Computer-based system configured to order transfer of digital

Abstract

In some embodiments, the present disclosure provides an exemplary method that may include the steps of: identifying a plurality of entities seeking to interact with each other; determining a set of workpieces associated with each of the plurality of entities; dynamically connecting the at least two entities based on the determination of the set of workpieces shared between the at least two entities using the cloud-based functionality; dynamically integrating a plurality of protocols into an interaction session associated with the at least two entities; verifying a plurality of protocols associated with the interactive session; initiating an interactive session between at least two entities based on the plurality of protocols and the set of workpieces; and automatically modifying the interaction session to orchestrate transfer of at least one workpiece of the set of workpieces between the at least two entities.

Description

[0001] Related applications

[0002] This application claims the benefits of the following applications, which are incorporated herein by reference in their entirety: U.S. Application No. 63 / 494,186, filed April 4, 2023, entitled “Computer-based Systems Configured to Automatically Update a Security Engine with a Plurality of Notifications and Methods of Use Thereof”; U.S. Application No. 63 / 494,188, filed April 4, 2023, entitled “Computer-based Systems Configured to Dynamically Retrieve a Plurality of Data Points from Disparate Data Sources and Methods of Use Thereof”; U.S. Application No. 63 / 494,193, filed April 4, 2023, entitled “Computer-based Systems Configured to Simultaneously Connect Multiple Parties and Methods of Use Thereof”; and U.S. Application No. 63 / 494,193, filed April 4, 2023, entitled “Computer-based Systems Configured to Generate a Plurality of Navigation Tools for a Plurality of Users”. U.S. Application No. 63 / 494,190, entitled “and Methods of Use Thereof”; and U.S. Application No. 63 / 494,144, filed on April 4, 2023, entitled “Computer-based Systems Configured to Dynamically Modify Input Data in Real-Time Based on a Baseline and Methods of Use Thereof”.U.S. Application No. 63 / 494,195, filed April 4, 2023, entitled "Computer-based Systems Configured to Automatically Connect a Plurality of Data Frameworks Simultaneously and Methods of Use Thereof," and U.S. Application No. 63 / 494,199, filed April 4, 2023, entitled "Computer-based Systems Configured to ModifyData to Perform at Least One Function and Methods of Use Thereof." Technical Field

[0003] This disclosure generally relates to computer-based systems configured to orchestrate the transmission of digital artifacts and methods of using them. Background Technology

[0004] Typically, data transfer is the process of transmitting or transferring electronic or analog data from one computer node to another using computational processes and technologies. Data is transmitted in bits and bytes via digital or analog media, and this process enables digital or analog communication and movement between devices. Digital artifacts are typically unintended or unintentional data alterations introduced during digital processing by the processes and / or technologies involved. Summary of the Invention

[0005] In some embodiments, this disclosure provides an exemplary, technically improved computer-based method, which includes at least the following steps: identifying a plurality of entities seeking to interact with each other; determining a set of artifacts associated with each of the plurality of entities; dynamically connecting the at least two entities based on the determination of artifacts shared between the at least two entities using cloud-based capabilities; dynamically integrating a plurality of protocols into an interaction session associated with the at least two entities in response to connecting the at least two entities, wherein the plurality of protocols associated with the interaction session include connection requests received from each of the plurality of entities; verifying the plurality of protocols associated with the interaction session, wherein verifying the plurality of protocols includes ensuring that the number of sharing requests from the plurality of entities exceeds a predetermined threshold; initiating an interaction session between the at least two entities based on the plurality of protocols and the set of artifacts; and automatically modifying the interaction session to orchestrate the delivery of at least one artifact from the set of artifacts between the at least two entities.

[0006] In some embodiments, a non-transitory computer-readable storage medium tangibly encodes computer-executable instructions, which, when executed by a device, perform a method comprising: identifying a plurality of entities seeking to interact with each other; determining a set of artifacts associated with each of the plurality of entities; dynamically connecting the at least two entities based on the determination of artifacts shared between the at least two entities using cloud-based capabilities; dynamically integrating a plurality of protocols into an interaction session associated with the at least two entities in response to connecting the at least two entities, wherein the plurality of protocols associated with the interaction session include connection requests received from each of the plurality of entities; verifying the plurality of protocols associated with the interaction session, wherein verifying the plurality of protocols includes ensuring that the number of sharing requests from the plurality of entities exceeds a predetermined threshold; initiating an interaction session between the at least two entities based on the plurality of protocols and the set of artifacts; and automatically modifying the interaction session to orchestrate the delivery of at least one artifact from the set of artifacts between the at least two entities. Attached Figure Description

[0007] Various embodiments of this disclosure can be further explained with reference to the accompanying drawings, in which similar structures are indicated by similar numbers throughout the several views. The drawings shown are not necessarily to scale, but rather the emphasis is generally placed on illustrating the principles of this disclosure. Therefore, the specific structural and functional details disclosed herein should not be construed as limiting, but merely as a representative basis for teaching those skilled in the art to employ one or more illustrative embodiments in various ways.

[0008] Figure 1 A block diagram of an exemplary computer-based system and platform for automatically modifying an interactive session to orchestrate the transfer of at least one artifact from a set of artifacts between at least two entities, according to one or more embodiments of the present disclosure, is depicted.

[0009] Figure 2 This is a flowchart illustrating operational steps for automatically modifying an interactive session to orchestrate the transfer of at least one workpiece in a set of workpieces between at least two entities, according to one or more embodiments of the present disclosure.

[0010] Figure 3A and Figure 3B A schematic diagram depicts upstream and downstream methods of an Enterprise Integration Service Layer (EISL) module between at least two entities according to one or more embodiments of this disclosure.

[0011] Figure 4 This is a flowchart illustrating the operational steps of the regulatory transaction control module to report via report enhancement and communicate with the trade verification module.

[0012] Figure 5A block diagram of an exemplary computer-based system / platform according to one or more embodiments of the present disclosure is depicted.

[0013] Figure 6 A block diagram of another exemplary computer-based system / platform according to one or more embodiments of the present disclosure is depicted.

[0014] Figure 7 and Figure 8 This is a diagram illustrating an implementation of a cloud computing architecture / aspect of which the disclosed technology can be specifically configured to operate according to one or more embodiments of this disclosure. Detailed Implementation

[0015] This document discloses various detailed embodiments of the present disclosure in conjunction with the accompanying drawings; however, it should be understood that the disclosed embodiments are merely illustrative. Furthermore, each example given in conjunction with the various embodiments of the present disclosure is intended to be illustrative and not restrictive.

[0016] Throughout this specification, unless the context clearly indicates otherwise, the following terms have the meaning explicitly associated with this document. The phrases “in one embodiment” and “in some embodiments” as used herein do not necessarily refer to the same(s) embodiments(s), but may refer to the same(s) embodiments(s). Furthermore, the phrases “in another embodiment” and “in some other embodiments” as used herein do not necessarily refer to different embodiments, but may refer to different embodiments. Therefore, as described below, various embodiments can be readily combined without departing from the scope or spirit of this disclosure.

[0017] Additionally, the term "based on" is not exclusive and may be based on additional factors not described, unless the context clearly specifies otherwise. Additionally, throughout the specification, the meanings of "a," "an," and "the" include plural references. The meaning of "in..." includes both "in..." and "on...".

[0018] As used herein, the terms “and” and “or” are used interchangeably to refer to sets of items in conjunctive and disjunctive forms to encompass a complete description of combinations and alternatives of items. For example, a set of items can be listed using either a disjunctive “or” or a conjunctive “and”. In either case, the set should be interpreted as meaning each item as an alternative individually, and any combination of the listed items.

