Method, system, and storage medium for implementing an extended open digital architecture for support systems - Patents.com

Abstract

An architecture, and a method and system for implementing the same, is disclosed. A system for implementing a Business Support System (BSS) architecture includes a memory and a processor that executes instructions to implement the architecture, the architecture including multiple layers and a real-time event stream that transfers data between components of the layers, the layers including an engagement and core commerce management layer for providing multiple user interfaces corresponding to multiple use cases, an event-based automation and user data platform layer including real-time customer data and multiple automation workflows for executing the multiple use cases based on the real-time customer data, a core BSS component layer, an intelligent management layer for managing insights, model development, and batch model execution, and a cloud infrastructure management layer configured to provide cloud capabilities for a Software as a Solution (SaaS) implementation of the BSS architecture.

Description

[Technical Field]

[0001] Apparatus and methods consistent with exemplary embodiments of the present disclosure relate to an enhanced Open Digital Architecture (ODA) for support systems, such as Business Support Systems (BSS). [Background technology]

[0002] Related art BSS ODA architectures (e.g., for carrier systems) are typically configured as multi-tier architectures based on engagement management, subscriber management, core commerce management, core production platform, and intelligent management, all of which are integrated via application programming interfaces (APIs). Figure 1 shows an example of this related art architecture 100, including an engagement management layer 101, a subscriber management sublayer 103, a core commerce sublayer 104, a core production sublayer 105, and an intelligent management layer 106. In related art architectures, integration of APIs 102 is required across the aforementioned components to provide inter-component communication and integration.

[0003] However, this related art architecture does not include real-time customer data capabilities and / or event streams or real-time data streams (e.g., Kafka data streams). The addition / inclusion of microservices and a cloud tech stack does not address these issues, at least without further modifying the underlying architecture. Microservices alone do not offer greater flexibility, better time to market, reduced customization costs, and reduced overall solution costs compared to related art architectures.

[0004] Currently, custom use cases are developed and deployed (i.e., hard-coded) as core production components of the BSS solution, which poses a major challenge when deploying a BSS solution in a software-as-a-service (SaaS)-based subscription model, which requires a significant upfront investment for any operator.

[0005] Embodiments of the present disclosure address these issues and can provide greater flexibility, better time to market, reduced customization costs, and reduced overall solution costs compared to current state-of-the-art architectures, including implementations on microservices and cloud tech stacks. Summary of the Invention

[0006] According to one aspect of the present disclosure, there is provided a system for implementing a business support system (BSS) architecture, the system comprising: at least one memory that stores instructions; and at least one processor configured to execute the instructions to implement the BSS architecture. The BSS architecture comprises a plurality of layers and a real-time event stream for transferring real-time event streams of data between components of the plurality of layers, the plurality of layers comprising: an engagement and core commerce management layer for providing a plurality of user interfaces corresponding to a plurality of use cases of the BSS architecture, an event-based automation and user data platform layer including real-time customer data and a plurality of automated workflows for executing the plurality of use cases based on the real-time customer data, a core BSS component layer including core BSS components, an intelligent management layer for managing insights, model development, and batch model execution, and a cloud infrastructure management layer configured to provide cloud capabilities for a Software as a Solution (SaaS) implementation of the BSS architecture.

[0007] In one aspect of the present disclosure, the BSS architecture may further comprise an open application programming interface (API) for real-time information provisioning of data between components.

[0008] In one aspect of the present disclosure, the real-time event stream may be a Kafka event stream.

[0009] In one aspect of the present disclosure, the BSS architecture may further comprise a management component used across multiple layers.

[0010] In one aspect of the present disclosure, multiple user interfaces may be each configurable by the customer of the SaaS implementation without hard coding.

[0011] In one aspect of the present disclosure, the BSS components may be productized in a SaaS implementation.

[0012] In one aspect of the present disclosure, components of multiple layers may be executable as microservices by at least one processor.

[0013] According to another aspect of the present disclosure, there is provided a method that includes receiving, within a first computer architecture layer, a first user request; determining, in real time, via a second computer architecture layer, a category of the first user request; providing, via the second computer architecture layer, an automated workflow and customer data platform for data entry and manipulation by a user based on the category of the first user request, wherein the user may make a second request; generating, via a third computer architecture layer, a productization model based on the second user request; and intelligently managing the productization model via a fourth computer architecture layer.

[0014] In one aspect of the present disclosure, the method may be performed on a cloud computing platform.

[0015] In one aspect of the present disclosure, the first computer architecture layer may be a core commerce and customer engagement layer.

[0016] In one aspect of the present disclosure, the first through fourth computer architecture layers may be integrated via an application programming interface.

[0017] In one aspect of the present disclosure, internal reporting for the first through fourth architecture layers may be centralized.

[0018] In one aspect of the present disclosure, internal reporting may be centralized in a fourth computer architecture layer.

[0019] In one aspect of the present disclosure, management of the productization model through the fourth computer architecture layer may be centralized.

[0020] Another aspect of the present disclosure relates to a system including one or more hardware processors configured with machine-readable instructions, wherein the one or more processors may be configured to: receive a first user request in a first computer architecture layer; determine, in real time, a category of the first user request via a second computer architecture layer; provide, based on the category of the first user request, via the second computer architecture layer, an automated workflow and customer data platform for data entry and manipulation by a user, where the user may make a second request; generate, based on the second user request via a third computer architecture layer, a productization model; and intelligently manage the productization model via a fourth computer architecture layer.

