Methods, systems, and storage media for implementing an extended open digital architecture for support systems

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] Devices and methods consistent with exemplary embodiments of the present disclosure relate to an extended open digital architecture (ODA) for a support system, such as a business support system (BSS).

Background Art

[0002] (For example, for a communication business system) the related art BSS ODA architecture is typically configured as a multi-layer architecture based on engagement management, subscriber management, core commerce management, a core production platform, and intelligent management, all of which are integrated via application programming interfaces (APIs). FIG. 1 shows an example of this related art architecture 100, which includes an engagement management layer 101, a subscriber management sub-layer 103, a core commerce sub-layer 104, a core production sub-layer 105, and an intelligent management layer 106. In the related art architecture, API 102 integration is required across the aforementioned components to provide component-to-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 cloud tech stacks does not address these issues without further changing at least the underlying architecture. By themselves, microservices do not provide greater flexibility, better time-to-market, reduced customization costs, and reduced overall solution costs compared to the related art architecture.

[0004] Currently, custom use cases are being developed and deployed as core production components of the BSS solution (i.e., hardcoded). This is a major challenge when deploying the BSS solution on a Software as a Service (SaaS) based subscription model, which requires significant upfront investment from any telecommunications operator.

[0005] Embodiments of this disclosure can address these issues and provide greater flexibility, faster time to market, reduced customization costs, and lower overall solution costs compared to current state-of-the-art architectures, including implementations in microservices and cloud tech stacks. [Overview of the project]

[0006] According to one aspect of this disclosure, a system is provided for implementing a Business Support System (BSS) architecture, the system comprising at least one memory for storing instructions and at least one processor configured to execute instructions in order 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 multiple layers, the multiple layers comprising 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 real-time customer data and multiple automation workflows for executing multiple 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 this disclosure, the BSS architecture may further include an Open Application Programming Interface (API) for real-time information provisioning of data between components.

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

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

[0010] In one aspect of this disclosure, multiple user interfaces may be configurable by the customer of the SaaS implementation without hardcoding.

[0011] In one aspect of this disclosure, the BSS component may be commercialized as a SaaS implementation.

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

[0013] Another aspect of the present disclosure provides a method that includes receiving a first user request within a first computer architecture layer; determining the category of the first user request in real time via a second computer architecture layer; providing an automated workflow and customer data platform for user data entry and manipulation via the second computer architecture layer, based on the category of the first user request, enabling the user to make a second request; generating a production model based on the second user request via a third computer architecture layer; and intelligently managing the production model via a fourth computer architecture layer.

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

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

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

[0017] In one aspect of this disclosure, internal reports relating to the first to fourth architectural layers may be centralized.

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

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

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

[0021] A further aspect of the present disclosure relates to a non-temporary computer-readable storage medium in which instructions are embodied, wherein the instructions are executable by one or more processors to perform a method, the method comprising: receiving a first user request within a first computer architecture layer; determining a category of the first user request in real time via a second computer architecture layer; providing an automated workflow and customer data platform for user data input and manipulation via the second computer architecture layer, based on the category of the first user request, so that the user can make a second request; generating a production model via a third computer architecture layer based on the second user request; and intelligently managing the production model via a fourth computer architecture layer.

[0022] These and other features and characteristics of the present technology, as well as the operation and function of the related structural elements, and the economics of the combination and manufacture of the components, will become more apparent upon consideration of the following description and the attached claims with reference to the attached drawings, all of which form part of this specification, and similar reference numbers indicate corresponding parts of various figures. However, it should be clearly understood that the drawings are for illustrative and explanatory purposes only and are not intended as definitions of the limitations of the present invention. Where used herein and in the claims, the singular “a,” “an,” and “the” refer to plural subjects unless the context explicitly indicates otherwise. [Brief explanation of the drawing]

[0023] The features, advantages, and importance of exemplary embodiments of this disclosure will be described below with reference to the attached drawings, where similar reference numerals indicate similar elements.