[0019] It should be understood that at least one aspect / function of the various embodiments described herein can be performed in real time and / or dynamically. As used herein, the term "real time" refers to an event / action that can occur instantaneously or nearly instantaneously in time while another event / action has already occurred. For example, "real-time processing," "real-time computation," and "real-time execution" all relate to the execution of computation during the actual time during which relevant physical processing (e.g., the creator interacts with an application on a mobile device) occurs, so that the results of the computation can be used to guide the physical process.

[0020] As used herein, the terms “dynamically” and “automatically”, and their logical and / or linguistic related and / or derived terms, indicate that certain events and / or actions can be triggered and / or occur without any human intervention. In some embodiments, events and / or actions according to this disclosure may be real-time and / or based on a predetermined periodicity of at least one of the following: nanoseconds, fractions of nanoseconds, milliseconds, fractions of milliseconds, seconds, fractions of seconds, minutes, minutes, hours, days, days, weeks, months, etc.

[0021] As used herein, the term "runtime" refers to any behavior that is dynamically determined during the execution of a software application or at least a portion thereof.

[0022] At least some embodiments of this disclosure provide technical solutions (one or more) to at least one computer-centric technical problem associated with orchestrating the transfer of digital artifacts between at least two entities that wish to trade with each other. Illustrative computer-centric technical problems associated with verifying the identity of each entity wishing to interact and verifying the multiple protocols associated with the transfer of digital artifacts are typical in this field. This problem also stems from one or more entities seeking anonymity when interacting with other entities, as this may reduce trust in the other entity and may involve and / or trigger fraudulent activities. Moreover, the more complex the digital artifact to be transferred, the more complex the multiple protocols associated with the transfer of that digital artifact, further reducing the optimal efficiency of the interaction. As detailed in at least some embodiments herein, at least one computer-centric technical solution associated with the illustrative computer-centric technical problem may include automatically modifying the interaction session to orchestrate the transfer of a specific artifact between at least two entities. In some embodiments, this disclosure may identify multiple entities seeking to interact with each other. In some embodiments, this disclosure may determine a set of artifacts associated with each of the multiple entities. In some embodiments, the set of artifacts may refer to a set of digital artifacts that can be transferred via a cloud-based network. In some embodiments, this disclosure may utilize cloud-based capabilities to dynamically connect at least two entities based on the determination of artifacts shared between at least two entities. In some embodiments, this disclosure may dynamically integrate multiple protocols into an interaction session associated with an entity. In some embodiments, the multiple protocols may refer to a database of pre-stored rules and / or requirements that enable a secure interaction session between each entity. In some embodiments, this disclosure may verify multiple protocols associated with the interaction session. In some embodiments, the verification of multiple protocols ensures that a certain number of protocols shared between entities meet a predetermined threshold. In some embodiments, this disclosure may initiate an interaction session between entities based on a set of multiple protocols and artifacts that meet the predetermined threshold. In some embodiments, this disclosure may automatically modify the interaction session. Modification may refer to the orchestration of the transfer of at least one artifact between entities.

[0023] Figure 1 A block diagram of an exemplary computer-based system and platform for automatically modifying an interactive session to orchestrate the transfer of at least one artifact from a set of artifacts between at least two entities, according to one or more embodiments of the present disclosure, is depicted.

[0024] In some embodiments, the illustrative computing system 100 of this disclosure may include a computing device 102 associated with at least one user and an illustrative program engine 104. In some embodiments, the illustrative program engine 104 may be stored on the computing device 102. In some embodiments, the illustrative program engine 104 may be stored on the computing device 102, which may include, for example, a processor 108, non-transitory memory 110, a communication circuitry system 112 for communication via a communication network 114 (not shown), and input and / or output (I / O) devices 116, such as a keyboard, mouse, touchscreen, and / or display. In some embodiments, the computing device 102 may refer to at least one of a plurality of communication-enabled computing devices.

[0025] In some embodiments, the illustrative program engine 104 may be configured to instruct the processor 108 to execute one or more software modules, such as, but not limited to, the exemplary transport orchestration module 118, machine learning module 120, and / or data output module 122.

[0026] In some embodiments, the exemplary transport orchestration module 118 of this disclosure may utilize at least one machine learning algorithm described herein to identify multiple entities seeking to interact with each other. In some embodiments, multiple entities may refer to at least one of, but not limited to, at least one individual, enterprise, integration service layer, financial institution, computing device 102, and / or a combination of both. In some embodiments, interaction may refer to the initiation of a transaction and / or communication session between at least two entities. In some embodiments, the exemplary transport orchestration module 118 may identify each of the multiple entities as a prospect, client, party, spouse, child, other relative, lawyer, accountant, stakeholder, corporation, partnership, other legal entity, partner, officer, employer, charity, entity representing a set of accounts, any other related legal entity, and a single entity with multiple entity records, and tailor subsequent interactions based on the identifier of each entity.

[0027] In some embodiments, the exemplary transport orchestration module 118 may determine a set of artifacts associated with each entity. In some embodiments, an artifact may refer to a transportable object capable of providing data to an entity. In some embodiments, the exemplary transport orchestration module 118 may dynamically connect entities based on the determination of artifacts shared by the entities. In some embodiments, the exemplary transport orchestration module 118 utilizes cloud-based functionality to perform entity connections. Cloud-based functionality may refer to a digital network capable of facilitating digital interaction between multiple computing devices. In some embodiments, the exemplary transport orchestration module 118 may utilize the interaction constraint module 124 to dynamically connect entities to determine artifacts shared between two entities.

[0028] In some embodiments, the exemplary transport orchestration module 118 dynamically integrates multiple protocols into an entity's interaction session. In some embodiments, in response to dynamically connecting entities, the exemplary transport orchestration module 118 may integrate multiple protocols into the interaction session. In some embodiments, the multiple protocols may refer to multiple requirements that provide a security level for the interaction session.

[0029] In some embodiments, the exemplary transport orchestration module 118 can verify multiple protocols associated with an interaction session. In some embodiments, the exemplary transport orchestration module 118 can initiate an interaction session between entities based on the verification of multiple protocols. In some embodiments, the exemplary transport orchestration module 118 can automatically modify the interaction session to orchestrate the transport of at least one artifact between entities. In some embodiments, the illustrative procedure can use a trade processing reporting tool to identify multiple trades. In some embodiments, the exemplary transport orchestration module 118 can utilize a rule engine 126 to identify data interruptions in multiple trades to compare the identified multiple trades with multiple requests. In some embodiments, a data interruption can refer to the time of non-action associated with each artifact. In some embodiments, the exemplary transport orchestration module 118 can verify the security of multiple protocols by dynamically calculating values ​​associated with identified artifacts and aggregating the average values ​​associated with the identified artifacts and at least one request.

[0030] In some embodiments, the exemplary transport orchestration module 118 may utilize the interaction constraint module 124 to streamline reports via report enhancement through automation control and system control, and communicate with the trade verification module 128 (not shown) to identify any trade rejections or anomalies for analysis and review. In some embodiments, the regulatory control module 124 may generate multiple system reports to ensure automatic verification of workpiece transport and requests for workpiece transport within a predetermined time period.

[0031] In some embodiments, the exemplary delivery orchestration module 118 may systematically capture at least one predicted delivery of a specific workpiece that fails to match multiple verified protocols. In some embodiments, the exemplary delivery orchestration module 118 may generate a control report based on predicted profit calculations using received workpiece data. In some embodiments, predicted profit calculations may refer to a prediction of the difference between the value of an identified workpiece and the value associated with a request for a received workpiece. In some embodiments, the exemplary delivery orchestration module 118 may automatically and systematically track the age associated with multiple requests for workpiece delivery and report the age associated with each request for each workpiece delivery in a control report. In some embodiments, the illustrative procedure 104 may generate system notifications within the computing device 102 to determine that a request was submitted within a predetermined time period. In some embodiments, the illustrative procedure 104 may utilize an operational console device to generate one or more system notifications within the computing device 102 to determine that a request was submitted within a predetermined time period. In some embodiments, system notifications may refer to a collection of timestamped control reports associated with multiple requests for workpiece delivery, wherein the collection may be converted into a log of notifications that may be referenced for subsequent comparison of the time of each workpiece request.