[0021] Yet another aspect of the present disclosure relates to a non-transitory computer-readable storage medium having instructions embodied thereon, the instructions being executable by one or more processors to perform a method, the method including receiving, within a first computer architecture layer, a first user request; determining, in real time, via a second computer architecture layer, a category of the first user request; providing, via the second computer architecture layer, an automated workflow and customer data platform for data entry and manipulation by a user based on the category of the first user request, wherein the user may make a second request; generating, via a third computer architecture layer, a productization model based on the second user request; and intelligently managing the productization model via a fourth computer architecture layer.

[0022] These and other features and characteristics of the present technology, as well as the method of operation and function of the associated elements of construction, and economies of combination of parts and manufacture, will become more apparent from a consideration of the following description and appended claims, taken in conjunction with the accompanying drawings, all of which form a part hereof, and in which like reference numerals indicate corresponding parts in the various views. It is to be expressly understood, however, that the drawings are for the purpose of illustration and description only and are not intended as a definition of the limits of the invention. As used in this specification and claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. [Brief explanation of the drawings]

[0023] The features, advantages, and significance of exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which like reference numerals refer to like elements.

[0024] [Figure 1] FIG. 1 is a diagram illustrating an open digital architecture (ODA) for a business support system (BSS) of the related art.

[0025] [Figure 2] FIG. 1 illustrates an open digital architecture (ODA) according to one or more implementations.

[0026] [Figure 3] FIG. 1 illustrates an open digital architecture (ODA) according to one or more implementations.

[0027] [Figure 4] FIG. 1 illustrates a method according to one or more implementations.

[0028] [Figure 5] FIG. 1 illustrates a system configured as an extended open digital architecture (ODA) for support systems, according to one or more implementations.

[0029] [Figure 6] FIG. 1 illustrates a method according to one or more implementations.

[0030] [Figure 7] FIG. 1 is a diagram of an exemplary environment in which the systems and / or methods described herein may be implemented, according to an embodiment.

[0031] [Figure 8] FIG. 8 is a diagram of exemplary components of one or more devices of FIG. 7 according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0032] The following detailed description refers to the accompanying drawings, in which the same reference numbers in different drawings may identify the same or similar elements.

[0033] The foregoing disclosure provides illustration and description, but is not intended to be exhaustive or to limit implementations to the precise form disclosed. Modifications and variations are possible in light of the above disclosure or may be acquired from practicing implementations. Furthermore, one or more features or components of one embodiment may be incorporated into or combined with another embodiment (or one or more features of another embodiment). Additionally, in the flowcharts and descriptions of operations provided below, it is understood that one or more operations may be omitted, one or more operations may be added, one or more operations may be performed (at least partially) concurrently, and the order of one or more operations may be permuted.

[0034] It will be apparent that the systems and / or methods described herein may be implemented in various forms of hardware, firmware, or combinations of hardware and software. The actual specialized control hardware or software code used to implement these systems and / or methods is not limiting of the implementation. Accordingly, the operation and behavior of the systems and / or methods are described herein without reference to specific software code. It will be understood that software and hardware can be designed to implement the systems and / or methods based on the description herein.

[0035] Although particular combinations of features are recited in the claims and / or disclosed herein, these combinations are not intended to limit the disclosure of possible implementations. Indeed, many of these features may be combined in ways not specifically recited in the claims and / or disclosed herein. Although each dependent claim listed below may depend directly on only one claim, the disclosure of possible implementations includes each dependent claim in combination with all other claims in the claim set.

[0036] No element, act, or instruction used herein should be construed as critical or required unless explicitly described as such. Also, as used herein, the articles "a" and "an" are intended to include one or more items and may be used interchangeably with "one or more." Where only one item is intended, the term "one" or similar phrases are used. Also, as used herein, terms such as "has," "have," "having," "include," and "including" are intended to be open-ended terms. Furthermore, the phrase "based on" is intended to mean "based at least in part on," unless specifically stated otherwise. Furthermore, phrases such as "at least one of [A] and [B]" or "at least one of [A] or [B]" should be understood to include A only, B only, or both A and B.

[0037] Embodiments of the present disclosure provide a multi-tiered Business Support System (BSS) architecture with a solution-oriented approach that gives operators (e.g., carriers) access to a more flexible ecosystem. In addition, embodiments enable a simplified Software as a Service (SaaS) approach for BSS vendors.

[0038] Aspects of the present disclosure provide a BSS architecture in which core commerce and customer engagement platforms are merged into a single layer. Such a merger enables simplified sales (e.g., agent sales and self-selling) and care processes, as well as increased processing efficiency.

[0039] Aspects of the present disclosure provide a BSS architecture that includes an event streaming layer (e.g., a Kafka layer) to complement the API layer. In addition to improving processing efficiency, this introduction reduces over-dependence on APIs for data transfer between components. According to aspects of the present disclosure, most data transfer is performed through this layer to avoid the complexities of API data transfer while providing more efficient traffic throughput. Additionally, with the introduction of the event streaming layer, reports (e.g., usage reports, performance reports, subscriber profile reports, bill payment reports, etc.) can be centralized in the data intelligence layer, and individual reports at each component may not be required (although they may be permitted).

[0040] Aspects of the present disclosure provide a BSS architecture that includes a workflow automation layer. In addition to improving processing efficiency, this introduction of a workflow automation layer allows for a reduction in the need for changes to the core solution. Custom use cases can be easily and flexibly deployed in this layer through upgrades, modifications, versioning, etc., without requiring hard coding or changes to the source code.

[0041] Aspects of the present disclosure provide a new layer in the BSS architecture (i.e., a workflow automation layer) for custom configuration across all BSS products, useful for SaaS-based solutions. Core BSS components can be tightly productized as SaaS offerings.