[0024] [Figure 1] This diagram shows the Open Digital Architecture (ODA) of the Business Support System (BSS) related technologies.

[0025] [Figure 2] A diagram showing an Open Digital Architecture (ODA) according to one or more implementations.

[0026] [Figure 3] A diagram showing an Open Digital Architecture (ODA) according to one or more implementations.

[0027] [Figure 4] A diagram showing a method according to one or more implementations.

[0028] [Figure 5] A diagram showing a system configured as an extended Open Digital Architecture (ODA) for a support system according to one or more implementations.

[0029] [Figure 6] A diagram showing a method according to one or more implementations.

[0030] [Figure 7] A diagram of an exemplary environment in which the systems and / or methods described herein can be implemented according to an embodiment.

[0031] [Figure 8] A diagram of exemplary components of one or more devices of FIG. 7 according to an embodiment.

MODE FOR CARRYING OUT THE INVENTION

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

[0033] The foregoing disclosures are illustrative and illustrative, but are not intended to be exhaustive or to limit implementations to the exact forms disclosed. Modifications and variations are possible in light of the foregoing disclosures, or such modifications and variations may be obtained from implementations. Furthermore, one or more features or components of one embodiment may be incorporated into another embodiment (or one or more features of another embodiment), or combined with another embodiment (or one or more features of another embodiment). In addition, it should be understood that in the flowcharts and descriptions of operation provided below, one or more operations may be omitted, one or more operations may be added, one or more operations may be performed (at least partially) simultaneously, and the order of one or more operations may be changed.

[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 dedicated control hardware or software code used to implement these systems and / or methods is not limited to the implementation form. Therefore, the operation and behavior of the systems and / or methods have been described herein without reference to specific software code. It will be understood that software and hardware may be designed to implement the systems and / or methods based on the descriptions herein.

[0035] Even if specific combinations of features are described in the claims and / or disclosed herein, these combinations are not intended to limit the disclosure of possible implementations. In fact, many of these features may be combined in ways not specifically described in the claims and / or disclosed herein. Each of the dependent claims listed below may directly depend on only one claim, but the disclosure of possible implementations includes each dependent claim combined with all other claims in the set of claims.

[0036] Any element, action, or command used herein should not be construed as important or essential unless expressly stated otherwise. Furthermore, where used herein, the articles “a” and “an” are intended to include one or more items and may be used interchangeably with “one or more.” When only one item is intended, use the term “one” or similar phrases. Also, where used herein, terms such as “has,” “have,” “having,” “include,” and “including” are intended to be non-restrictive. Additionally, the phrase “based on” is intended to mean “at least partially based on” unless otherwise specified. Furthermore, expressions 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 this disclosure provide a multi-tier business support system (BSS) architecture with a solution-oriented approach that gives operators (e.g., telecommunications operators) more flexible access to the ecosystem. In addition, the embodiments enable a simplification of the Software as a Service (SaaS) approach for BSS vendors.

[0038] Aspects of this disclosure provide a BSS architecture in which the core commerce and customer engagement platforms are merged into a single layer. Such merging enables improved processing efficiency, as well as simplification of sales (e.g., agent sales and direct sales) and care processes.

[0039] Aspects of this 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-reliance on APIs for data transfer between components. According to aspects of this disclosure, most data transfers are performed through this layer to avoid the complexities of API data transfer while providing more efficient traffic throughput. In addition, the introduction of an event streaming layer allows reporting (e.g., usage reports, performance reports, subscriber profile reports, bill payment reports, etc.) to be centralized in the data intelligent layer, and individual reports in each component may not be necessary (although they may be permitted).

[0040] The aspects of this disclosure provide a BSS architecture that includes a workflow automation layer. In addition to improving processing efficiency, this introduction of the workflow automation layer reduces the need to modify the core solution. Custom use cases can be easily and flexibly deployed in this layer through upgrades, modifications, and versioning without requiring hardcoding or modifications to the source code.