[0032] In some embodiments, the exemplary transport orchestration module 118 may utilize an Enterprise Integration Service Layer (hereinafter referred to as "EISL") module to simultaneously connect multiple parties using cloud capabilities, multiple abstraction layers, and multiple transformation layers. In some embodiments, the exemplary transport orchestration module 118 may utilize EISL to communicate with a single gateway, API management module, notification hub, data translation layer, and at least one reverse bridging layer. In some embodiments, the EISL module may provide connectivity, messaging, technical services, data services, and data transformation, thereby enabling the entire digital data management platform to operate interactive sessions.

[0033] In some embodiments, the exemplary transport orchestration module 118 can support distributed and legacy mainframe applications, where each application has a predetermined set of protocols for establishing secure connections. In some embodiments, the exemplary transport orchestration module 118 can utilize an enterprise integration service layer module to access multiple data services associated with each entity in an orchestrated manner. In some embodiments, the enterprise integration service layer module can predict whether each entity can meet the requirements without changing the format or protocol used by downstream / upstream applications. In some embodiments, the ability of the enterprise integration service layer module to predict requirement thresholds between entities can reduce the cost and time of performing artifact transport. In some embodiments, the enterprise integration service layer module can provide entities with access to multiple services, such as arbitration services and orchestration services, in a uniform manner.

[0034] In some embodiments, a single data gateway tool associated with the exemplary transport orchestration module 118 may provide a single definition of data across multiple systems and may serve as a gateway for accessing multiple data services in an orchestrated manner. For example, the single data gateway tool may normalize data associated with artifacts to be transported between entities. In some embodiments, the exemplary transport orchestration module 118 may utilize an API management module to leverage API capabilities to address security, monitor and manage traffic within an interaction session, and provide analytics to ensure consistency across multiple API implementations and versions. In some embodiments, a notification hub associated with the exemplary transport orchestration module 118 may identify any associated data types and locations for artifact transport, including discrete artifacts associated with anomalies resulting from multiple data interactions. For example, the notification hub may be a tool associated with a data workstation. In some embodiments, the exemplary transport orchestration module 118 may provide multiple consecutive notifications that inform at least one of multiple entities of modifications to the interaction session and critical data via a message streaming component. In some embodiments, the exemplary transport orchestration module 118 may utilize a data translation layer to digitally track messages and implement multiple data controls associated with the interaction session. In some embodiments, exemplary transport orchestration module 118 may utilize a reverse bridging layer to limit the development and testing required for subsequent modifications to the interactive session by providing similar-for-like datasets and services as currently received.

[0035] In some embodiments, the exemplary delivery orchestration module 118 may utilize a unified management account module to include multiple types of data displayed via multiple data structure sleeves associated with multiple data patterns. In some embodiments, the multiple data structure sleeves may refer to multiple artifacts associated with at least one of multiple accounts, such as data representing investment instruments. In some embodiments, each account may be associated with a specific entity. In some embodiments, each of the multiple data structure sleeves may represent a specific data sleeve within a specific account. In some embodiments, the multiple data structure sleeves may be displayed via a user interface located on a data workstation. In some embodiments, the multiple data structure sleeves may include any or all of the following: electronically traded funds, managed investment strategies, and / or mutual funds that can be delivered within an interactive session. In some embodiments, the multiple data structure sleeves may provide the ability to position and simulate multiple strategies within multiple data patterns of a specific portfolio associated with each entity. In some embodiments, at least one data strategy manager may have a dedicated data structure sleeve within the multiple data structure sleeves associated with a specific account. In some embodiments, multiple investment instruments within a specific portfolio may be stored in an external database and / or server computing device 106. In some embodiments, multiple data structure sets are not user accounts. In some embodiments, multiple data structure sets may have the same characteristics as specific accounts that multiple investment instruments can transfer within a secure interactive session.

[0036] In some embodiments, the exemplary transport orchestration module 118 may utilize a data workstation framework with a front-end framework that provides structure and control for system, page, and component-level customization, thereby providing entities with capabilities ranging from menu navigation to interactive sessions. In some embodiments, the data workstation framework may request a digital single sign-on (hereinafter referred to as "SSO") entry. In some embodiments, the data workstation framework may utilize a screen container with multiple programmable graphical user interface ("GUI") elements to display multiple windows on a user dashboard upon startup. In some embodiments, the data workstation framework may display a masthead menu structure based on multiple user permissions. In some embodiments, the data workstation framework may run multiple data windows simultaneously. In some embodiments, the data workstation framework may provide entities with additional control within an interactive session, such as automatically transmitting signals in response to receiving signals from the entity related to subsequent actions. For example, an entity may initiate the transport of an artifact via the data workstation framework. In some embodiments, the data workstation framework may display market data in the form of a snapshot quote box within at least one window of the user dashboard. In some embodiments, the data workstation framework may dynamically print via a browser printing function, and multiple independent applications may retain their own printing functions where applicable.

[0037] In some embodiments, multiple login authorizations and / or permissions associated with the data workstation framework can be connected to an external data source to establish interactive sessions. In some embodiments, a theme management module can control styles and branding, which can be centrally managed by the data workstation framework and allow for consistent updates across the data ecosystem. In some embodiments, multiple navigations can be configurable, componentized, and permission-based. In some embodiments, the data workstation framework can generate multiple navigations to entities by adjusting configurations within the data workstation framework to hide at least one page. In some embodiments, a context passing module can include a screen that receives and passes relevant context. In some embodiments, the data workstation framework can utilize the context passing module to transmit entity information in the context of each screen associated with the data workstation framework. In some embodiments, the input interface layer can be controlled by the data workstation framework and can be configured via management tools. In some embodiments, the data workstation framework can utilize multiple applications rendered by the input interface layer. In some embodiments, the data workstation framework can provide a responsive design rendered on multiple devices, such as screens with sizes of 1280-1920 pixels.

[0038] In some embodiments, the exemplary transport orchestration module 118 may utilize a tracking layer to track and record multiple details associated with multiple workpiece transports within any interaction session. The exemplary transport orchestration module 118 may calculate trade profit for each trade to manage the profit of each workpiece transport and ensure that the profit remains within a predetermined level. In some embodiments, the exemplary transport orchestration module 118 may integrate with other security modules using its associated security module to provide real-time or near-real-time automated security setup and support for supplier data sources. In some embodiments, the security module may integrate security information associated with specific workpieces and specific entities within an interaction session. In some embodiments, the exemplary transport orchestration module 118 may feed security data to the server computing device 106.

[0039] In some embodiments, the exemplary transport orchestration module 118 may utilize an integrated blotting engine to provide solutions for multiple scenarios associated with predictions of artifact transfers between entities in an interactive session. In some embodiments, the exemplary transport orchestration module 118 may automatically update security data based on the output of the integrated blotting engine associated with a specific artifact transfer notification and direct feeds to the operating system of an external computing device. In some embodiments, the exemplary transport orchestration module 118 may utilize the integrated blotting engine to provide confirmation of available artifacts and completed artifact transfers within the interactive session. In some embodiments, the exemplary transport orchestration module 118 may provide a streamlined root cause analysis of reconciliation failures associated with attempted artifact transfers within the interactive session. In some embodiments, the integrated blotting engine may systematically generate reconciliations; mitigate operational risks or errors through automation; provide real-time status of transfers; and provide automated order routing and / or booking for downstream processing.

