Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/3/2025 has been entered.
DETAILED ACTION
The following Non-Final office action is in response to application 18/300,861 filed on 12/3/2025.
Status of Claims
Claims 1-10 and 12-21 are currently pending and have been rejected as follows.
Response to Amendments
Rejections under 35 USC 101 are maintained and updated below. New rejections under 35 USC 103 are issued below.
Response to Arguments
Applicant’s 35 USC 101 arguments and amendments have been fully considered but they are not persuasive to overcome the rejection.
Applicant argues on p. 12-13 that amended claim 1 does not recite an abstract idea because amended claim 1 specifically recites "processing … the user configuration of business logic into code representative of a rule…; compiling… the code into the rule without requiring software development of the rule by a user; [and] deploying the rule to a rules repository," alleging this is not merely a method of organizing human activity, since the quoted claim language recites a particular and technical process for automated generation of code based on a configuration received via a user interface without requiring user software development. Applicant further states, claim 1 as amended recites an inherently computer-based method of operation and not a method of organization human activity because the MPEP states that [c]ommercial interactions' or 'legal interactions' include agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors, and business relations and the generation of code and the compiling of that code into a rule without requiring software development by a user is inherently a computer-based process as such a process is tied to the operation of the computing system in generating code and compiling that code into a rule, and is not directed towards "sales activities” or other forms of commercial interactions.Examiner respectfully disagrees. The claimed steps aim to automate the filtering of customers by contact restrictions to ensure compliance with regulatory requirements and customer preferences. The inclusion of "processing … the user configuration of business logic into code representative of a rule…; compiling… the code into the rule without requiring software development of the rule by a user; [and] deploying the rule to a rules repository," does not preclude the claim from being directed to a certain method of organizing human activity because the focus of the claim is still to automate the filtering of customers by contact restrictions and outputting reports indicating which rules apply for a customer and a list of customers permitted to be contacted for a marketing campaign. The amended claim language functionally implements the recited abstract idea and is considered further at Step 2A, Prong 2.
Applicant argues on p. 13 that amended claim 1 is still directed to eligible subject matter based on the analysis at Step 2A Prong 2 because amended claim 1 as a whole integrates the alleged abstract idea into a practical application, stating claim 1 recites a method for generating and compiling code based on user configuration via a user interface and without requiring software development by the user. In this way, claim 1 provides a solution to a problem that is rooted in the technology of computer-based management of rules, which conventionally require software development expertise to create applicable rules or filters. Claim 1 provides a technical improvement by enabling the creation of computer-based rules without requiring specialized knowledge of a software team to implement the computer-based rules required to process data and instead enable low code/no code generation of the computer-based rules based on user-configuration of abstracted business logic.Examiner respectfully disagrees. The claim does not recite the technical detail required to demonstrate the asserted technical improvement. The claim merely recites the functional result “without requiring software development of the rule by a user.”
Applicant argues on p. 13 that amended claim 1 is still directed to eligible subject matter based on the analysis at Step 2B because amended claim 1 provides a specific improvement to the automated generation of code without requiring software development by a user. As described in Applicant's specification, "[d]igital customer consent engine 104 enables a user of marketing devices 108 to modify the business logic without requiring a software development team to recode a program…” When read in light of Applicant's specification, amended claim 1 provides a specific improvement to the generation of rules by enabling the automated generation and compiling of code into rules without requiring software development by a user. As a result, significant advantages may be derived from the method of claim 1. Claim 1, as amended, therefore provides significantly more than mere methods of organizing human activity.Examiner respectfully disagrees. Generating and compiling code, as functionally claimed and supported in specification paragraphs [0050]-[0056], are well-understood, routine, and conventional. The claims and specification do not recite the technical detail necessary to support a technical improvement or significantly more than the judicial exception.
Response to Arguments
Applicant’s prior art arguments and amendments have been fully considered but they are not persuasive.
Applicant argues on p. 14-15 that Cyr in view of Sheldon do not disclose the amended features of “receiving, by a computing system, a user configuration of business logic; processing, by the computing system, the user configuration of business logic into code representative of a rule to identify one or more customer contact restrictions from customer data;…” Examiner respectfully disagrees and has mapped the amended features to Cyr.Regarding receiving, by a computing system, a user configuration of business logic, see Cyr [0115] “the administrative interface service/proxy 116 may be to provide a programmatic interface for rules, parameters, AI queries, campaign templates … to be created and saved for downstream use … All of this input may be facilitated via an administrative interface governed and hosted by the administrative interface service/proxy 116;” [0142] “the practitioner may create … using an administrative UI” note the programmatic interface for receiving input of business logic.
