine may identify at block416, the first command associated with the first computing operation. Moreover, the data engine may further access, at block418, based on the first command, the first registration object. According to one embodiment, the data engine may determine, at block420, the digital path comprised in the first registration object. The data engine may also access, at block422, based on the digital path (e.g., digital path associated with an API) comprised in the first registration object, a first application for the first computing operation. According to one embodiment, the data engine may execute, at block424, the first computing operation, using the first application, for the second digital request data object. Furthermore, the data engine may receive, at block426, a second input associated with a third digital request data object. At block428, the data engine may analyze the second input to determine third semantic or syntactic data associated with the second input. The data engine may also determine, at block430, if the third semantic or syntactic data does not substantially match the first semantic or syntactic data. In response to determining the second semantic or syntactic data does not substantially match the first semantic or syntactic data, the data engine may determine, at block432: the second input is not executable for the third digital request data object based on the second input; or a command associated with the second input is not executable for the third digital request data object based on the second input; or a command associated with the first registration object is not executable for the third digital request data object based on the second input.

These and other implementations may each optionally include one or more of the following features. The first input associated with the first digital request data object is a natural language input. In one embodiment, natural language may comprise a human language (e.g., English language, French language, Portuguese language, Chinese language, Japanese language, Korean language, Dutch language, etc.) that is spoken or written. Furthermore, analyzing the first input by the data engine may comprise: resolving the natural language input into one or more data strings; and applying the first semantic or syntactic data to the one or more data strings to generate the second semantic or syntactic data. According to some embodiments, the first digital request data object or the second digital request data object, or the third digital request data object comprises a document or a file outlining one or more of: account data associated with a client request; or data indicating a stage-wise progression of analysis operations required to resolve an exception event associated with the digital request data object. In particular, the first digital request data object, or the second digital request data object, or the third digital request data object can comprise: a file; or a document; or a record; or profile data associated with a user request (e.g., a digital request data object); or profile data associated with a digital service comprised in or associated with the multi-application network. The file, document, record, or profile data associated with the first digital request data object, or the second digital request data object, or the third digital request data object, or profile data associated with a service comprised in, or associated with the multi-application network can outline or be associated with one or more of: account data associated with the digital request data object; or parametric data associated with resolving one or more exception events associated with the digital request data object; or data indicating a stage-wise progression of analysis operations required to resolve an exception event associated with the first digital request data object, or the second digital request data object, or third digital request data object. In addition, encapsulating the first registration object or a second registration object can comprise: mapping one or more metadata associated with the first command to the context data to generate one or more registration identifiers; and including the one or more registration identifiers in the first registration object or the second registration object.

Moreover, the first computing operation comprises a computing operation for determining an exception event associated with the first digital request data object. For example, the exception event can indicate a completion status associated with a processing stage of the first digital request data object.

In some implementations, the data engine may encapsulate a second registration object such that the second registration object comprises one or more of: fourth semantic or syntactic data associated with the one or more components of a second command; a digital path to a second application for executing a second computing operation associated with the second command; and context data associated with the second command. The second computing operation, for example, may comprise a computing operation for solving, addressing, or managing a detected exception event associated with the digital request data object.

Moreover, the first registration object may be activated, by the data engine for execution of the first computing operation based on one or more of: context data associated with the first input; device profile data associated with a first computing device through which the first input was received; and user profile data associated with a user providing the first input. Similarly, the first registration object may be deactivated by the data engine for execution of the first computing operation based on one or more of: context data associated with the second input; device profile data associated with a second computing device through which the second input was received; and user profile data associated with a user providing the second input.

According to one embodiment, the context data may control, confirm, or otherwise regulate: the formatting and/or presentation of analysis operation recommendations associated with the digital request data object based on one or more user inputs; exception event detection operations associated with one or more of the digital request data object; recommendation of stage-wise progression of operations that resolve exception events associated with the digital request data object; and communicate with one or more APIs coupled to one or more native or non-native or third-party applications that execute workflows based on one or more of a user input, a selected analysis operation recommendation, or the context data (e.g., new or updated context data).