[0040] In some embodiments, illustrative procedure 104 may identify at least one workpiece transfer request. In some embodiments, illustrative procedure 104 may input the identified workpiece transfer request into multiple verified interaction sessions that meet at least one predetermined criterion associated with the workpiece. In some embodiments, illustrative procedure 104 may integrate at least two predicted workpiece transfer results into an imprint engine. In some embodiments, illustrative procedure 104 may assign the integrated results associated with the identified workpiece transfer request to a corresponding server computing device 106 associated with a specific entity based on workpiece settlement requirements. In some embodiments, illustrative procedure 104 may perform multiple additional calculations, wherein the additional calculations are automated to mitigate operational risks and / or errors in workpiece transfers within the interaction session. In some embodiments, illustrative procedure 104 may utilize the settlement engine to transmit workpiece transfer information to other entities within the interaction session and generate confirmation notifications associated with the workpiece transfer.

[0041] Figure 2 This is a flowchart 200 illustrating operational steps for automatically modifying an interactive session to orchestrate the transfer of at least one workpiece in a set of workpieces between at least two entities, according to one or more embodiments of the present disclosure.

[0042] In step 202, the illustrative program engine 104 of the computing device 102 identifies a plurality of entities seeking to interact with each other. In some embodiments, the illustrative program engine 104 may identify a plurality of entities seeking to interact with each other. In some embodiments, each of the plurality of entities may refer to at least one of, but is not limited to: an individual, a computing device 102 associated with an individual, a financial institution, and / or a server computing device 106 associated with a company. In some embodiments, the exemplary transport orchestration module 118 may identify a plurality of entities seeking to interact with each other.

[0043] In step 204, the illustrative program engine 104 determines a set of artifacts. In some embodiments, the illustrative program engine 104 may determine at least one artifact in the set of artifacts that can be digitally transferred between computing devices 102. In some embodiments, each artifact may be associated with a specific entity. In some embodiments, an exemplary transport orchestration module 118 may determine a set of artifacts associated with each entity.

[0044] In step 206, the illustrative program engine 104 connects at least two entities. In some embodiments, the illustrative program engine 104 may utilize cloud-based capabilities to dynamically connect entities. In some embodiments, the illustrative program engine 104 may dynamically connect entities based on the determination of artifacts. The determination of artifacts may refer to the number of artifacts shared between the entities attempting to connect. In some embodiments, the exemplary transport orchestration module 118 may utilize cloud-based capabilities to dynamically connect entities based on the determination of artifacts.

[0045] In step 208, the illustrative program engine 104 dynamically integrates multiple protocols into the interaction session. In some embodiments, the illustrative program engine 104 may dynamically integrate multiple protocols in response to a connected entity. In some embodiments, the illustrative program engine 104 may dynamically integrate multiple protocols into an interaction session associated with an entity. In some embodiments, the multiple protocols may refer to multiple requirements that must be completed to initiate a secure interaction session. In some embodiments, the exemplary transport orchestration module 118 may dynamically integrate multiple protocols into an interaction session associated with an entity.

[0046] In step 210, the illustrative program engine 104 verifies multiple protocols. In some embodiments, the illustrative program engine 104 may verify multiple protocols associated with an interaction session. In some embodiments, the illustrative program engine 104 may verify multiple protocols associated with an interaction session to protect the interaction session by utilizing the interaction constraint module 124. In some embodiments, verification of multiple protocols may require that the number of requirements shared between entities meets and / or exceeds a predetermined threshold. In some embodiments, the exemplary transport orchestration module 118 may verify multiple protocols associated with an interaction session.

[0047] In step 212, the illustrative program engine 104 initiates an interaction session between entities. In some embodiments, the illustrative program engine 104 may initiate an interaction session between entities based on multiple protocols. In some embodiments, the illustrative program engine 104 may initiate an interaction session between entities based on a set of artifacts to be transmitted. In some embodiments, the illustrative program engine 104 may initiate an interaction session between entities based on a combination of multiple protocols and a set of artifacts to be transmitted. In some embodiments, the exemplary transmission orchestration module 118 may initiate an interaction session between entities based on a combination of multiple protocols and a set of artifacts to be transmitted.

[0048] In step 214, the illustrative program engine 104 automatically modifies the interaction session. In some embodiments, the illustrative program engine 104 may automatically modify the interaction session to orchestrate the transfer of artifacts. In some embodiments, the illustrative program engine 104 may orchestrate the transfer of artifacts in a set of artifacts between entities. In some embodiments, the transfer of an artifact may be the dynamic result of a verified interaction session initiated to transfer the artifact between entities. In some embodiments, the exemplary transfer orchestration module 118 may automatically modify the interaction session to orchestrate the transfer of artifacts.

[0049] Figure 3A and Figure 3B A schematic diagram illustrating EISL module 300 orchestrating artifact transfers between at least two entities is depicted. In some embodiments, EISL 300 may receive multiple requests from entities willing to participate in a secure interaction session, where the multiple requests may refer to multiple intraday updates 301. EISL 300 may verify the multiple requests to ensure that there is no significant duplication with previous and / or existing requests within the multiple requests. In some embodiments, EISL 300 may transmit multiple update requests for existing services. In some embodiments, EISL 300 may tidy up logic for any derived attributes as needed to construct multiple derivations and provide the attributes required by the multiple derivations as part of the requirements. In some embodiments, EISL 300 may review multiple artifacts. In some embodiments, EISL 300 may perform any additional mappings that are feasible. In some embodiments, EISL 300 may publish multiple issues and / or data gaps to multiple downstream users.

[0050] In some embodiments, the Enterprise Integration Service Layer Module 300 can integrate with internal and external applications in the current and future scenarios. In some embodiments, the Enterprise Integration Service Layer Module 300 can support distributed and legacy mainframe applications. In some embodiments, the Enterprise Integration Service Layer Module 300 can access multiple data services in an orchestrated manner. In some embodiments, the Enterprise Integration Service Layer Module 300 can meet requirements without altering the format or protocol of verified interaction sessions.

[0051] In some embodiments, a single data gateway tool 302 can provide a single data definition across multiple systems and can be used as a gateway to access multiple data services 303 in an orchestrated manner. In some embodiments, the multiple data services 303 may include, but are not limited to: resting time service 303a, message quality 303b, network data mover 303c, file transfer protocol 303d, and Kafka service 303e, wherein Kafka service 303e may refer to a service capable of building applications and data pipelines that adapt to real-time data flows. In some embodiments, the API management module 304 via the aggregation layer 305 can leverage API capabilities to address security, monitor and manage traffic, provide analytics, and ensure consistency among multiple API implementations and versions. In some embodiments, the aggregation layer 305 can leverage the API management module 304 to address security via the caching layer 307, wherein the caching layer 307 communicates with the security instrument layer 309a, client, account and relationship layer 309b, product master layer 309c, artifact request layer 309d, and settlement layer 309e. In some embodiments, aggregation layer 305 may utilize API management module 304 to provide analytics via data aggregation layer 311, wherein data aggregation layer 311 communicates with performance layer 309f, billing layer 309g, cash treasury management layer 309h, and corporate action layer 309i. In some embodiments, API management module 304 may refer to the core bookkeeping system associated with EISL 300. In some embodiments, notification hub 306 may identify all associated data types and locations of events, including discrete artifacts associated with anomalies resulting from multiple data interactions. In some embodiments, enterprise integration service layer module 300 may provide multiple consecutive notifications that notify at least one of multiple entities of changes to critical data via artifact delivery message streaming component 308. In some embodiments, data translation layer 310 may digitally track messages and implement multiple data controls. In some embodiments, data translation layer 310 may utilize caching layer 307 and extract transform loading processing layer 313 to digitally track messages and implement data controls. In some embodiments, the reverse bridging layer 312 can limit the development and testing required by the retained application by providing similar datasets and services as currently received. In some embodiments, the output of the notification hub 306 can flow into the abstraction layer 314, which can also communicate with multiple computing devices, wherein the multiple computing devices may refer to the client core system 315.