Regarding processing, by the computing system, the user configuration of business logic into code representative of a rule to identify one or more customer contact restrictions from customer data, see Cyr [0142] “the practitioner may create … using an administrative UI … Defining a workflow refers to chaining logical events in order to establish a programmatic routine that can be executed by the AI-based Compliance & Preference Service 100;” [0143] “invoke the use of the decisioning & workflow engine 115 to assert rules pertaining to time of day, compliance restrictions, and other attributes to tag the list entries appropriately” note the practitioner’s configured logic processed into an executable routine that asserts contact rules.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-10 and 12-21 are clearly drawn to at least one of the four categories of patent eligible subject matter recited in 35 U.S.C. 101 (method, system, and non-transitory computer-readable storage medium). Claims 1-10 and 12-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without integrating the abstract idea into a practical application or amounting to significantly more than the abstract idea.
Regarding Step 1 of the 2019 Revised Patent Subject Matter Eligibility Guidance (‘2019 PEG”), Claims 1-10, 12, and 21 are directed toward the statutory category of a process (reciting a “method”). Claims 13-19 are directed toward the statutory category of a machine (reciting a “system”). Claim 20 is directed toward the statutory category of an article of manufacturer (reciting a “non-transitory computer-readable storage medium”).
Regarding Step 2A, prong 1 of the 2019 PEG, Claims 1, 13 and 20 are directed to an abstract idea by reciting receiving, …, a user configuration of business logic … deploying, …, the rule to a rules repository that includes one or more rules maintained by the computing system; receiving … a data stream of customer data of the plurality of customers; applying … and in real-time the one or more rules including the rule deployed to the rules repository to the data stream of customer data to identify the one or more customer contact restrictions for one or more customers of the plurality of customers as the customer data is streamed to the computing system; outputting … a first report comprising a plurality of customer identifiers for the plurality of customers, and for a particular customer identifier for a particular customer, an indicator of which customer contact restrictions apply to the particular customer; and outputting … a second report comprising a list of customer identifiers as a subset of the plurality of customer identifiers that are permitted to be contacted for a marketing campaign (Example Claim 1).
The claims are considered abstract because these steps recite certain methods of organizing human activity like commercial interactions (including advertising, marketing or sales activities or behaviors; business relations) and managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). The claims recite collecting customer data, applying rules to the customer data to determine contact restrictions and outputting reports in response. Applicant’s disclosure does not recite a particular problem the claimed steps aim to solve, however, it is understood that the claimed steps aim to automate the filtering of customers by contact restrictions to ensure compliance with regulatory requirements and customer preferences (Applicant’s Specification, [0006]). By this evidence, the claims recite a type of commercial interactions (including advertising, marketing or sales activities or behaviors; business relations) and managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) common to judicial exception to patent-eligibility. By preponderance, the claims recite an abstract idea (e.g., a “digital customer consent engine” for determining whether customers can be contacted).
Regarding Step 2A, prong 2 of the 2019 PEG, the judicial exception is not integrated into a practical application because the claims (the judicial exception and the additional elements such as a computing system; a memory; and one or more processors; processing, by the computing system, the user configuration of business logic into code representative of a rule to identify one or more customer contact restrictions from customer data; compiling, by the computing system, the code into the rule without requiring software development of the rule by a user) are not an improvement to a computer or a technology, the claims do not apply the judicial exception with a particular machine, the claims do not effect a transformation or reduction of a particular article to a different state or thing nor do the claims apply the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment such that the claims as a whole is more than a drafting effort designed to monopolize the exception (see MPEP §§ 2106.05(a-c, e)).
Dependent claims 2-10. 12, 14-19, and 21 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the limitations recite mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea ‐ see MPEP 2106.05(f).
Regarding Step 2B of the 2019 PEG, the additional elements have been considered above in Step 2A Prong 2. The claim limitations do not amount to significantly more than the judicial exception because they are directed to limitations referenced in MPEP 2106.05I.A. that are not enough to qualify as significantly more when recited in a claim with an abstract idea because the limitations recite mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea ‐ see MPEP
2106.05(f).