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

[0042] According to the aspects of this disclosure, management components such as log management can be centralized. This can be applied to some or all of the management components.

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

[0044] In some embodiments, 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) via 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 be used, and these streams may also be open source. The use of real-time data streams and microservices gives rise to a new, redesigned open-source platform.

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

[0046] Figure 3 shows another embodiment of the BSS ODA architecture. The architecture in Figure 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 analysis layer 304, and an infrastructure management and operations platform layer 305. Similar to the embodiment shown in Figure 2, each of the different layers in Figure 3 may be configured as a real-time event stream layer (e.g., a Kafka event stream layer) via an event stream 306 (e.g., a Kafka event stream) and may be connected via an open API 307. In addition, the different architectural layers may include a management component 308, which includes a digital workflow 309, a security platform 310, a third-party API gateway 311, log management 312, document management 313, and service assurance 314, as described in relation to Figure 2.

[0047] According to the embodiment shown in Figure 3, the customer engagement layer 301 (i.e., the layer that manages the interaction and engagement of customers (e.g., internal customers such as sales teams, service teams, and administrative teams, or external customers such as paying customers) with the system) may include an advertising platform 301-1, an e-commerce platform 301-2, a mobile application platform 301-3, an e-care self-service platform 301-4, a kiosk and display advertising platform 301-5, and a media platform 301-6. The event-based and real-time decision engine layer 302 (i.e., the layer that makes event-based decisions) may include an automated workflow platform 302-1, a real-time customer data platform 302-2, a prescriptive analytics platform 302-3, and a predictive analytics platform 302-4. The Core BSS Component Layer 303 (i.e., the layer containing 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 Pricing and Billing Platform 303-9, a Campaign and Lead Management Platform 303-10, a Membership and 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 Intermediary Platform 303-17. The insights 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, an AI asset 304-4, and a descriptive analytics platform 304-5.Furthermore, the infrastructure management and operations platform layer 305 (i.e., the layer that manages and controls the required infrastructure, such as provisioning databases that host the required cloud infrastructure) may include the cloud infrastructure and network platform 305-1 and the cloud orchestration platform 305-2.

[0048] Figure 4 illustrates one or more implementations of Method 400. The operation of Method 400 presented below is intended to be illustrative. 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. In addition, the order in which the operation of Method 400 is shown in Figure 4 and described below is not intended to be limiting.

[0049] In some implementations, Method 400 can 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). 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 in an electronic storage medium. One or more processing devices may include one or more devices configured via hardware, firmware, and / or software that will be specifically designed for one or more executions of the operations of Method 400.

[0050] Operation 401 may include implementing a Business Support System (BSS) architecture, and operation 402 may include transferring data between components of multiple layers via a real-time event stream. The BSS architecture may correspond to the architecture described above with reference to Figures 2 and 3.

[0051] The above-described architecture, in one or more embodiments, enables a simplified implementation of multiple BSS use cases compared to customizing each use case and BSS component layer in systems of related technologies. The above-described architecture enables simplification and orientation of BSS solutions toward a Software as a Service (SaaS) implementation model. The above-described architecture provides improvements compared to systems of related technologies by enabling the movement of data across all BSS components through the introduction of real-time event streams (e.g., Kafka streams).

[0052] The architecture described above includes key components for digital evolution, that is, deploying the BSS solution as a SaaS solution while still providing the product uniqueness required by businesses (i.e., customized use cases specific to each business). In other words, the BSS solution deployed as a SaaS solution enables businesses to launch services with lower upfront costs and faster time to market.

[0053] In addition, including event-based capabilities using real-time event streams (e.g., Kafka) enables efficient data distribution across all components. Furthermore, including automated workflow capabilities provides a no-code or low-code layer for users to customize their own use cases. Relatedly, introducing real-time analytics as part of the automation layer brings real-time analytics closer to the customer engagement layer. Moreover, depending on the implementation, it becomes possible to reduce the need for extensive API calls across the platform compared to related systems such as the one shown in Figure 1, which require excessive API integration 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 several example / implementation forms of use cases that can be deployed with greater flexibility and faster time to market using the newly proposed architectural approach.