[0042] According to aspects of the present disclosure, management components such as log management may be centralized, which may apply to some or all of the management components.

[0043] 2, each of the different architecture layers 201-205 may be configured as an event stream layer via multiple event streams 206 and may be connected via open APIs 207. Additionally, the different architecture layers may include management components 208 including digital workflow 209, security platform 210, third-party API gateway 211, log management 212, document management 213, and service assurance 214, each of which is required to provide the operational capabilities of the disclosed architecture. For example, digital workflow 209 is configured to provide business workflow (e.g., Business Process Model and Notation (BPMN), etc.), security platform 210 is configured to provide security-related credentials, third-party API gateway 211 is configured to provide external component integration, log management 212 is configured to provide a log of activity within the architecture, document management 213 is configured to manage (e.g., store, retrieve, etc.) documents (e.g., reports, contracts, etc.), and service assurance 214 is configured to guarantee service quality (e.g., monitor system operation to ensure service quality, etc.).

[0044] In some embodiments, the event stream 206 is a Kafka event stream. Kafka is a distributed event store and stream processing platform. It is an open-source system that provides a unified, high-throughput, low-latency platform for handling real-time data feeds. Kafka can connect to external systems (for data import / export) through Kafka Connect and provides the Kafka Stream library for stream processing applications. Kafka uses a binary TCP-based protocol optimized for efficiency and relies on a "message set" abstraction that naturally groups messages together to reduce network round-trip overhead. While Kafka may be used in some embodiments, other real-time data streams may also be used, and these streams may be open source. The use of real-time data streams and microservices gives rise to a newly reimagined open-source platform.

[0045] In some implementations, the method may be performed on a cloud computing platform. In some implementations, the first through fourth computer architecture layers 201-204 (and optionally the fifth computer architecture layer 205) may be integrated via an application programming interface, e.g., 207. In some implementations, internal reporting for the first through fourth architecture layers 201-204 (and optionally the fifth computer architecture layer 205) may be centralized. In some implementations, the method may be performed on an event streaming layer, e.g., computer architecture layer 206.

[0046] FIG. 3 illustrates another embodiment of a BSS ODA architecture. The architecture of FIG. 3 includes a customer (user) engagement layer 301, an event-based and real-time decision engine layer 302, a core BSS component layer 303, an insights and batch analytics layer 304, and an infrastructure management and operations platform layer 305. Similar to the embodiment shown in FIG. 2, each of the different layers in FIG. 3 can be configured as a real-time event stream layer (e.g., a Kafka event stream layer, etc.) via event stream 306 (e.g., a Kafka event stream, etc.) and can be connected via open APIs 307. Additionally, the different architecture layers can include management components 308, including digital workflow 309, security platform 310, third-party API gateway 311, log management 312, document management 313, and service assurance 314, as described in connection with FIG. 2.

[0047] 3, customer engagement layer 301 (i.e., a layer that manages customer (e.g., internal customers such as sales team, service team, management team, etc., or external customers such as paying customers) interactions and engagements with the system) may include advertising platform 301-1, e-commerce platform 301-2, mobile application platform 301-3, e-care self-service platform 301-4, kiosk and display advertising platform 301-5, and media platform 301-6. Event-based and real-time decision engine layer 302 (i.e., a layer that makes event-based decisions) may include automated workflow platform 302-1, real-time customer data platform 302-2, prescriptive analytics platform 302-3, and predictive analytics platform 302-4. The core BSS component layer 303 (i.e., the layer including the core BSS components) may include a product catalog 303-1, a customer platform 303-2, a COM 303-2, a SOM 303-3, an Electronic Know-Your-Customer (eKYC) platform 303-4, a customer management platform 303-5, a voucher and coupon platform 303-6, an inventory management platform 303-7, a quote manager sales portal 303-8, a price rating and billing platform 303-9, a campaign and lead management platform 303-10, a membership loyalty platform 303-11, a gaming platform 303-13, a fraud management platform 303-14, a business-to-business (B2B) account management platform 303-15, a payment platform 303-16, and an intermediation platform 303-17. The insight and batch analytics layer 304 (i.e., the layer that processes and manages data) may include a data lake 304-1, a reporting visualization platform 304-2, an artificial intelligence (AI) platform 304-3, AI assets 304-4, and a descriptive analytics platform 304-5.Additionally, the infrastructure management and operations platform layer 305 (i.e., the layer that manages and controls the required infrastructure, such as provisioning the databases that host the required cloud infrastructure) may include a cloud infrastructure and network platform 305-1 and a cloud orchestration platform 305-2.

[0048] 4 illustrates a method 400 according to one or more implementations. The operations of method 400 presented below are intended to be exemplary. In some implementations, method 400 may be achieved with one or more additional operations not described and / or without one or more of the operations described. Additionally, the order in which the operations of method 400 are shown in FIG. 4 and described below is not intended to be limiting.

[0049] In some implementations, method 400 may be implemented in one or more processing devices (e.g., digital processors, analog processors, digital circuits designed to process information, analog circuits designed to process information, state machines, and / or other mechanisms for electronically processing information). The one or more processing devices may include one or more devices that perform some or all of the operations of method 400 in response to instructions electronically stored on an electronic storage medium. The one or more processing devices may include one or more devices configured via hardware, firmware, and / or software that would be specifically designed to perform one or more of the operations of method 400.

[0050] Act 401 may include implementing a business support system (BSS) architecture, and act 402 may include transferring data between components of multiple layers via real-time event streams. The BSS architecture may correspond to the architecture described above with reference to Figures 2 and 3.