[0052] Figure 4A flowchart 400 depicts the operational steps of an interactive constraint module 124, which streamlines reporting via automated control and system control through report enhancement and communicates with an exemplary transport orchestration module 118. In some embodiments, multiple workpiece transport-related inputs 402 are fed into the interactive constraint module 124. In some embodiments, the interactive constraint module 400 may utilize multiple trade-related inputs 402 to compare workpiece transports associated with the inputs with any transports associated with the interactive session. In some embodiments, the interactive constraint module 124 may communicate with an allocation recon tool 404, which may be able to compare multiple requests to identify multiple data interruptions. In some embodiments, the allocation recon tool 404 may communicate with a rules engine 126. In some embodiments, the rules engine 126 may identify multiple data interruptions in multiple workpiece transports to compare the identified multiple transports with multiple requests. In some embodiments, any results from the rules engine 126 may be stored within a server computing device 106. In some embodiments, the interactive constraint module 124 may systematically capture any workpiece transports that are not processed between the allocation recon tool 404 and the rules engine 126. In some embodiments, the interaction constraint module 124 may automatically track the age associated with each of a plurality of requests within the request store 408. In some embodiments, the request store 408 may refer to a data warehouse. In some embodiments, the interaction constraint module 124 may generate multiple system notifications to ensure that the plurality of requests are submitted within a predetermined time period. In some embodiments, the predetermined time period may refer to a 10-day requirement associated with the plurality of requests. In some embodiments, the regulator 406 may verify the timestamp associated with each system notification generated by the interaction constraint module 124. In response to verification via the regulator 406, the interaction constraint module 124 may transmit the plurality of verified notifications to the user via a notification hub 306 for use by a subsequent post-submission control 410, wherein the notification hub 306 may communicate with the remote desktop service 411 and the enterprise data warehouse 412 prior to transmitting the verified notifications to the user for use by the post-submission control 410. In some embodiments, the post-submission control 410 may modify the plurality of artifact requests associated with the interaction constraint module 124.

[0053] Figure 5A block diagram of an exemplary computer-based system / platform 500 according to one or more embodiments of the present disclosure is depicted. However, practicing one or more embodiments may not require all of these components, and the arrangement and type of components may be varied without departing from the spirit or scope of the various embodiments of the present disclosure. In some embodiments, the exemplary inventive computing device and / or exemplary inventive computing components of the exemplary computer-based system / platform 500 may be configured to automatically modify an interaction session to orchestrate the transfer of at least one artifact from a set of artifacts between at least two entities, as detailed herein.

[0054] In some embodiments, the exemplary computer-based system / platform 500 may be based on a scalable computer and / or network architecture that incorporates various strategies for evaluating data, caching, searching, and / or database connection pooling. An example of a scalable architecture is one capable of operating multiple servers. In some embodiments, the exemplary inventive computing devices and / or exemplary inventive computing components of the exemplary computer-based system / platform 500 may be configured to automatically utilize at least one machine learning model described herein to remotely execute instructions associated with the exemplary transport orchestration module 118 of this disclosure.

[0055] In some embodiments, reference Figure 5Members 502-504 (e.g., clients) of the exemplary computer-based system / platform 500 may include virtually any computing device capable of automatically modifying an interactive session using the exemplary transport orchestration module 118 to orchestrate the transport of at least one artifact from a set of artifacts, such as those to and from another computing device (e.g., servers 506 and 507) and between at least two entities via a network (e.g., cloud network 109) (such as network 505) and between themselves. In some embodiments, member devices 502-504 may be smartphones, personal computers, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs, etc. In some embodiments, one or more member devices within member devices 502-504 may include computing devices connected using wireless communication media (such as cellular phones, smartphones, pagers, walkie-talkies, radio frequency (RF) devices, infrared (IR) devices, CBs, integrated devices combining one or more of the aforementioned devices, or virtually any mobile computing device, etc.). In some embodiments, one or more member devices within member devices 502-504 may be devices capable of connecting using wired or wireless communication media (such as PDAs, POCKETPCs, wearable computers, laptops, tablets, desktop computers, netbooks, video game devices, pagers, smartphones, ultra-mobile personal computers (UMPCs), and / or any other device equipped to communicate via wired and / or wireless communication media (e.g., NFC, RFID, NB-IoT, 3G, 4G, 5G, GSM, GPRS, WiFi, WiMax, CDMA, satellite, ZigBee, etc.). In some embodiments, one or more member devices within member devices 502-504 may include devices capable of launching one or more applications, such as internet browsers, mobile applications, voice calls, video games, video conferencing, and email. In some embodiments, one or more member devices within member devices 502-404 may be configured to receive and send web pages, etc. In some embodiments, the exemplary transmission orchestration module 118 of this disclosure can be configured to collect market input, modify the transformed uniform data state input data based on an established baseline to match market output data, and employ virtually any web-based language, including but not limited to Standard Generalized Markup Language (SMGL), such as Hypertext Markup Language (HTML), Wireless Application Protocol (WAP), and Handheld Device Markup Language (HDML), such as Wireless Markup Language (WML), WMLScript, XML, JavaScript, etc. In some embodiments, member devices within member devices 502-504 can be specifically programmed using Java, .Net, QT, C, C++, and / or other suitable programming languages.In some embodiments, one or more member devices among member devices 502-504 may be specifically programmed to include or execute applications to perform various possible tasks, such as, but not limited to, messaging functions, browsing, searching, playing, streaming, or displaying content in various forms, including locally stored or uploaded messages, images and / or videos and / or games.

[0056] In some embodiments, exemplary network 505 may provide network access, data transmission, and / or other services to any computing device coupled thereto. In some embodiments, exemplary network 505 may include and implement at least one dedicated network architecture, which may be at least partially based on one or more standards defined by, for example, but not limited to, the Global System for Mobile Communications (GSM) Association, the Internet Engineering Task Force (IETF), and the Global Microwave Access Interoperability (WiMAX) Forum. In some embodiments, exemplary network 505 may implement one or more of the GSM architecture, the General Packet Radio Service (GPRS) architecture, the Universal Mobile Telecommunications System (UMTS) architecture, and UMTS evolution known as Long Term Evolution (LTE). In some embodiments, exemplary network 505 may include and implement the WiMAX architecture defined by the WiMAX Forum as an alternative or in combination with one or more of the foregoing. In some embodiments, and optionally, in conjunction with any embodiments described above or below, exemplary network 505 may also include at least one of, for example, a Local Area Network (LAN), a Wide Area Network (WAN), the Internet, a Virtual LAN (VLAN), an Enterprise LAN, a Layer 3 Virtual Private Network (VPN), an Enterprise IP Network, or any combination thereof. In some embodiments, and optionally, in conjunction with any of the embodiments described above or below, at least one computer network communication via exemplary network 505 may be transmitted at least in part based on one of a plurality of communication modes, such as, but not limited to: NFC, RFID, Narrowband Internet of Things (NB-IoT), ZigBee, 3G, 4G, 5G, GSM, GPRS, WiFi, WiMax, CDMA, satellite, and any combination thereof. In some embodiments, exemplary network 405 may also include mass storage devices, such as network-attached storage (NAS), storage area network (SAN), content delivery network (CDN), or other forms of computer or machine-readable media.