[0055] [Table 1]

[0056] The architecture described above simplifies the overall ODA architecture compared to traditional systems while providing greater flexibility for deploying BSS use cases. This allows operators (e.g., telecommunications companies) to rapidly deploy standard product-based SaaS BSS solutions while still retaining 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, the BSS SaaS solution requires significantly less initial investment, has a faster timeline to market, and offers the flexibility to scale as customer needs grow, compared to traditional systems.

[0058] Figure 5 shows a system 500 configured based on an Extended Open Digital Architecture (ODA) (100) for a support system, such as a Business Support System (BSS), relating to one or more implementations. In some implementations, system 500 may include one or more computing platforms 502. The computing platform 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 architecture. The remote platform 504 may be configured to communicate with other remote platforms via the computing platform 502 and / or according to a client / server architecture, a peer-to-peer architecture, and / or other architecture. Users can access the computing platform 502 via the remote platform 504.

[0059] The computing platform 502 may consist of machine-readable instructions 506, i.e., one or more instruction modules. An instruction module (i.e., a computer-readable or machine-readable instruction that can be executed by at least one processor to perform a corresponding function) may include one or more of the following: a computer architecture layer receiving module 508, a computer architecture layer decision module 510, a computer architecture layer providing module 512, a model generation module 514, a model management module 516, and / or other instruction modules.

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

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

[0062] The second computer architecture layer allows the combination of data from multiple sources and / or tools to create a centralized customer database (or more) containing data on every possible touchpoint and interaction with a product or service. This database can then be segmented in virtually unlimited ways, for example, to create personalized marketing campaigns.

[0063] The computer architecture layer providing module 512 may be configured to provide an automated workflow and customer data platform for user data entry and manipulation via a second computer architecture layer, based on a first category of user requests. The user can make a second request.

[0064] The model generation module 514 may be configured to generate a product model based on a second user requirement via a third computer architecture layer. The third computer architecture layer may be a core production platform layer (as shown in Figure 2).

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

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

[0067] In some implementations, the computing platform 502, the remote platform 504, and / or external resources 518 may be operationally 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 this disclosure includes implementations in which the computing platform 502, the remote platform 504, and / or external resources 518 may be operationally linked via some other communication medium.

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

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

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

[0071] The electronic storage 520 may include non-temporary storage media for electronically storing information. The electronic storage media of the electronic storage 520 may include either or both system storage provided integrally with the computing platform 502 (i.e., substantially inremovable) and / or removable storage that is removablely connected to the 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.). The electronic storage 520 may include one or more of the following: optically readable storage media (e.g., optical discs, 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. The electronic storage 520 may also include one or more virtual storage resources (e.g., cloud storage, a virtual private network, and / or other virtual storage resources). The electronic storage 520 may store software algorithms, information determined by the processor 522, information received from the computing platform 502, information received from the remote platform 504, and / or other information that enables the 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. Therefore, the processor 522 may include one or more of the following: a digital processor, an analog processor, digital circuits designed to process information, analog circuits designed to process information, a state machine, and / or other mechanisms for electronically processing information. Although the processor 522 is shown as a single entity in Figure 5, 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 capabilities of multiple devices working together. The processor 522 may be configured to run modules 508, 510, 512, 514, and / or 516, and / or other modules. The processor 522 may be configured to run modules 508, 510, 512, 514, and / or 516, and / or other modules, by software; hardware; firmware; any combination of software, hardware, and / or firmware; and / or other mechanisms for configuring processing power on the processor 522. As used herein, the term “module” may refer to any component or set of components that perform a function attributable to the module. This may include processor-readable instructions, circuitry, hardware, storage media, or one or more physical processors running any other component.