Applicant's claims mimic conventional, routine, and generic computing by their similarity to other concepts already deemed routine, generic, and conventional [Berkheimer Memorandum, Page 4, item 2] by the following [MPEP § 2106.05(d) Part (II)]. The claims recite steps like: “Receiving or transmitting data over a network, e.g., using the Internet to gather data,” Symantec, “Performing repetitive calculations,” Flook, and “storing and retrieving information in memory,” Versata Dev. Group, Inc. v. SAP Am., Inc. (citations omitted), by performing steps of “receiving” user configured business logic, “processing” the business logic into code, “compiling” the code into a rule, “deploying” the rule to a rules repository, “receiving” customer data, “ applying” rules to the customer data, “outputting” a first report, and “outputting” a second report (Example Claim 1).
By the above, the claimed computing “call[s] for performance of the claimed information collection, analysis, and display functions ‘on a set of generic computer components' and display devices” [Elec. Power Group, 830 F.3d at 1355] operating in a “normal, expected manner” [DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d at 1245, 1258 (Fed. Cir. 2014)].
Conclusively, Applicant's invention is patent-ineligible. When viewed both individually and as a whole, Claims 1-10 and 12-21 are directed toward an abstract idea without integration into a practical application and lacking an inventive concept.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-5, 7-10, 12-15, and 17-21 are rejected under 35 USC 103 as being unpatentable over the teachings of
St-Cyr et al., US 20190158666 A1, hereinafter Cyr, in view of
Sheldon et al., US 20150121241 A1, hereinafter Sheldon. As per,
Claims 1, 13, 20
Cyr teaches
A method comprising: /
A computing system, comprising: a memory; and one or more processors in communication with the memory, and configured to: /
A non-transitory computer-readable storage medium comprising instructions that, when executed, cause one or more processors to:
receiving, by a computing system, a user configuration of business logic; (Cyr [0115] “the administrative interface service/proxy 116 may be to provide a programmatic interface for rules, parameters, AI queries, campaign templates … to be created and saved for downstream use … All of this input may be facilitated via an administrative interface governed and hosted by the administrative interface service/proxy 116;” [0142] “the practitioner may create … using an administrative UI” note the programmatic interface for receiving input of business logic)
processing, by the computing system, the user configuration of business logic into code representative of a rule to identify one or more customer contact restrictions from customer data; (Cyr [0142] “the practitioner may create … using an administrative UI … Defining a workflow refers to chaining logical events in order to establish a programmatic routine that can be executed by the AI-based Compliance & Preference Service 100;” [0143] “invoke the use of the decisioning & workflow engine 115 to assert rules pertaining to time of day, compliance restrictions, and other attributes to tag the list entries appropriately” note the practitioner’s configured logic processed into an executable routine that asserts contact rules)
compiling, by the computing system, the code into the rule without requiring software development of the rule by a user; (Cyr [0094] “RTEs may be designed to convert application-specific routines, manifest in a computer-read language, into a language that the hardware (machine) can understand (machine language);” [0061] “the disclosed embodiments make it possible to abstract practitioners … from the complexity and expertise required to build custom applications … that allows the practitioner to easily define AI-based routines” note the runtime engine that converts the application routines into machine language and the practitioners abstracted from needing programming expertise to create the routines)
deploying, by the computing system, the rule to a rules repository that includes one or more rules maintained by the computing system; (Cyr [0114] “the decisioning & workflow engine 115 may act as a micro-service always accessible to the AI-based Compliance & Preference Service 100. System-related and campaign-related rules, workflow and decision logic may be identified and accessed here;” [0115] “The purpose of the administrative interface service/proxy 116 may be to provide a programmatic interface for rules ... to be created and saved for downstream use by the AI-based Compliance & Preference Service 100” noting the decisioning and workflow engine housing the system-related and campaign-related rules, which include the practitioner created rules)
receiving, by the computing system, a data stream of customer data of the plurality of customers; (Cyr [0012] “the system may use AI to match credentialed customers with profiles from social media, customer relationship management (CRM) platforms, automatic call distributors (ACDs), etc. to ascertain preferred channels, demographics, and other data that can be used for intelligent routing and compliance” noting the customer data)