[0057] In some embodiments, exemplary server 506 or exemplary server 507 may be a web server (or a series of servers) running a network operating system, examples of which may include, but are not limited to, Microsoft Windows Server, Novell NetWare, or Linux. In some embodiments, exemplary server 506 or exemplary server 507 may be used to and / or provide cloud and / or network computing. Although not explicitly stated in the text... Figure 5 As shown, but in some embodiments, exemplary server 506 or exemplary server 507 may have connections to external systems (e.g., email, SMS messaging, text messaging, advertising content providers, etc.). Any feature of exemplary server 506 may also be implemented in exemplary server 507, and vice versa.

[0058] In some embodiments, one or more of the exemplary servers 506 and 507 may be specifically programmed to perform, in non-limiting examples, as an authentication server, search server, email server, social networking service server, SMS server, IM server, MMS server, exchange server, photo sharing service server, advertising delivery server, financial / banking related service server, travel service server, or any similar suitable service-based server for users of member computing devices 501-504.

[0059] In some embodiments, optionally, in combination with any of the embodiments described above or below, such as one or more illustrative computing member devices 502-504, exemplary server 506 and / or exemplary server 507, may include specially programmed software modules that can be configured to automatically modify interactive sessions to orchestrate the transfer of at least one artifact from a set of artifacts between at least two entities.

[0060] Figure 6A block diagram of another exemplary computer-based system / platform 600 according to one or more embodiments of the present disclosure is depicted. However, practicing one or more embodiments may not require all of these components, and the arrangement and type of components may be varied without departing from the spirit or scope of the various embodiments of the present disclosure. In some embodiments, each of the illustrated member computing devices 602a, 602b to 602n includes at least a computer-readable medium, such as random access memory (RAM) 608 coupled to processor 610 or flash memory. In some embodiments, processor 610 may execute computer-executable program instructions stored in memory 608. In some embodiments, processor 610 may include a microprocessor, ASIC, and / or state machine. In some embodiments, processor 610 may include or be able to communicate with a medium, such as a computer-readable medium storing instructions that, when executed by processor 610, may cause processor 610 to perform one or more steps described herein. In some embodiments, examples of computer-readable media may include, but are not limited to, electronic, optical, magnetic, or other storage or transmission devices capable of providing computer-readable instructions to a processor such as processor 610 of client 602a. In some embodiments, other examples of suitable media may include, but are not limited to, floppy disks, CD-ROMs, DVDs, magnetic disks, memory chips, ROMs, RAMs, ASICs, configured processors, all optical media, all magnetic tapes or other magnetic media, or any other media from which a computer processor can read instructions. Furthermore, various other forms of computer-readable media may transmit or carry instructions wired and wirelessly to or from computers (including routers), private or public networks, or other transmission devices or channels. In some embodiments, instructions may include code from any computer programming language, including, for example, C, C++, Visual Basic, Java, Python, Perl, JavaScript, etc.

[0061] In some embodiments, member computing devices 602a to 602n may further include multiple external or internal devices, such as a mouse, CD-ROM, DVD, physical or virtual keyboard, display, speaker, or other input or output devices. In some embodiments, examples of member computing devices 602a to 602n (e.g., clients) may be any type of processor-based platform connected to network 606, such as, but not limited to, personal computers, digital assistants, personal digital assistants, smartphones, pagers, digital tablets, laptops, internet-connected appliances, and other processor-based devices. In some embodiments, member computing devices 602a to 602n may be specifically programmed with one or more applications according to one or more principles / methods detailed herein. In some embodiments, member computing devices 602a to 602n may run on any operating system capable of supporting browsers or browser-enabled applications (such as Microsoft...). TM Windows TM Running on Linux. In some embodiments, the illustrated member computing devices 602a to 602n may include, for example, executing browser applications (such as Microsoft's Internet Explorer). TM Apple Computer's Safari TM Personal computers running Mozilla Firefox and / or Opera. In some embodiments, through member computing client devices 602a to 602n, users 612a to 612n can communicate with each other and / or with other systems and / or devices coupled to network 606 via exemplary network 606. Figure 6 As shown, exemplary server devices 604 and 613 may also be coupled to network 606. Exemplary server device 604 may include processor 605 that is coupled to memory of storage network engine 617. Exemplary server device 613 may include processor 614 that is coupled to memory 616 of storage network engine. In some embodiments, one or more member computing devices 602a to 602n may be mobile clients. Figure 6 As shown, network 606 can be coupled to one or more cloud computing / architectures 625. One or more cloud computing / architectures 625 can include cloud services coupled to cloud infrastructure and cloud platforms, wherein the cloud platform can be coupled to cloud storage.

[0062] In some embodiments, at least one of the exemplary databases 607 and 615 can be any type of database, including databases managed by a database management system (DBMS). In some embodiments, the database managed by the exemplary DBMS can be specifically programmed to control the organization, storage, management, and / or retrieval of data in the respective database. In some embodiments, the database managed by the exemplary DBMS can be specifically programmed to provide the ability to query, back up and replicate, enforce rules, provide security, perform computations, perform change and access logging, and / or automate optimizations. In some embodiments, the database managed by the exemplary DBMS can be selected from Oracle Database, IBM DB2, Adaptive Server Enterprise, FileMaker, Microsoft Access, Microsoft SQL Server, MySQL, PostgreSQL, and NoSQL implementations. In some embodiments, the database managed by the exemplary DBMS can be specifically programmed to define each respective schema of each database in the exemplary DBMS according to a specific database model of this disclosure, which may include a hierarchical model, a network model, a relational model, an object model, or some other suitable organization that can produce one or more applicable data structures, which may include fields, records, files, and / or objects. In some embodiments, the database managed by the exemplary DBMS can be specifically programmed to include metadata about the stored data.

[0063] Figure 7 and 8 The illustrations are schematic diagrams of exemplary implementations of cloud computing / architecture(s) in which exemplary inventive computer-based systems / platforms, exemplary inventive computer-based devices and / or exemplary inventive computer-based components of this disclosure can be specifically configured to operate. Figure 7 The diagram shows... Figure 6 The extended view of (one or more) cloud computing / architecture 625 found. Figure 8 The illustration shows that an exemplary computer-based component of this disclosure can be specifically configured to operate as a source database 804 in a cloud computing / architecture 625, wherein the source database 804 can be a web browser, mobile application, thin client, and terminal emulator. Figure 8 In this disclosure, the exemplary inventive computer-based systems / platforms, exemplary inventive computer-based devices, and / or exemplary inventive computer-based components may be specifically configured to operate in cloud computing / architectures such as, but not limited to, Infrastructure as a Service (IaaS) 810, Platform as a Service (PaaS) 808, and / or Software as a Service (SaaS) 806.

[0064] In some embodiments, optionally, in conjunction with any of the embodiments described above or below, the exemplary trained neural network model may specify the neural network by at least a neural network topology, a series of activation functions, and connection weights. For example, the topology of the neural network may include the configuration of the nodes of the neural network and the connections between these nodes. In some embodiments, optionally, in conjunction with any of the embodiments described above or below, the exemplary trained neural network model may also be specified to include other parameters, including but not limited to bias values / functions and / or aggregation functions. For example, the activation function of a node may be a step function, a sine function, a continuous or piecewise linear function, a sigmoid function, a hyperbolic tangent function, or other types of mathematical functions representing a threshold at which a node is activated. In some embodiments, optionally, in conjunction with any of the embodiments described above or below, the exemplary aggregation function may be a mathematical function that combines an input signal with nodes (e.g., summation, product, etc.). In some embodiments, optionally, in conjunction with any of the embodiments described above or below, the output of the exemplary aggregation function may be used as input to the exemplary activation function. In some embodiments, optionally, in conjunction with any of the embodiments described above or below, bias can be a constant value or function that can be used by aggregation functions and / or activation functions to make a node more or less activated.