[0051] The above-described architecture, according to one or more embodiments, allows for simplified implementation of multiple BSS use cases compared to customizing each use case and BSS component layer in related art systems. The above-described architecture allows for simplification and orienting the BSS solution toward a Software as a Service (SaaS) implementation model. The above-described architecture provides an improvement over related art systems by allowing data to move across all BSS components through the introduction of real-time event streams (e.g., Kafka Streams).

[0052] The above architecture includes a key component for use in Digital Evolution, i.e., deploying a BSS solution as a SaaS solution while still providing the product uniqueness (i.e., customized use cases specific to each operator) required across operators. That is, the above BSS solution deployed as a SaaS solution enables operators to launch services with lower upfront costs and faster time to market.

[0053] Additionally, the inclusion of event-based capabilities using real-time event streams (e.g., Kafka) enables efficient distribution of data across all components. Furthermore, the inclusion of automated workflow capabilities provides a no-code or low-code layer for users to customize their own use cases. Relatedly, the introduction of real-time analytics as part of the automation layer brings real-time analytics closer to the customer engagement layer. Furthermore, the implementation reduces the need for extensive API calls across the platform compared to related systems such as those shown in Figure 1, which require excessive API integrations and calls to transfer data and interact between different layers or components of the BSS architecture. This reduces operational complexity and improves overall performance.

[0054] The table below provides some examples / implementations of use cases that can be deployed with more flexibility and faster time to market using the new proposed architecture approach.

[0055] [Table 1]

[0056] The above-described architecture provides greater flexibility for deploying BSS use cases while simplifying the overall ODA architecture compared to traditional systems. This enables operators (e.g., telecommunications carriers) to rapidly deploy standard product-based SaaS BSS solutions while still having the flexibility to deploy their own use cases. For BSS vendors, the architectural approach simplifies their efforts to develop and deploy SaaS versions of their BSS products.

[0057] According to the architecture described above, BSS SaaS solutions require much lower initial investment, faster time-to-market, and the flexibility to scale as customer needs grow compared to traditional systems.

[0058] 5 illustrates a system 500 configured based on an extended Open Digital Architecture (ODA) (100) for a support system, such as a business support system (BSS), according to one or more implementations. In some implementations, the system 500 may include one or more computing platforms 502. The computing platforms 502 may be configured to communicate with one or more remote platforms 504 according to a client / server architecture, a peer-to-peer architecture, and / or other architectures. The remote platforms 504 may be configured to communicate via the computing platforms 502 and / or with other remote platforms according to a client / server architecture, a peer-to-peer architecture, and / or other architectures. A user may access the computing platforms 502 via the remote platforms 504.

[0059] The computing platform 502 may be configured with machine-readable instructions 506, i.e., one or more instruction modules. The instruction modules (i.e., computer-readable or machine-readable instructions executable by at least one processor to perform a corresponding function) may include one or more of a computer architecture layer receiving module 508, a computer architecture layer determining module 510, a computer architecture layer providing module 512, a model generating module 514, a model managing module 516, and / or other instruction modules.

[0060] 5, the computer architecture layer receiving module 508 can be configured to receive a first user request in a first computer architecture layer. The first computer architecture layer can be a core commerce and customer engagement layer (as shown in FIG. 2). The first user request can be a SaaS or BSS-related request.

[0061] The computer architecture layer determination module 510 may be configured to determine, in real time, a category of the first user request via a second computer architecture layer. The second computer architecture layer may be an event-based automation workflow layer (as shown in FIG. 2 ). The first computer architecture layer may be configurable based on the category of the first user request.

[0062] A second computer architecture layer allows the combination of data from multiple sources and / or tools to create a centralized customer database(s) that contains data about each and every touchpoint and interaction with a product or service, which can then be segmented in an almost infinite number of ways, for example, to create personalized marketing campaigns.

[0063] The computer architecture layer provisioning module 512 can be configured to provide an automated workflow and customer data platform for data entry and manipulation by a user through a second computer architecture layer based on a category of the first user request. The user can make a second request.

[0064] The model generation module 514 may be configured to generate a productization model based on the second user requirements via a third computer architecture layer, which may be a core production platform layer (as shown in FIG. 2).

[0065] The model management module 516 may be configured to intelligently manage the productization models via the fourth computer architecture layer 204. The fourth computer architecture layer 204 may be an intelligent management layer (as shown in FIG. 2). Additionally, internal reporting may be centralized in the fourth computer architecture layer 204. Management of the productization models via the fourth computer architecture layer 204 may be centralized.

[0066] According to an embodiment, a fifth computer architecture layer may also be provided, for example, provided as a cloud infrastructure management layer (as shown in FIG. 2).

[0067] In some implementations, the computing platform 502, the remote platform 504, and / or the external resources 518 may be operatively linked via one or more electronic communication links from the network cloud 519. For example, such electronic communication links may be established, at least in part, via a network, such as the Internet and / or other networks. This is not intended to be limiting, and it will be understood that the scope of the present disclosure includes implementations in which the computing platform 502, the remote platform 504, and / or the external resources 518 may be operatively linked via some other communication medium.

[0068] A given remote platform 504 may include one or more processors configured to execute computer program modules that may be configured to enable a professional or user associated with the given remote platform 504 to interface with the system 500 and / or external resources 518 and / or provide other functionality attributed to the remote platform 504 herein. By way of non-limiting example, a given remote platform 504 and / or a given computing platform 502 may include one or more of a server, a desktop computer, a laptop computer, a handheld computer, a tablet computing platform, a NetBook, a smartphone, a gaming console, and / or other computing platforms.

[0069] External resources 518 may include sources of information external to system 500, external entities involved with system 500, and / or other resources. In some implementations, some or all of the functionality attributed herein to external resources 518 may be provided by resources included in system 500.