applying, by the computing system and in real-time, the one or more rules including the rule deployed to the rules repository to the data stream of customer data to identify the one or more customer contact restrictions for one or more customers of the plurality of customers as the customer data is streamed to the computing system; (Cyr [0143] “a) load target customer list into memory, b) run a specific named AI template consisting of an AI routine from the compliance AI library 2000 against the target list, c) run a specific named AI template consisting of an AI routine from the BTTC AI library 3000, d) output the resulting AI-based list from steps b and c into a data file stored in the database 105, e) invoke the use of the decisioning & workflow engine 115 to assert rules pertaining to time of day, compliance restrictions, and other attributes to tag the list entries appropriately;” [0152] “the tagging and identification … of callout lists, lead lists, customer lists may occur in this step along with the association of such lists with the particular campaign. In addition, data relating to customer experience and forensic data including historical and real time customer journey data;” [0164] “the AI-based Compliance & Preference Service 100 to globally implement updates automatically and in real time as regulations and customer preferences change.” Cyr expressly teaches applying the one or more rules (compliance AI library template) to identify customer contact restrictions as the customer data is streamed to the computing system in real-time)
outputting, by the computing system, a first report comprising a plurality of customer identifiers for the plurality of customers, and […] (Cyr [0016] “a method for translation of these “AI compliance templates” and further the ability to automatically output them into “scrubbed” campaign lists, complete with consumers' names, contact information and channel preferences”)
outputting, by the computing system, a second report comprising a list of customer identifiers as a subset of the plurality of customer identifiers that are permitted to be contacted for a marketing campaign. (Cyr [0013] “the system may use AI templates to automatically provide instructions on what form of communication to use for each customer based on compliance conformance and preference. This may include the ability to either output scrubbed and up-loadable lists” noting the output of the scrubbed list)
Cyr does not explicitly teach, Sheldon however in the analogous art of customer contact compliance teaches
[…] for a particular customer identifier for a particular customer, an indicator of which customer contact restrictions apply to the particular customer; and (Sheldon fig. 6 noting the key; [0003] “Provided herein are embodiments directed to systems for assigning visual representation to contacts … at least one contact associated with each customer comprises one or more contact statuses … a permission-to-communicate status;” [0004] “In some embodiments, at least one of the one or more indicators indicates that communicating with a customer via the first contact is prohibited” note the contact restriction indicator)
Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to modify Cyr’s compliance platform to include an indicator of what restriction applies in view of Sheldon in an effort to quickly identify and exclude customers from contact (see Sheldon ¶ [0056] & MPEP 2143G).
Claim 2
Cyr teaches
wherein maintaining the one or more rules comprises: receiving, via a user interface from a user computing device, a request to modify a first rule of the one or more rules including the rule deployed to the rules repository; (Cyr [0083] “Administrative tools may include an HTML/JavaScript-enabled web server for UI (User Interface) access to provisioning services. Such services may be enabled by a reports & analytics service/proxy 108 (e.g. a proxy server) as described in more detail with respect to FIG. 3. The primary reports & analytics & administration portal 225 can be created by a person with average skill in Web Services, HTML, or JavaScript programming.” Note the interface with administrative tools)
modifying, based on the receiving, the first rule to create a second rule without further requiring software development or further input from a user; and maintaining the second rule such that the first rule is replaced by the second rule within the one or more rules including the rule deployed to the rules repository. (Cyr [0074] “the AI-based Compliance & Preference Service 100 may obtain a customer list associated with a particular tenant … modify the customer list according to one or more AI templates associated with the tenant or a campaign of the tenant” note the modification of customer list for a tenant according to one or more templates corresponding to modifying a rule without further software development; [0164] “Among the advantages of the disclosed embodiments relative to conventional systems is the capability of the AI-based Compliance & Preference Service 100 to globally implement updates automatically and in real time as regulations and customer preferences change.”)