[0073] While modules 508, 510, 512, 514, and / or 516 are shown in Figure 5 as being implemented within a single processing unit, it should be understood that in an implementation where the 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 descriptions of the functions provided by the different modules 508, 510, 512, 514, and / or 516 described below are illustrative and not intended to be limiting, as any one 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 excluded, and some or all of their functionality may be provided by the others of modules 508, 510, 512, 514, and / or 516. As another example, processor 522 may be configured to run one or more additional modules that can perform some or all of the functions attributed to one of modules 508, 510, 512, 514, and / or 516.

[0074] Figure 6 shows one or more implementations of Method 600. The operation of Method 600 presented below is intended to be illustrative. 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. In addition, the order in which the operation of Method 600 is shown in Figure 6 and described below is not intended to be limiting.

[0075] In some implementations, Method 600 can 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). 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 in an electronic storage medium. One or more processing devices may include one or more devices configured via hardware, firmware, and / or software that will be specifically designed for one or more executions of the operations of Method 600.

[0076] Operation 601 may include receiving a first user request within a first computer architecture layer. Operation 601 may be executed by one or more hardware processors comprising machine-readable instructions, which include a module that is the same as or similar to the computer architecture layer receiving module 508, according to one or more implementations.

[0077] Operation 602 may include determining the category of the first user request in real time via a second computer architecture layer. Operation 602 may be executed by one or more hardware processors comprising machine-readable instructions, which include a module that is the same as or similar to the computer architecture layer determination module 510, according to one or more implementation forms.

[0078] Operation 603 may include providing an automated workflow and customer data platform for user data entry and manipulation via a second computer architecture layer, based on a first category of user requests. The user can make a second request via the automated workflow and customer data platform, for example, a request to define a new automated workflow based on data from the customer data platform. Operation 603 may be executed by one or more hardware processors comprising machine-readable instructions, including modules that are the same as or similar to the computer architecture layer providing module 512, according to one or more implementation forms.

[0079] Operation 604 may include generating a production model (i.e., a model for implementing a use case customized by the end user using BSS ODA) based on a second user requirement via a third computer architecture layer. For example, the production model may be an automated workflow that conforms to the second user requirement. Operation 604 may be executed by one or more hardware processors consisting of machine-readable instructions, which include modules that are the same as or similar to the model generation module 514, according to one or more implementation forms.

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

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

[0082] The user device 710 includes one or more devices capable of receiving, generating, storing, processing, and / or providing information related to the platform 720. For example, the user device 710 may include computing devices (e.g., desktop computers, laptop computers, tablet computers, handheld computers, smart speakers, servers, etc.), mobile phones (e.g., smartphones, wireless phones, etc.), wearable devices (e.g., smart glasses or smartwatches), or similar devices. In some implementations, the user device 710 may receive information from and / or transmit information to the 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 so that certain software components can be swapped in or swapped out as needed. Thus, Platform 720 can be easily and / or quickly reconfigured for different uses.

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

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

[0086] Computing resource 724 includes 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 resource 724 can host platform 720. Cloud resources may include computing instances running within computing resource 724, storage devices located within computing resource 724, and data transfer devices provided by computing resource 724. In some implementations, computing resource 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 Figure 7, the computing resource 724 includes 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] Application 724-1 includes one or more software applications that may be provided to or accessed by the user device 710. Application 724-1 eliminates the need to install and run software applications on the user device 710. For example, Application 724-1 may include software related to platform 720 and / or any other software that may be provided via the cloud computing environment 722. In some implementations, one application 724-1 may send and receive information to and from one or more other applications 724-1 via a virtual machine 724-2.

[0089] A virtual machine 724-2 includes a machine (e.g., a computer) in the form of a software implementation that runs programs like a physical machine. Depending on its application and the degree to which the virtual machine 724-2 corresponds to an actual machine, it may be either a system virtual machine or a process virtual 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 run a single program and can support a single process. In some implementations, the virtual machine 724-2 may run on behalf of a user (e.g., a user device 710) and may manage the infrastructure of a 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 system or device of the computing resource 724. In some implementations, in the context of a storage system, the types of virtualization may include block virtualization and file virtualization. Block virtualization can refer to the extraction (or isolation) of logical storage from physical storage so that the storage system can be accessed regardless of whether it is physical storage or heterogeneous. Isolation may allow administrators flexibility in how the storage system manages 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 optimized storage usage, server consolidation, and / or non-disruptive file movement.