In some embodiments, a digital assistant associated with the multi-application network may be configured to receive the first input, the second input, or a third input associated with resolving an exception event of the first digital request data object, or the second digital request data object. The digital assistant can match one or more keywords in a user input to one or more dynamically configured operations associated with a digital request data object to generate one or more analysis operation recommendations for selection by the user. Furthermore, based on the context data, the digital assistant can suggest other tasks or data types to the user for selection as the case may require. If the digital assistant makes a suggestion that a user is not interested in, the user can provide other input commands (e.g., natural language input commands) clarifying the context data for the digital assistant to generate pertinent outputs for selection by the user. In such cases, the digital assistant (e.g., powered by an artificial intelligence engine) is able to track and assimilate a trajectory of user inputs leading to an eventual recommendation selection by the user and at a later date provide said recommendations for the same or other set of user inputs associated with the same or different digital request data objects. In addition, the digital path of the first registration object can comprise a script that is executed to activate, via an API, the first application during accessing the first application.

Furthermore, a computing operation result may be generated, by the data engine, in response to executing the first computing operation. The computing operation result may comprise a first set of computing operation recommendations including a second computing operation associated with the digital request data object and which is executed by a second application. In addition, the computing operation result may be displayed on a single user interface that is configured to display a plurality of computing operation results generated from analysis operations executed by the first application or the second application. The single user interface may display the plurality of computing operation results instead of a plurality of interfaces associated with the first application or the second application or a plurality of applications associated with the multi-application network. In one embodiment the first application comprises an application native to the multi-application network while the second application comprises an application that is non-native to the multi-application network and which is accessible via an application programming interface.

It is appreciated that the digital request data object may comprise a file or document indicating a loan request, a request to process medical registration data, a request to process student data associated with an educational institution, a request to process scientific data associated with a research, etc.

According to one embodiment, a second digital command, a third digital command, or a fourth digital command may be registered using the process outlined inFIGS.4A and4B. Furthermore, the context data discussed in association withFIGS.4A and4Bmay comprise one or more of: profile data comprising user data associated with the digital request data object, trajectory data associated with one or more computing operations previously executed on the digital request data object, and metadata associated with the digital request data object. In such cases, the user data may comprise: user-specific data associated with a specific user; or group-specific data associated with a plurality of users belonging to a specific group. In one embodiment, access protocols comprised in the user data may drive the activation or deactivation of one or more registered commands or registration objects based on one or more inputs associated with a specific user or from a specific group of users.

This patent application incorporates by reference the following commonly owned applications, naming the same inventors, and filed on the same date as the present application (note that the list includes the present application): (1) U.S. patent application Ser. No. 18/373,771, titled “Methods And Systems For Implementing An Intelligent Digital Assistant In A Multi-Application Network,” filed on Sep. 27, 2023; (2) U.S. patent application Ser. No. 18/373,797, titled “Methods And Systems For Registering A Digital Command In A Multi-Application Network,” filed on Sep. 27, 2023; (3) U.S. patent application Ser. No. 18/373,813, titled “Methods And Systems For Generating Dynamic Context Data Associated With A Digital Request Data Object In A Multi-Application Network,” filed on Sep. 27, 2023; (4) U.S. patent application Ser. No. 18/373,822, titled “Methods And Systems For Curating Data In A Multi-Application Network,” filed on Sep. 27, 2023; and (5) U.S. patent application Ser. No. 18/373,830, titled “Methods And Systems For Generating Digital Records Indicating Computing Operations And State Data In A Multi-Application Network,” filed on Sep. 27, 2023.

The foregoing description, for purpose of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. The embodiments were chosen and described in order to explain the principles of the disclosed subject-matter and its practical applications, to thereby enable others skilled in the art to use the technology disclosed and various embodiments with various modifications as are suited to the particular use contemplated. It is appreciated that the term optimize/optimal and its variants (e.g., efficient or optimally) may simply indicate improving, rather than the ultimate form of ‘perfection’ or the like.

Furthermore, the functions or operations described above can be implemented in digital electronic circuitry, in computer software, firmware or hardware. In particular, the disclosed techniques can be implemented using one or more computer program products. The computer program products, in some embodiments, comprises non-transitory computer-readable media comprising code configured to execute the disclosed approach. Programmable processors and computers can be included in or packaged as mobile devices according to some embodiments. The processes and logic flows can be performed by one or more programmable processors and by one or more programmable logic circuitry. General and special purpose computing devices and storage devices can be interconnected through communication networks.

As used herein, the term “if” may be construed to mean “when” or “upon” or “in response to determining” or “in response to detecting,” depending on the context.

Those with skill in the art will appreciate that while some terms in this disclosure may refer to absolutes, e.g., all source receiver traces, each of a plurality of objects, etc., the methods and techniques disclosed herein may also be performed on fewer than all of a given thing, e.g., performed on one or more components and/or performed on one or more source receiver traces. Accordingly, in instances in the disclosure where an absolute is used, the disclosure may also be interpreted to be referring to a subset.