Claim 3
Cyr teaches
wherein maintaining the one or more rules comprises: receiving, by the computing system, data regarding one or more regulatory requirements; (Cyr [0012] “The system may be designed to incorporate known litigator lists, regional statutes for time-of-day and emergency restrictions, reverse directories, and other important regulatory compliance data”)
creating, by the computing system, at least one rule to implement the regulatory requirement without requiring software development or further input from a user; and maintaining, by the computing system, the rule in addition to the one or more rules including the rule deployed to the rules repository. (Cyr [0131] “regulatory statutes may dictate when you are not allowed to call customers in each state, such as before or after certain hours of the day or during certain state or region-wide emergencies. This information can be compiled and an algorithm can be used to determine “black out periods” when NOT to call. … In addition, demographic data may be used to determine the best time to call including socio-economic data associated with the zip code of the customer … A BTTC routine can be used to amalgamate all of these data points to make a determination of the best time to call.” Note the multiple rules created and maintained in addition to the regulatory requirements rule)
Claims 4, 14
Cyr teaches
receiving, by the computing system, one or more contact requirements for the contact campaign; and (Cyr [0012] “the system may use AI to match credentialed customers with profiles from social media, customer relationship management (CRM) platforms, automatic call distributors (ACDs), etc. to ascertain preferred channels, demographics, and other data that can be used for intelligent routing and compliance”)
selecting, by the computing device, a set of rules from the one or more rules including the rule deployed to the rules repository, wherein the set of rules identify a set of customer contact restrictions for compliance by the contact campaign, (Cyr [0141] “the routines that have been stored thus far in either, all, or some of the compliance AI library 2000, BTTC AI library 3000, prioritization library 4000, BOT library 5000, or predictive library 6000 may be associated with a template and then stored as a named template in a template library 7000. In this way, the AI-based Compliance & Preference Service 100 or a practitioner thereof may store a plurality of AI templates, each of which is associated with one or more AI routines (e.g. selected from among the AI routines stored in the libraries 2000, 3000, 4000, 5000, 6000). Such templates may also be referred to as name states for the purposes of building and editing workflows” note the selection of rules; [0145] “Once named states and workflow are documented in this step 1035, the resulting named workflows may then be stored as workflow objects in a workflow library 8000. In subsequent steps described below, such workflow objects may thereafter be associated with tenants and tenant-specific campaigns for execution” corresponding to a contact campaign)
wherein applying the one or more rules to the data stream of customer data comprises: comparing, by the computing system, the set of rules to at least a portion of the data stream of customer data indicating contact restrictions for the particular customer; and determining, by the computing system and based on the comparison, that the particular customer is permitted to be contacted for the contact campaign, and (Cyr [0023] “system may have the ability to create AI subroutines and associated logic and save them in a AI library for downstream incorporation into targeted, tenant-specific campaigns for the specific purpose of applying AI classifier-based libraries for Best Time to Call (BTTC) and other constraints” note the application of the rules to the customer data)
wherein outputting the second report comprises outputting, by the computing system and based on the determination, a second report that includes the particular customer identifier of the particular customer. (Cyr [0013] “the system may use AI templates to automatically provide instructions on what form of communication to use for each customer based on compliance conformance and preference. This may include the ability to either output scrubbed and up-loadable lists” noting the output of the scrubbed list)
Claims 5, 15
Cyr teaches
receiving, by the computing system, one or more contact requirements for the contact; and (Cyr [0012] “the system may use AI to match credentialed customers with profiles from social media, customer relationship management (CRM) platforms, automatic call distributors (ACDs), etc. to ascertain preferred channels, demographics, and other data that can be used for intelligent routing and compliance”)
selecting, by the computing system, a set of rules from the one or more rules including the rule deployed to the rules repository, wherein the set of rules identify a set of customer contact restrictions for compliance by the contact campaign, (Cyr [0141] “the routines that have been stored thus far in either, all, or some of the compliance AI library 2000, BTTC AI library 3000, prioritization library 4000, BOT library 5000, or predictive library 6000 may be associated with a template and then stored as a named template in a template library 7000. In this way, the AI-based Compliance & Preference Service 100 or a practitioner thereof may store a plurality of AI templates, each of which is associated with one or more AI routines (e.g. selected from among the AI routines stored in the libraries 2000, 3000, 4000, 5000, 6000). Such templates may also be referred to as name states for the purposes of building and editing workflows” note the selection of rules; [0145] “Once named states and workflow are documented in this step 1035, the resulting named workflows may then be stored as workflow objects in a workflow library 8000. In subsequent steps described below, such workflow objects may thereafter be associated with tenants and tenant-specific campaigns for execution” corresponding to a contact campaign)
wherein applying the one or more rules to the data stream of customer data comprises: comparing, by the computing system, the set of rules to at least a portion of the data stream of customer data indicating contact restrictions for the particular customer; and determining, by the computing system and based on the comparison, that the particular customer is not permitted to be contacted, and (Cyr [0023] “system may have the ability to create AI subroutines and associated logic and save them in a AI library for downstream incorporation into targeted, tenant-specific campaigns for the specific purpose of applying AI classifier-based libraries for Best Time to Call (BTTC) and other constraints” note the application of the rules to the customer data)
wherein outputting the second report comprises outputting, by the computing system and based on the determination, a second report that does not include the particular customer identifier of the particular customer. (Cyr [0013] “the system may use AI templates to automatically provide instructions on what form of communication to use for each customer based on compliance conformance and preference. This may include the ability to either output scrubbed and up-loadable lists” noting the output of the scrubbed list)
Claims 7, 17
Cyr teaches
receiving, by the computing system, do-not-contact list data for the particular customer of the plurality of customers; and (Cyr [0071] “The AI-based Compliance & Preference Service 100 may further be connected to a 3rd party compliance, preference, profile, or directory system or systems 210.”)