[0065] The material disclosed herein may be implemented as software, firmware, or a combination of both, or as instructions stored on a machine-readable medium that can be read and executed by one or more processors. A machine-readable medium may include any medium and / or mechanism for storing or transmitting information in a machine-readable form (e.g., a computing device). For example, a machine-readable medium may include read-only memory (ROM), random access memory (RAM); disk storage media; optical storage media; knowledge corpora; stored audio recordings; flash memory devices; electrical, optical, acoustic, or other forms of propagation signals (e.g., carrier waves, infrared signals, digital signals, etc.) and others.

[0066] As used herein, the terms “computer engine” and “engine” identify at least one software component and / or a combination of at least one software component and at least one hardware component that is designed / programmed / configured to manage / control other software and / or hardware components (such as libraries, software development kits (SDKs), objects, etc.).

[0067] Examples of hardware components may include processors, microprocessors, circuits, circuit elements (e.g., transistors, resistors, capacitors, inductors, etc.), integrated circuits, application-specific integrated circuits (ASICs), programmable logic devices (PLDs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs), logic gates, registers, semiconductor devices, chips, microchips, chipsets, etc. In some embodiments, one or more processors may be implemented as complex instruction set computer (CISC) or reduced instruction set computer (RISC) processors; x86 instruction set compatible processors, multi-core processors, or any other microprocessor or central processing unit (CPU). In various implementations, one or more processors may be one or more dual-core processors, one or more dual-core mobile processors, etc.

[0068] As used herein, computer-related systems, computer systems, and systems include any combination of hardware and software. Examples of software may include software components, operating system software, middleware, firmware, software modules, routines, subroutines, functions, methods, procedures, software interfaces, application programming interfaces (APIs), instruction sets, computer code, computer code segments, words, values, symbols, or any combination thereof. Determining whether an embodiment is implemented using hardware and / or software components can vary depending on a variety of factors, such as desired computing speed, power levels, thermal tolerance, processing cycle budget, input data rate, output data rate, memory resources, data bus speed, and other design or performance constraints.

[0069] One or more aspects of at least one embodiment can be implemented by representative instructions stored on a machine-readable medium, representing various logic within a processor, which, when read by a machine, cause machine-manufacturing logic to perform the techniques described herein. Such a representation (referred to as an "IP core") can be stored on a tangible machine-readable medium and supplied to various customers or manufacturing plants for loading into manufacturing machines that produce logic or processors. It is worth noting that the various embodiments described herein can, of course, be implemented using any suitable hardware and / or computational software language (e.g., C++, Objective-C, Swift, Java, JavaScript, Python, Perl, QT, etc.).

[0070] In some embodiments, one or more of the exemplary inventive computer-based systems / platforms, exemplary inventive computer-based devices, and / or exemplary inventive computer-based components of this disclosure may be partially or wholly included or incorporated into at least one personal computer (PC), laptop computer, ultra-laptop computer, tablet computer, touchpad, portable computer, handheld computer, PDA, personal digital assistant (PDA), cellular phone, cellular phone / PDA combination, television, smart device (e.g., smartphone, smart tablet, or smart TV), mobile internet device (MID), messaging device, data communication device, etc.

[0071] As used herein, the term "server" should be understood to refer to a point of service that provides processing, database, and communication facilities. For example, but not limited to, the term "server" can refer to a single physical processor associated with communication, data storage, and database facilities, or it can refer to a networked or clustered complex of processors and associated network and storage devices, as well as the operating software and one or more database systems and application software that support the services provided by the server. In some embodiments, a server may store transactions and dynamically trained machine learning models. A cloud server is an example.

[0072] In some embodiments, as detailed herein, one or more of the exemplary inventive computer-based systems / platforms, exemplary inventive computer-based devices, and / or exemplary inventive computer-based components of this disclosure may acquire, manipulate, transmit, store, transform, generate, and / or output (e.g., from within and / or outside a particular application) any digital object and / or data unit, which may be in any suitable form, such as, but not limited to, files, contacts, tasks, emails, social media posts, maps, entire applications (e.g., calculators), etc. In some embodiments, as detailed herein, one or more of the exemplary inventive computer-based systems / platforms, exemplary inventive computer-based devices, and / or exemplary inventive computer-based components of this disclosure may be implemented across one or more of various computer platforms, such as, but not limited to: (1) FreeBSD™, NetBSD™, OpenBSD™; (2) Linux™; (3) Microsoft Windows™; (4) OSX (MacOS)™; (5) MacOS 11™; (6) Solaris™; (7) Android™; (8) iOS™; (9) Embedded Linux™; (10) Tizen™; (11) WebOS™; (12) IBM i™; (13) IBM AIX™; (14) Wireless Binary Runtime Environment (BREW)™; (15) Cocoa (API)™; (16) Cocoa Touch™; (17) Java Platform™; (18) JavaFX™; (19) JavaFX Mobile;™; (20) Microsoft DirectX™; (21) .NET Framework™; (22) Silverlight™; (23) Open Web Platform™; (24) Oracle Database™; (25) Qt™; (26) Eclipse Rich Client Platform™; (27) SAP NetWeaver™; (28) Smartface™; and / or (29) Windows Runtime™.

[0073] In some embodiments, the exemplary inventive computer-based systems / platforms, exemplary inventive computer-based devices, and / or exemplary inventive computer-based components of this disclosure may be configured to utilize hardwired circuitry systems that may be used in place of or in combination with software instructions to achieve features consistent with the principles of this disclosure. Therefore, implementations consistent with the principles of this disclosure are not limited to any particular combination of hardware circuitry systems and software. For example, various embodiments may be implemented as software components in a variety of different ways, such as, but not limited to, standalone software packages, combinations of software packages, or they may be software packages incorporated as “tools” into a larger software product.

[0074] For example, exemplary software specifically programmed according to one or more principles of this disclosure may be downloaded from a network (e.g., a website), as a standalone product, or as a plug-in package installed in an existing software application. For example, exemplary software specifically programmed according to one or more principles of this disclosure may also be used as a client-server software application or a web-enabled software application. For example, exemplary software specifically programmed according to one or more principles of this disclosure may also be implemented as a software package installed on a hardware device. In at least one embodiment, the exemplary spam prevention module 118 of this disclosure utilizing at least one machine learning model described herein may be referred to as exemplary software.

[0075] In some embodiments, the exemplary inventive computer-based systems / platforms, exemplary inventive computer-based devices, and / or exemplary inventive computer-based components of this disclosure can be configured to handle a large number of concurrent tests against a software agent, which may be, but are not limited to, at least 100 (e.g., but not limited to 100-999), at least 1,000 (e.g., but not limited to 1,000-9,999), at least 10,000 (e.g., but not limited to 10,000-99,999), or at least 100,000 (e.g., but not limited to 100,000-99,999). 000-999,999), at least 1,000,000 (e.g., but not limited to 1,000,000-9,999,999), at least 10,000,000 (e.g., but not limited to 10,000,000-99,999,999), at least 100,000,000 (e.g., but not limited to 100,000,000-999,999,999), at least 1,000,000,000 (e.g., but not limited to 1,000,000,000-999,999,999,999), etc.

[0076] In some embodiments, the exemplary inventive computer-based systems / platforms, exemplary inventive computer-based devices, and / or exemplary inventive computer-based components of this disclosure can be configured to output to different, specially programmed graphical user interface implementations of this disclosure (e.g., desktop, web applications, etc.). In various implementations of this disclosure, the final output can be displayed on a display screen, which can be, but is not limited to, a computer screen, a mobile device screen, etc. In various implementations, the display can be a holographic display. In various implementations, the display can be a transparent surface capable of receiving visual projections. Such projections can convey various forms of information, images, and / or objects. For example, such projections can be visual overlays in mobile augmented reality (MAR) applications.