[0070] Computing platform 502 may include electronic storage 520, one or more processors 522, and / or other components. Computing platform 502 may include communication lines or ports that allow for the exchange of information with a network and / or other computing platforms. The illustration of computing platform 502 in FIG. 5 is not intended to be limiting. Computing platform 502 may include multiple hardware, software, and / or firmware components that work together to provide the functionality attributed to computing platform 502 herein. For example, computing platform 502 may be implemented by a cloud of computing platforms that work together as computing platform 502. Other implementations are described in more detail below.

[0071] Electronic storage 520 may comprise non-transitory storage media that electronically store information. The electronic storage media of electronic storage 520 may include one or both of system storage provided integrally with computing platform 502 (i.e., substantially non-removable) and / or removable storage removably connectable to computing platform 502 via, for example, a port (e.g., a USB port, a FireWire port, etc.) or a drive (e.g., a disk drive, etc.). Electronic storage 520 may include one or more of optically readable storage media (e.g., optical disks, etc.), magnetically readable storage media (e.g., magnetic tape, magnetic hard drives, floppy drives, etc.), charge-based storage media (e.g., EEPROM, RAM, etc.), solid-state storage media (e.g., flash drives, etc.), and / or other electronically readable storage media. Electronic storage 520 may also include one or more virtual storage resources (e.g., cloud storage, virtual private networks, and / or other virtual storage resources). Electronic storage 520 may store software algorithms, information determined by processor 522, information received from computing platform 502, information received from remote platform 504, and / or other information that enables computing platform 502 to function as described herein.

[0072] The processor 522 can be configured to provide information processing capabilities in the computing platform 502. As such, the processor 522 may include one or more of a digital processor, an analog processor, a digital circuit designed to process information, an analog circuit designed to process information, a state machine, and / or other mechanisms for electronically processing information. While the processor 522 is depicted in FIG. 5 as a single entity, this is for illustrative purposes only. In some implementations, the processor 522 may include multiple processing units. These processing units may be physically located within the same device, or the processor 522 may represent the processing functions of multiple devices acting in concert. The processor 522 may be configured to execute modules 508, 510, 512, 514, and / or 516, and / or other modules. Processor 522 may be configured to execute modules 508, 510, 512, 514, and / or 516 and / or other modules by software; hardware; firmware; some combination of software, hardware, and / or firmware; and / or other mechanisms for configuring processing power on processor 522. As used herein, the term "module" may refer to any component or set of components that perform the functions attributed to a module. This may include one or more physical processors executing processor-readable instructions, circuitry, hardware, storage media, or any other component.

[0073] 5 as being implemented within a single processing unit, it should be understood that in implementations in which processor 522 includes multiple processing units, one or more of modules 508, 510, 512, 514, and / or 516 may be implemented remotely from the other modules. The description of functionality provided by different modules 508, 510, 512, 514, and / or 516 described below is for illustrative purposes and is not intended to be limiting, as any of modules 508, 510, 512, 514, and / or 516 may provide more or less functionality than described. For example, one or more of modules 508, 510, 512, 514, and / or 516 may be eliminated, and some or all of its functionality may be provided by other of modules 508, 510, 512, 514, and / or 516. As another example, processor 522 may be configured to execute one or more additional modules that may perform some or all of the functionality attributed below to one of modules 508, 510, 512, 514, and / or 516.

[0074] 6 illustrates a method 600 according to one or more implementations. The operations of method 600 presented below are intended to be exemplary. In some implementations, method 600 may be achieved with one or more additional operations not described and / or without one or more of the operations described. Additionally, the order in which the operations of method 600 are shown in FIG. 6 and described below is not intended to be limiting.

[0075] In some implementations, method 600 may be implemented in one or more processing devices (e.g., digital processors, analog processors, digital circuits designed to process information, analog circuits designed to process information, state machines, and / or other mechanisms for electronically processing information). The one or more processing devices may include one or more devices that perform some or all of the operations of method 600 in response to instructions electronically stored on an electronic storage medium. The one or more processing devices may include one or more devices configured via hardware, firmware, and / or software that would be specifically designed to perform one or more of the operations of method 600.

[0076] Operation 601 may include receiving a first user request in a first computer architecture layer. Operation 601 may be performed by one or more hardware processors configured with machine-readable instructions, including modules the same as or similar to computer architecture layer receiving module 508, according to one or more implementations.

[0077] Operation 602 may include determining, in real time, a category of the first user request via a second computer architecture layer. Operation 602 may be performed by one or more hardware processors configured with machine-readable instructions, including modules the same as or similar to computer architecture layer determination module 510, according to one or more implementations.

[0078] Operation 603 may include providing, via a second computer architecture layer, an automated workflow and customer data platform for data entry and manipulation by a user based on the category of the first user request. The user may make a second request via the automated workflow and customer data platform, such as a request to define a new automated workflow based on data from the customer data platform. Operation 603 may be performed by one or more hardware processors configured with machine-readable instructions, including modules the same as or similar to computer architecture layer provisioning module 512, according to one or more implementations.

[0079] Operation 604 may include generating, via a third computer architecture layer, a productization model (i.e., a model for implementing a use case customized by an end user using the BSS ODA) based on the second user request. For example, the productization model may be an automated workflow according to the second user request. Operation 604 may be performed by one or more hardware processors configured with machine-readable instructions, including modules the same as or similar to model generation module 514, according to one or more implementations.