associating, by the computing system, the do-not-contact list data with the particular customer identifier of the particular customer, wherein applying the one or more rules including the rule deployed to the rules repository to the data stream of customer data comprises applying a rule to identify a do-not-call list restriction for the particular customer, and (Cyr [0012] “The system may be designed to incorporate known litigator lists, regional statutes for time-of-day and emergency restrictions, reverse directories, and other important regulatory compliance data.”)
wherein outputting the second report comprises outputting a second report that does not include the particular customer identifier of the particular customer. (Cyr [0013] “the system may use AI templates to automatically provide instructions on what form of communication to use for each customer based on compliance conformance and preference. This may include the ability to either output scrubbed and up-loadable lists” noting the output of the scrubbed list)
Claims 8, 18
Cyr teaches
wherein the customer data is a first customer data received in the stream of customer data at a first point in time, the method further comprising: receiving, by the computing system, second customer data in the stream of customer data at a second point in time, wherein the second customer data includes a change in contact preferences for the particular customer, wherein the change in contact preferences indicates a do-not-contact preference for one or more types of contact channels; and (Cyr [0018] “the ability of the AI-based Compliance & Preference Service to provide a universal means for each enterprise's customers to provide feedback and establish preferred communication methods or channels. For example, a customer may only wish to be contacted by SMS. Or another customer may only want to be contacted via phone or email.” Note the feedback including a contact channel preference change)
applying, by the computing system, the one or more rules including the rule deployed to the rules repository to the data stream of customer data at or after the second point in time, wherein applying the one or more rules including the rule deployed to the rules repository to the data stream of customer data comprises applying a rule to the second customer data to identify a do-not-call preference restriction for the particular customer, and (Cyr [0023] “system may have the ability to create AI subroutines and associated logic and save them in a AI library for downstream incorporation into targeted, tenant-specific campaigns for the specific purpose of applying AI classifier-based libraries for Best Time to Call (BTTC) and other constraints” note the application of the rules to the customer data)
wherein outputting the second report comprises outputting a second report that does not include the one or more types of contact channels for the particular customer identifier of the particular customer. (Cyr [0013] “the system may use AI templates to automatically provide instructions on what form of communication to use for each customer based on compliance conformance and preference. This may include the ability to either output scrubbed and up-loadable lists” noting the output including what form of communication to use)
Claim 9
Cyr does not explicitly teach, Sheldon however in the analogous art of customer contact compliance teaches
wherein outputting the first report comprises outputting the first report for inclusion in an audit log of the customer contact restrictions applied to the one or more customers. (Sheldon [0038] “the system may track and store details regarding the customer communications. … The system may identify the date, time, means of communication (such as specific telephone number, email address, or the like). Furthermore, the system may store any comments or notes made by the representative during the communications;” [0048] “even contacts that lack permission may be included in manual or semi-manual dialing campaigns. In such embodiments, contacts are assigned indicators” noting the tracking and storing of details regarding customer communications and the restricted contacts assigned indicators)
The motivation/rationale to combine Cyr with Sheldon persists.