[0077] As used herein, the term "mobile electronic device" can refer to any portable electronic device that may or may not have location tracking capabilities (e.g., MAC address, Internet Protocol (IP) address, etc.). For example, a mobile electronic device can include, but is not limited to, a mobile phone, a personal digital assistant (PDA), a Blackberry™, a pager, a smartphone, or any other reasonable mobile electronic device.

[0078] While one or more embodiments of this disclosure have been described, it should be understood that these embodiments are illustrative only and not restrictive, and many modifications will become apparent to those skilled in the art. Various embodiments of the inventive methods, inventive systems / platforms, and inventive devices described herein can be used in any combination thereof. Furthermore, the steps can be performed in any desired order (and any desired steps can be added and / or eliminated).

Claims

1. A computer-implemented method, comprising: Multiple entities seeking to interact with each other are identified by at least one processor; The at least one processor determines the set of workpieces associated with each of the plurality of entities; The at least one processor utilizes cloud-based capabilities to dynamically connect the at least two entities based on a determination of the set of artifacts shared between the at least two entities; In response to connecting the at least two entities, the at least one processor dynamically integrates multiple protocols into an interaction session associated with the at least two entities. The plurality of protocols associated with the interaction session include connection requests received from each of the plurality of entities; The at least one processor verifies the plurality of protocols associated with the interaction session. Verifying the multiple protocols includes ensuring that the number of sharing requests from the multiple entities exceeds a predetermined threshold; The at least one processor initiates an interactive session between at least two entities based on the plurality of protocols and the set of artifacts; as well as The interaction session is automatically modified by the at least one processor to orchestrate the transfer of at least one workpiece from the workpiece set between the at least two entities.

2. The method of claim 1, wherein each entity is a server computing device associated with a financial institution.

3. The method of claim 1, wherein the workpiece includes digitally transmittable data items.

4. The method of claim 1, wherein the determination of the set of workpieces includes using an interaction constraint module to analyze any shared workpieces between the at least two entities.

5. The method of claim 1, wherein the cloud-based functionality includes a digital network capable of facilitating digital interaction between multiple computing devices.

6. The method of claim 1, wherein the dynamic integration of the plurality of protocols includes using a rule engine to identify data interruptions in the set of workpieces for subsequent comparison with the plurality of workpiece requests.

7. The method of claim 1, wherein the interaction session includes a secure digital marketplace that allows entities to exchange data with artifacts.

8. The method of claim 1, wherein automatic modification of the interactive session includes reducing one or more authentication steps required for orchestrating the transfer of artifacts between the at least two entities.

9. The method of claim 1, further comprising using an enterprise integration service layer module to predict the probability associated with the successful transfer of a particular artifact between the at least two entities.

10. The method of claim 9, wherein the enterprise integration service layer comprises: Single gateway module; API management module; Data workstation framework; Data translation layer; as well as At least one reverse bridging layer.

11. The method of claim 9, wherein the enterprise integration service layer predicts the likelihood of successful delivery by dynamically predicting that each entity can meet the requirements without modifying the plurality of protocols used for subsequent artifact delivery.

12. The method of claim 11, wherein dynamically predicting that each entity can meet the requirements without modification comprises: A rules engine is used to organize any transport information associated with any derived attributes for a specific artifact and entity to construct multiple derivations and provide the attributes required by the multiple derivations as part of the requirements associated with the multiple protocols.

13. The method of claim 1, further comprising: Systematically capture at least one predicted workpiece delivery that fails to match multiple verified protocols for a specific workpiece; as well as Generate multiple system reports associated with multiple predicted workpiece deliveries and requests for workpiece deliveries that are automatically verified within a predetermined time period.

14. The method of claim 1, further comprising: At least one machine learning module is used to analyze a specific set of data associated with each entity, wherein the specific set of data includes protocol preferences and predetermined artifact delivery rules.

15. The method of claim 1, further comprising: The interactive constraint module is used to receive inputs related to the transmission of multiple workpieces. The allocation reconnaissance tool is used to compare the multiple workpiece transfers with multiple transfer-related inputs to determine additional inputs and common workpiece transfers associated with the interaction session; A machine learning module is used to identify multiple data interruptions associated with the multiple workpiece transfers and the comparison of the multiple transfer-related inputs; Automatically track the age associated with each request for the transfer of the multiple workpieces within an external database; as well as Multiple system notifications are generated to ensure that the multiple workpiece transfers are submitted within a predetermined time period.

16. The method of claim 1, further comprising using an interaction constraint module to initiate a secure interaction session between the at least two entities.

17. The method of claim 1, further comprising using a data workstation framework to display notifications associated with artifact transfers within the interactive session.

18. A computer-implemented method, comprising: Multiple entities seeking to interact with each other are identified by at least one processor; The at least one processor determines the set of workpieces associated with each of the plurality of entities; The at least one processor utilizes cloud-based capabilities to dynamically connect the at least two entities based on the determination of the set of artifacts shared between the at least two entities; In response to connecting the at least two entities, the at least one processor dynamically integrates multiple protocols into an interaction session associated with the at least two entities. The plurality of protocols associated with the interaction session include connection requests received from each of the plurality of entities; The at least one processor uses at least one machine learning module to analyze specific sets of data associated with each entity. The specific data set mentioned above contains protocol preferences and predefined artifact delivery rules associated with each entity; The at least one processor verifies the plurality of protocols associated with the interaction session. Verifying the multiple protocols includes ensuring that the number of sharing requests from the multiple entities exceeds a predetermined threshold; The at least one processor initiates an interactive session between at least two entities based on the plurality of protocols and the set of artifacts; The at least one processor uses the Enterprise Integration Service Layer module to predict the probability of a successful transfer of a specific artifact between the at least two entities. The interaction session is automatically modified by the at least one processor to orchestrate the transfer of at least one workpiece from the workpiece set between the at least two entities; as well as Systematically capture at least one predicted workpiece delivery that fails to match multiple verified protocols for a specific workpiece; as well as Generate multiple system reports associated with multiple predicted workpiece deliveries and requests for workpiece deliveries that are automatically verified within a predetermined time period.

19. The method of claim 18, further comprising: The interactive constraint module is used to receive relevant inputs from multiple workpieces. The allocation reconnaissance tool is used to compare the multiple workpiece transfers with multiple transfer-related inputs to determine additional inputs and common workpiece transfers associated with the interaction session; A machine learning module is used to identify multiple data interruptions associated with the multiple workpiece transfers and the comparison of the multiple transfer-related inputs; Automatically track the age associated with each request for the transfer of the multiple workpieces within an external database; as well as Multiple system notifications are generated to ensure that the multiple workpiece transfers are submitted within a predetermined time period.

20. A system comprising: Non-transitory computer memory, wherein the non-transitory computer memory stores software instructions; At least one processor of a computing device associated with an entity; Wherein, when the at least one processor executes the software instructions, the computing device is programmed to: Identify multiple entities that seek to interact with each other; Determine the set of workpieces associated with each of the plurality of entities; By leveraging cloud-based capabilities, the at least two entities are dynamically connected based on the determination of the set of workpieces shared between them. In response to connecting the at least two entities, multiple protocols are dynamically integrated into the interaction session associated with the at least two entities. The plurality of protocols associated with the interaction session include connection requests received from each of the plurality of entities; Verify the multiple protocols associated with the interaction session. Verifying the multiple protocols includes ensuring that the number of sharing requests from the multiple entities exceeds a predetermined threshold; Initiate an interactive session between at least two entities based on the multiple protocols and the set of artifacts; and The interaction session is automatically modified to orchestrate the transfer of at least one workpiece from the workpiece set between the at least two entities.

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