[0080] Operation 605 may include intelligently managing the productization model via a fourth computer architecture layer. Operation 605 may be performed by one or more hardware processors configured with machine-readable instructions, including modules that are the same as or similar to model management module 516, according to one or more implementations. Intelligent management of the model may include integration with artificial intelligence models to provide input (e.g., inference) or to automatically drive model execution, data visualization of reports generated from the model (e.g., of data processed or output by the model), etc.

[0081] 7 is a diagram of an example environment 700 in which the systems and / or methods described herein may be implemented. As shown in FIG. 7, environment 700 may include a user device 710, a platform 720, and a network 730. The devices in environment 700 may be interconnected via wired connections, wireless connections, or a combination of wired and wireless connections. In embodiments, any of the functions and operations described with reference to FIGS. 4 and 6 above may be performed by any combination of elements shown in FIG. 7.

[0082] User device 710 includes one or more devices capable of receiving, generating, storing, processing, and / or providing information related to platform 720. For example, user device 710 may include a computing device (e.g., a desktop computer, a laptop computer, a tablet computer, a handheld computer, a smart speaker, a server, etc.), a mobile phone (e.g., a smartphone, a wireless telephone, etc.), a wearable device (e.g., smart glasses or a smart watch), or similar device. In some implementations, user device 710 may receive information from and / or transmit information to platform 720.

[0083] Platform 720 includes one or more devices capable of receiving, generating, storing, processing, and / or providing information. In some implementations, platform 720 may include a cloud server or a group of cloud servers. In some implementations, platform 720 may be designed to be modular, such that particular software components can be swapped in or out depending on particular needs. Thus, platform 720 may be easily and / or quickly reconfigured for different uses.

[0084] In some implementations, as shown, platform 720 may be hosted in a cloud computing environment 722. Notably, although the implementations described herein describe platform 720 as being hosted within cloud computing environment 722, in some implementations platform 720 may not be cloud-based (i.e., may be implemented outside of a cloud computing environment) or may be partially cloud-based.

[0085] Cloud computing environment 722 includes an environment that hosts platform 720. Cloud computing environment 722 can provide services such as computation, software, data access, storage, etc. that do not require end-user (e.g., user device 710) knowledge of the physical location and configuration of the systems and / or devices that host platform 720. As shown, cloud computing environment 722 can include a group of computing resources 724 (collectively referred to as “computing resources 724” and individually referred to as “computing resource 724”).

[0086] Computing resources 724 include one or more personal computers, clusters of computing devices, workstation computers, server devices, or other types of computing and / or communication devices. In some implementations, computing resources 724 may host platform 720. Cloud resources may include compute instances executing within computing resources 724, storage devices provided within computing resources 724, data transfer devices provided by computing resources 724, etc. In some implementations, computing resources 724 may communicate with other computing resources 724 via wired connections, wireless connections, or a combination of wired and wireless connections.

[0087] As further shown in FIG. 7, computing resources 724 include a group of cloud resources such as one or more applications (“APP”) 724-1, one or more virtual machines (“VM”) 724-2, virtualized storage (“VS”) 724-3, and one or more hypervisors (“HYP”) 724-4.

[0088] Applications 724-1 include one or more software applications that may be provided to or accessed by user device 710. Applications 724-1 may obviate the need to install and run software applications on user device 710. For example, applications 724-1 may include software associated with platform 720 and / or any other software that may be provided via cloud computing environment 722. In some implementations, one application 724-1 may send information to or receive information from one or more other applications 724-1 via virtual machine 724-2.

[0089] Virtual machine 724-2 includes a software-implemented machine (e.g., a computer) that executes programs like a physical machine. Virtual machine 724-2 can be either a system virtual machine or a process virtual machine, depending on the application and the degree to which virtual machine 724-2 matches an actual machine. A system virtual machine can provide a complete system platform that supports the execution of a complete operating system (“OS”). A process virtual machine can execute a single program and support a single process. In some implementations, virtual machine 724-2 may run on behalf of a user (e.g., user device 710) and manage the infrastructure of cloud computing environment 722, such as data management, synchronization, or long-term data transfer.

[0090] Virtualized storage 724-3 includes one or more storage systems and / or one or more devices that use virtualization technology within the storage systems or devices of computing resources 724. In some implementations, in the context of storage systems, types of virtualization may include block virtualization and file virtualization. Block virtualization may refer to the abstraction (or separation) of logical storage from physical storage such that the storage system can be accessed regardless of the physical storage or heterogeneous structure. The separation may allow administrators flexibility in how they manage the storage for end users. File virtualization can eliminate the dependency between data accessed at the file level and where the file is physically stored. This may enable optimization of storage usage, server consolidation, and / or performing non-disruptive file movements.

[0091] The hypervisor 724-4 can provide hardware virtualization technology that allows multiple operating systems (e.g., "guest operating systems") to run simultaneously on a host computer, such as the computing resource 724. The hypervisor 724-4 can present a virtual operating platform to the guest operating systems and can manage the execution of the guest operating systems. Multiple instances of different operating systems can share virtualized hardware resources.

[0092] Network 730 may include one or more wired and / or wireless networks. For example, network 730 may include a cellular network (e.g., a fifth-generation (5G) network, a long-term evolution (LTE) network, a third-generation (3G) network, a code division multiple access (CDMA) network, etc.), a public land mobile network (PLMN), a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a telephone network (e.g., a public switched telephone network (PSTN)), a private network, an ad hoc network, an intranet, the Internet, an optical fiber-based network, etc., and / or a combination of these or other types of networks.

[0093] The number and arrangement of devices and networks shown in Figure 7 are provided as an example. In practice, there may be additional, fewer, different, or differently arranged devices and / or networks than those shown in Figure 7. Furthermore, two or more devices shown in Figure 7 may be implemented within a single device, or a single device shown in Figure 7 may be implemented as multiple distributed devices. Additionally, or instead, a set of devices in environment 700 (e.g., one or more devices) may perform one or more functions that are described as being performed by another set of devices in environment 700.