Claim 10
Cyr does not explicitly teach, Sheldon however in the analogous art of customer contact compliance teaches
wherein the first report includes, for each indicator of which customer contact restrictions apply to the particular customer, a reason why the particular customer is not permitted to be contacted for the contact campaign. (Sheldon [0003] “Provided herein are embodiments directed to systems for assigning visual representation to contacts … at least one contact associated with each customer comprises one or more contact statuses … a permission-to-communicate status;” [0004] “the executable instructions cause the processor to assign a first indicator to a first contact of a first account based on the first contact being locked, assign a second indicator to a second contact of a second account based on an external request associated with the second contact, and assign a third indicator to a third contact of the first account based on a velocity range of the third account. In still other embodiments, each of the second indicator and the third indicator comprise the same visual representation and the first indicator comprises an auditory indicator. In some embodiments, at least one of the one or more indicators indicates that communicating with a customer via the first contact is prohibited.” note the different indicators corresponding to different reasons why contact is prohibited)
The motivation/rationale to combine Cyr with Sheldon persists.
Claims 12, 19
Cyr teaches
wherein outputting the second report comprises outputting the second report via an API to one or more services. (Cyr [0057] “various systems and methods for implementing an AI-based Compliance & Preference Service to, among other things, provide artificial intelligence (AI) functionality to target legacy customer outreach platforms” noting the one or more services; [0076] “The AI-based Compliance & Preference Service 100 may be connected to the 3rd party media systems 215 over a communications channel or transmission method 903. Such 3rd party media systems 215 are typically operated by service providers that allow enterprises to connect using published APIs and other methods” noting the use of APIs)
Claim 21
Cyr teaches
receiving, by the computing system, a user modification of business logic; and (Cyr [0015] “An AI engine embedded in the AI-based Compliance & Preference Service can be programmed with “AI compliance templates” that can be stored, used and modified;” [0115] “The purpose of the administrative interface service/proxy 116 may be to provide a programmatic interface for rules, parameters, AI queries, campaign templates, tenant attributes, skills, agents, groups, etc. to be created and saved” note the admin user modifying the compliance templates)
modifying, by the computing system and in real-time, a rule of the one or more rules including the rule deployed to the rules repository based on the user modification of business logic and without further requiring software development or further input from a user. (Cyr [0164] “the AI-based Compliance & Preference Service 100 to globally implement updates automatically and in real time as regulations and customer preferences change;” [0088] “the AI-based Compliance & Preference Service 100 can be used to pre-define the format, fields, objects, etc. required … list services gateway 120 can be used to automatically transmit AI-enhanced lists … so that no manual intervention, or very little manual intervention, is required” note the modifying of a rule without new software development and further user input)
Claims 6 and 16 are rejected under 35 USC 103 as being unpatentable over the teachings of
Cyr in view of Sheldon in view of
Sivasubramanian et al., US 20210157834 A1, hereinafter Sivasubramanian. As per,
Claims 6, 16
Cyr / Sheldon do not explicitly teach, Sivasubramanian however in the analogous art of customer contact compliance teaches
determining, by the computing system, that a first rule of the one or more rules including the rule deployed to the rules repository is in conflict with a second rule; (Sivasubramanian [0096] “If the authorization matches the request to one or more permissions specified by the policy”)
identifying, by the computing system, which of the first rule or the second rule would result in more customers of the plurality of customers being indicated as having at least one customer contact restriction; and (Sivasubramanian [0096] “If the authorization matches the request to one or more permissions specified by the policy, the authorization module 312 may resolve this by selecting the least restrictive response”)
selecting, by the computing system, the one of the first rule or the second rule that would result in more customers that are permitted to be contacted. (Sivasubramanian [0096] “If the authorization matches the request to one or more permissions specified by the policy, the authorization module 312 may resolve this by selecting the least restrictive response”)
Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to modify Cyr’s compliance platform and Sheldon’s restriction indicators to conflicting rules resolution in view of Sheldon in an effort to improve operational efficiency of customer contact centers (see Sivasubramanian ¶ [0034] & MPEP 2143G).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 11743137 B2; WO 2011002777 A2; Badger et al, Cloud computing synopsis and recommendations, 2012.
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/MOHAMED N EL-BATHY/Primary Examiner, Art Unit 3624