[0091] Hypervisor 724-4 can provide hardware virtualization technology that enables multiple operating systems (e.g., "guest operating systems") to run simultaneously on a host computer such as Compute Resource 724. Hypervisor 724-4 can present a virtual operating platform to guest operating systems and manage the execution of those guest operating systems. Multiple instances of various operating systems can share virtualized hardware resources.

[0092] Network 730 includes one or more wired and / or wireless networks. For example, Network 730 may include cellular networks (e.g., fifth-generation (5G) networks, long-term evolution (LTE) networks, third-generation (3G) networks, code division multiple access (CDMA) networks, etc.), public land mobile networks (PLMN), local area networks (LANs), wide area networks (WANs), metropolitan area networks (MANs), telephone networks (e.g., public switched telephone networks (PSTNs)), private networks, ad hoc networks, intranets, the Internet, fiber optic-based networks, etc., and / or combinations of these or other types of networks.

[0093] The number and arrangement of devices and networks shown in Figure 7 are provided as examples. In practice, there may be additional devices and / or networks, fewer devices and / or networks, different devices and / or networks, or devices and / or networks in different arrangements compared to 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. In addition, 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] Figure 8 shows an exemplary component of device 800. Device 800 may correspond to user device 810 and / or platform 820. As shown in Figure 8, device 800 may include a bus 810, a processor 820, 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), acceleration 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 device 800. For example, the storage component 840, along with a corresponding drive, may include hard disks (e.g., magnetic disks, optical disks, magneto-optical disks, and / or solid-state disks), compact discs (CDs), digital versatile discs (DVDs), floppy disks, cartridges, magnetic tapes, and / or other types of non-temporary computer-readable media. The input component 850 includes components that enable device 800 to receive information via user input (e.g., touchscreen displays, keyboards, keypads, mice, buttons, switches, and / or microphones). In addition, or instead, the input component 850 may include sensors for sensing information (e.g., Global Positioning System (GPS) components, accelerometers, gyroscopes, and / or actuators). The output component 860 includes components that provide output information from device 800 (e.g., displays, speakers, and / or one or more light-emitting diodes (LEDs)).

[0097] The communication interface 870 includes transceiver-like components (e.g., transceivers and / or separate receivers and transmitters) that enable device 800 to communicate with other devices via wired connections, wireless connections, or a combination of wired and wireless connections. The communication interface 870 may enable device 800 to receive information from and / or provide information to other devices. For example, the communication interface 870 may include Ethernet interfaces, optical interfaces, coaxial interfaces, infrared interfaces, radio frequency (RF) interfaces, Universal Serial Bus (USB) interfaces, Wi-Fi interfaces, cellular network interfaces, and the like.

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

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

[0100] In addition, or instead, hardwired circuits may be used instead of, or in combination with, software instructions to perform one or more of the processes described herein. Therefore, the implementations described herein are not limited to any particular combination of hardware circuits 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 components, fewer components, different components, or components in different arrangements compared to those shown in Figure 8. In addition, or instead, a set of components of device 800 (e.g., one or more components) may perform one or more functions described as being performed by another set of components of device 800.

[0102] In the embodiment, one of the operations or processes shown in Figures 4 and 6 may be implemented by or using one of the elements shown in Figures 7 and 8.

[0103] The foregoing disclosures are intended to provide examples and explanations, but are not intended to be exhaustive or to limit implementations to the exact forms disclosed. Modifications and variations are possible in light of the foregoing disclosures, or such modifications and variations may be obtained from the implementations.