[0094] 8 is a diagram of example components of a device 800. The device 800 may correspond to a user device 810 and / or a platform 820. As shown in FIG. 8, the device 800 may include a bus 810, a processor 820, a memory 830, a storage component 840, an input component 850, an output component 860, and a communication interface 870.

[0095] Bus 810 includes components that enable communication between components of device 800. Processor 820 may be implemented in hardware, firmware, or a combination of hardware and software. Processor 820 may be a central processing unit (CPU), graphics processing unit (GPU), accelerated processing unit (APU), microprocessor, microcontroller, digital signal processor (DSP), field programmable gate array (FPGA), application specific integrated circuit (ASIC), or another type of processing component. In some implementations, processor 820 includes one or more processors that can be programmed to perform functions. Memory 830 includes random access memory (RAM), read-only memory (ROM), and / or another type of dynamic or static storage device (e.g., flash memory, magnetic memory, and / or optical memory) that stores information and / or instructions for use by processor 820.

[0096] The storage component 840 stores information and / or software related to the operation and use of the device 800. For example, the storage component 840 may include a hard disk (e.g., a magnetic disk, optical disk, magneto-optical disk, and / or solid-state disk), a compact disk (CD), a digital versatile disk (DVD), a floppy disk, a cartridge, magnetic tape, and / or another type of non-transitory computer-readable medium, along with a corresponding drive. The input component 850 includes components that enable the device 800 to receive information, such as via user input (e.g., a touchscreen display, a keyboard, a keypad, a mouse, buttons, switches, and / or a microphone). Additionally or alternatively, the input component 850 may include sensors for sensing information (e.g., a global positioning system (GPS) component, an accelerometer, a gyroscope, and / or an actuator). The output component 860 includes components that provide output information from the device 800 (e.g., a display, a speaker, and / or one or more light-emitting diodes (LEDs)).

[0097] Communications interface 870 includes transceiver-like components (e.g., a transceiver and / or a separate receiver and transmitter) that allow device 800 to communicate with other devices, such as via a wired connection, a wireless connection, or a combination of wired and wireless connections. Communications interface 870 may allow device 800 to receive information from and / or provide information to another device. For example, communications interface 870 may include an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, a radio frequency (RF) interface, a universal serial bus (USB) interface, a Wi-Fi interface, a cellular network interface, etc.

[0098] Device 800 may perform one or more processes described herein. Device 800 may perform these processes in response to processor 820 executing software instructions stored by a non-transitory computer-readable medium, such as memory 830 and / or storage component 840. A computer-readable medium is defined herein as a non-transitory memory device. A memory device includes memory space within a single physical storage device or memory space spread across multiple physical storage devices.

[0099] The software instructions may be loaded into memory 830 and / or storage component 840 from another computer-readable medium or from another device via communications interface 870. When executed, the software instructions stored in memory 830 and / or storage component 840 may cause processor 820 to perform one or more processes described herein.

[0100] Additionally, or instead, hardwired circuitry may be used in place of or in combination with software instructions to perform one or more processes described herein. Thus, implementations described herein are not limited to any specific combination of hardware circuitry and software.

[0101] The number and arrangement of components shown in Figure 8 are provided as an example. In practice, device 800 may include additional, fewer, different, or differently arranged components than those shown in Figure 8. Additionally or alternatively, a set of components (e.g., one or more components) of device 800 may perform one or more functions described as being performed by another set of components of device 800.

[0102] In an embodiment, any one of the operations or processes of FIGS. 4 and 6 may be implemented by or using any one of the elements shown in FIGS.

[0103] The foregoing disclosure provides illustration and description, but is not intended to be exhaustive or to limit the implementation to the precise form disclosed. Modifications and variations are possible in light of the above disclosure or may be acquired from practicing the implementations.

[0104] Some embodiments may relate to systems, methods, and / or computer-readable media at any possible level of technical detail integration. Furthermore, one or more of the above components described above may be implemented as instructions stored on a computer-readable medium and executable by at least one processor (and / or may include at least one processor). The computer-readable medium may include computer-readable non-transitory storage medium(s) having computer-readable program instructions for causing a processor to perform operations.

[0105] A computer-readable storage medium may be a tangible device capable of retaining and storing instructions for use by an instruction-execution device. A computer-readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of computer-readable storage media includes portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital versatile disc (DVD), memory stick, floppy disk, mechanically encoded devices such as punch cards or ridge-in-groove structures on which instructions are recorded, and any suitable combination of the foregoing. Computer-readable storage media, as used herein, should not be construed as a transitory signal per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., light pulses passing through a fiber optic cable), or electrical signals transmitted through wires.

[0106] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device or to an external computer or external storage device over a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may include copper transmission cables, optical transmission fiber, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing / processing device.

[0107] The computer-readable program code / instructions for carrying out operations may be either source code or object code written in any combination of one or more programming languages, including assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, configuration data for integrated circuits, or object-oriented programming languages ​​such as Smalltalk, C++, and procedural programming languages ​​such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet Service Provider). In some embodiments, an electronic circuit, including, for example, a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may execute computer-readable program instructions by utilizing state information of the computer-readable program instructions to personalize the electronic circuit to perform an aspect or operation.

[0108] These computer-readable program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute on the processor of the computer or other programmable data processing apparatus, create means for performing the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams. These computer-readable program instructions may also be stored on a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and / or other device to function in a particular manner, such that the computer-readable storage medium on which the instructions are stored comprises a product including instructions that implement aspects of the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams.