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

[0105] A computer-readable storage medium can be a tangible device capable of holding and storing instructions for use by an instruction execution device. A computer-readable storage medium may, 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 mediums 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 disk read-only memory (CD-ROM), digital multipurpose disks (DVDs), memory sticks, floppy disks, mechanically encoded devices such as punch cards or grooved raised structures on which instructions are recorded, and any suitable combination of the foregoing. The computer-readable storage mediums used herein should not be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., optical pulses through optical fiber cables), 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 via 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 fibers, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface within each computing / processing device receives computer-readable program instructions from the network and transfers the computer-readable program instructions for storage in a computer-readable storage medium within each computing / processing device.

[0107] The computer-readable program code / instructions for performing an operation may be either assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, integrated circuit configuration data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk and C++, and procedural programming languages ​​such as the C programming language or similar programming languages. The computer-readable program instructions may run entirely on the user's computer, partially on the user's computer, as a standalone 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 it may be connected to an external computer (for example, via the Internet using an Internet service provider). In some embodiments, for example, an electronic circuit including 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 computer-readable program instructions for personalizing the electronic circuit in order to perform an action or operation.

[0108] These computer-readable program instructions may be provided to a general-purpose computer, a dedicated computer, or a processor of another programmable data processing device to generate a machine such that instructions executed via the processor of a computer or other programmable data processing device create means for performing functions / operations specified in one or more blocks of a flowchart and / or block diagram. These computer-readable program instructions may also be stored in a computer-readable storage medium that can instruct computers, programmable data processing devices, and / or other devices to function in a particular way, and as a result, the computer-readable storage medium on which the instructions are stored includes a product containing instructions that perform the modes of functions / operations specified in one or more blocks of a flowchart and / or block diagram.

[0109] Computer-readable program instructions may also be loaded onto a computer, another programmable device, or another device to cause a series of operational steps to be executed on the computer, another programmable device, or another device in order to generate a computer implementation process, the instructions executed on the computer, another programmable device, or another device performing the functions / operations specified in one or more blocks of a flowchart and / or block diagram.

[0110] The flowcharts and block diagrams in the figures illustrate the architecture, functions, and operation of possible implementations of systems, methods, and computer-readable media according to various embodiments. In this regard, each block in a flowchart or block diagram may represent a module, segment, or part of an instruction containing one or more executable instructions for implementing a particular logical function. Methods, computer systems, and computer-readable media may include additional blocks, fewer blocks, different blocks, or blocks in different arrangements compared to the blocks shown in the figures. In some alternative implementations, the functions described in the blocks may be performed in a different order than those shown in the figures. For example, two blocks shown consecutively may be executed in practice simultaneously or substantially simultaneously, or blocks may sometimes be executed in reverse order depending on the functions they relate to. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs a specified function or operation, or 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 combinations of hardware and software. The actual dedicated control hardware or software code used to implement these systems and / or methods is not limited to the implementation form. Therefore, the operation and behavior of the systems and / or methods are described herein without reference to specific software code, and it is understood that software and hardware may be designed to implement the systems and / or methods based on the descriptions herein.

Claims

1. A system for implementing a Business Support System (BSS) architecture, At least one memory for storing instructions, The system comprises at least one processor configured to execute the instructions in order to implement the BSS architecture, The aforementioned BSS architecture, Multiple layers, The system includes a real-time event stream for transferring real-time event streams of data between the components of the multiple layers, The aforementioned multiple 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 multiple automation workflows for executing the multiple use cases based on real-time data from the CDP, The core BSS component layer, which includes the core BSS component, An intelligent management layer for managing insights, model development, and batch model execution, The BSS architecture comprises a cloud infrastructure management layer configured to provide cloud functionality for a Software as a Solution (SaaS) implementation. system.

2. The system according to 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 according to claim 1, wherein the real-time event stream is a Kafka event stream.

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

5. The system according to claim 1, wherein each of the plurality of user interfaces can be configured by the customer of the SaaS implementation without hardcoding.

6. The system according to claim 1, wherein the core BSS component is commercialized in the SaaS implementation.

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

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