[0109] The computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause the computer, other programmable apparatus, or other device to execute a series of operational steps to create a computer-implemented process, such that the instructions executing on the computer, other programmable apparatus, or other device perform the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams.

[0110] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer-readable media according to various embodiments. In this regard, each block in the flowcharts or block diagrams may represent a module, segment, or portion of instructions, including one or more executable instructions for implementing a particular logical function. The methods, computer systems, and computer-readable media may include additional, fewer, different, or differently arranged blocks compared to the blocks shown in the figures. In some alternative implementations, the functions noted in the blocks may occur in a different order than that noted in the figures. For example, two blocks shown in succession may actually be executed concurrently or substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending on the functionality involved. It should also be noted that each block of the block diagrams and / or flowchart diagrams, and combinations of blocks in the block diagrams and / or flowchart diagrams, may be implemented by a dedicated hardware-based system that performs the specified functions or operations or executes a combination of dedicated hardware and computer instructions.

[0111] It will be apparent that the systems and / or methods described herein may be implemented in various forms of hardware, firmware, or a combination of hardware and software. The actual specialized control hardware or software code used to implement these systems and / or methods is not intended to limit the implementation. Thus, the operation and behavior of the systems and / or methods are described herein without reference to specific software code, and it will be understood that software and hardware may be designed to implement the systems and / or methods based on the description herein.

Claims

1. 1. A system for implementing a Business Support System (BSS) architecture, comprising: at least one memory for storing instructions; at least one processor configured to execute the instructions to implement the BSS architecture; The BSS architecture comprises: Multiple layers and a real-time event stream for transferring real-time event streams of data between components of the plurality of layers; The plurality of layers an engagement and core commerce management layer for providing multiple user interfaces corresponding to multiple use cases of the BSS architecture; an event-based automation and user data platform layer including a real-time customer data platform (CDP) and a plurality of automation workflows for executing the plurality of use cases based on real-time data from the CDP; a core BSS component layer including core BSS components; an intelligent management layer for managing insights, model development, and batch model execution; a cloud infrastructure management layer configured to provide cloud functionality for a Software as a Solution (SaaS) implementation of the BSS architecture. system.

2. The system of claim 1 , wherein the BSS architecture further comprises an open application programming interface (API) for real-time information provisioning of the data between the components.

3. The system of claim 1 , wherein the real-time event stream is a Kafka event stream.

4. The system of claim 1 , wherein the BSS architecture further comprises a management component used across the multiple layers.

5. The system of claim 1 , wherein the plurality of user interfaces are each configurable by a customer of the SaaS implementation without hard coding.

6. The system of claim 1 , wherein the BSS component is productized in the SaaS implementation.

7. The system of claim 1 , wherein the components of the multiple layers are executable by the at least one processor as microservices.

8. 1. A method for implementing a business support system (BSS) architecture, comprising: Executing, by at least one processor, instructions to implement multiple layers of the BSS architecture; transferring data between components of the plurality of layers via real-time event streams; The plurality of layers an engagement and core commerce management layer for providing multiple user interfaces corresponding to multiple use cases of the BSS architecture; an event-based automation and user data platform layer including a real-time customer data platform (CDP) and a plurality of automation workflows for executing the plurality of use cases based on real-time data from the CDP; a core BSS component layer including core BSS components; an intelligent management layer for managing insights, model development, and batch model execution; a cloud infrastructure management layer configured to provide cloud functionality for a Software as a Solution (SaaS) implementation of the BSS architecture. method.

9. The method of claim 8 , wherein the BSS architecture further comprises an open application programming interface (API) for real-time information provisioning of the data between the components.

10. The method of claim 8 , wherein the real-time event stream is a Kafka event stream.

11. The method of claim 8 , wherein the BSS architecture further comprises a management component used across the multiple layers.

12. The method of claim 8 , wherein the plurality of user interfaces are each configurable by a customer of the SaaS implementation without hard coding.

13. The method of claim 8 , wherein the BSS component is productized in the SaaS implementation.

14. The method of claim 8 , wherein the components of the multiple layers are executable by the at least one processor as microservices.

15. A non-transitory computer-readable storage medium having instructions embodied thereon, the instructions being executable by at least one processor to perform a method, the method comprising: Executing, by the at least one processor, instructions to implement multiple layers of a business support system (BSS) architecture; transferring data between components of the plurality of layers via real-time event streams; The plurality of layers an engagement and core commerce management layer for providing multiple user interfaces corresponding to multiple use cases of the BSS architecture; an event-based automation and user data platform layer including a real-time customer data platform (CDP) and a plurality of automation workflows for executing the plurality of use cases based on real-time data from the CDP; a core BSS component layer including core BSS components; an intelligent management layer for managing insights, model development, and batch model execution; a cloud infrastructure management layer configured to provide cloud functionality for a Software as a Solution (SaaS) implementation of the BSS architecture. A non-transitory computer-readable storage medium.

16. 16. The computer-readable storage medium of claim 15, wherein the BSS architecture further comprises an open application programming interface (API) for real-time information provisioning of the data between the components.

17. 16. The computer-readable storage medium of claim 15, wherein the real-time event stream is a Kafka event stream.

18. The computer-readable storage medium of claim 15 , wherein the BSS architecture further comprises a management component used across the multiple layers.

19. 16. The computer-readable storage medium of claim 15, wherein the plurality of user interfaces are each configurable by a customer of the SaaS implementation without hard coding.

20. The computer-readable storage medium of claim 15 , wherein the BSS component is productized in the SaaS implementation.

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