Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 October 28, 2025 has been entered.
Status of Claims
Claims 1, 3-8, 10-15, 17-20 have been amended.
Claims 1-20 are currently pending and have been examined.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
Claims 15-20 are drawn to methods while claim(s) 1-14 is/are drawn to an apparatus. As such, claims 1-20 are drawn to one of the statutory categories of invention (Step 1: YES).
Step 2A - Prong One:
Claim 15 (representative of independent claim(s) 1 and 8 recites the following steps:
training, a learning model using sets of training data to create a trained learning model, the sets of training data comprising a first set of training data comprising a plurality of languages to train the learning model to recognize the plurality of languages;
generating and displaying, a first chat that facilitates a chat communication session between the user and support agent;
generating and displaying, one or more probing questions from the support agent;
receiving, responsive to a service request in a service request in a first natural language input
detecting a language used by the user executing natural language processing of the first natural language input;
executing, human support agent analysis of the service request, using the trained learning model, to identify a human support agent to automatically route the chat communication session based on the identified human support agent having: a) a linguistic compatibility with the detected language, and b) previously engaged in less than a predetermined number of chat communication sessions during a current business day, wherein the trained learning model dynamically analyzes, in response to answers provided by the user to the one or more probing questions, stored human support agent data, including stored chat data ,associated with a plurality of human support agents, and
automatically routing, via the automated support agent in response to executing the human support agent analysis, the virtual chat communication session from the automated support agent to the identified
These steps, under its broadest reasonable interpretation, describe or set-forth delivering financial services by facilitating chat support, which amounts to a “managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions)”. These limitations therefore fall within the "certain methods of organizing human activity" subject matter grouping of abstract ideas.
Alternatively, these steps, under its broadest reasonable interpretation, encompass a learning model which is interpreted to be a mathematical relationship. These limitations therefore fall within the “mathematical concepts” subject matter grouping of abstract ideas.
Alternatively, these steps, under its broadest reasonable interpretation, encompass a human manually (e.g., in their mind, or using paper and pen) engaging with a user, detecting a linguistic compatibility and routing to a qualified agent (i.e., one or more concepts performed in the human mind, such as one or more observations, evaluations, judgments, opinions), but for the recitation of generic computer components. If one or more claim limitations, under their broadest reasonable interpretation, covers performance of the limitation(s) in the mind but for the recitation of generic computer components, then it falls within the "mental processes" subject matter grouping of abstract ideas.
As such, the Examiner concludes that claim 15 recites an abstract idea (Step 2A - Prong One: YES).
Independent claim(s) 1 and 8 are determined to recite an abstract idea under the same analysis.
Step 2A - Prong Two:
This judicial exception is not integrated into a practical application. The claim(s) recite the additional elements/limitations of:
by a server computer system,
machine learning model
by the one or more financial institution servers on a client device
a first chat interface
a virtual chat communication session
an automated support agent
by the server computer system via the first chat interface,
by the server computer system via the first chat interface,
executing, by the server computer system,
wherein the stored human support agent data resides in a non- transitory memory of the server computer system;
A server computer system comprising: one or more processors; and a non-transitory memory coupled to the one or more processors, the non-transitory memory including a set of instructions of computer-executable program code, which when executed by the one or more processors, (Claim 1)
A computer program product comprising at least one non-transitory computer readable medium having with a set of instructions of computer- executable program code, which when executed by one or more processors of a server computer system, (Claim 8)
The requirement to execute the claimed steps/functions listed above is equivalent to adding the words ''apply it'' on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. This/these limitation(s) do/does not impose any meaningful limits on producing the abstract idea and therefore do/does not integrate the abstract idea into a practical application (see MPEP 2106.05(f)).
Additionally, “Step 2A - Prong 2”, the recited additional element(s) of "during execution of a software application by a client device of a user over a communication network" serve merely to generally link the use of the judicial exception to a particular technological environment or field of use. These limitations therefore do not integrate the abstract idea into a practical application (see MPEP 2106.05(h)).
The Examiner has therefore determined that the additional elements, or combination of additional elements, do not integrate the abstract idea into a practical application. Accordingly, the claim(s) is/are directed to an abstract idea (Step 2A -Prong Two: NO).
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
As discussed above in "Step 2A - Prong 2", the requirement to execute the claimed steps/functions listed above is equivalent to adding the words "apply it" on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. These limitations therefore do not qualify as "significantly more" (see MPEP 2106.05 (f)).
As discussed above in “Step 2A - Prong 2”, the recited additional element(s) of "during execution of a software application associated with the financial institution by a client device of a user over a communication network" serves merely to generally link the use of the judicial exception to a particular technological environment or field of use. These limitations therefore do not qualify as “significantly more5' (see MPEP 2106.05(g, h)).
The Examiner has therefore determined that no additional element, or combination of additional claims elements is/are sufficient to ensure the claim(s) amount to significantly more than the abstract idea identified above (Step 2B: NO).
Regarding Dependent Claims:
Dependent claims 4 and 11 and 18 include additional limitations that are part of the abstract idea.
Dependent claims 2-7, 9-10, 12-15 and 16, 17, 19-20 include additional limitations that are part of the abstract idea except for:
Machine learning model
virtual chat communication session
automated support agent
client device
a second chat interface
the first chat interface
the widget
server computer system
The additional elements of the dependent claims are equivalent to adding the words ''apply it'' on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. Even in combination, these additional elements do not integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea itself. The claims are ineligible.
The additional elements of the dependent claims of 7 and 14 which state “generate and display a widget superimposed on the first chat interface,” and Claim 3 and 10 and 17“displaying on the client device a second chat interface in a second format, the second format comprising a floating action chat icon superimposed on the first chat interface and connects the client device to the identified human support agent” serves merely to generally link the use of the judicial exception to a particular technological environment or field of use. These limitations therefore do not qualify as “significantly more5' (see MPEP 2106.05(g, h)).
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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Cummins (2019/0087707) in view of Indyk (2020/0007687).
Claims 1, 8 and 15
Cummins discloses a server computer system, comprising:
one or more processors (Cummins [0074]); See the ELectronic DEVice (ELDEV) “includes one or more processors 610 and a memory 612 coupled to processor(s) 610.”
a non-transitory memory coupled to the one or more processors, the non-transitory memory including a set of instructions of computer-executable program code, which when executed by the one or more processors, cause the server computer system (Cummins [0011][0070]); See “First and second primary content servers 590A and 590B may also host for example other Internet services such as a search engine, financial services, third party applications and other Internet based services.”
A computer program product comprising at least one non-transitory computer readable medium having with a set of instructions of computer-executable program code, which when executed by one or more processors of server computer system, (Cummins [0011]);
training, byWhich teaches the training of conversation.
generating and displaying, by the server computer system on the client device, a first chat interface that facilitates a virtual chat communication session between the user and an automated support agent (Cummin Figure 8B, 824]); See also [0093] where the Artificial Conversational Entity (ACESAP) message is the automated support agent. See also [0010] “providing a conversation interface within a graphical user interface of an electronic device…”
generating and displaying, by the server computer system on the first chat interface, one or more probing questions from the automated support agent (Cummins [0094]); See at least “Accordingly, the ACESAP provides second ACESAP message 826 which is a repeat of second ACESAP output 730 in flow 700 in FIG. 7 indicating the selected product and seeking the user's next input through a directed question.”
Cummin does not explicitly disclose routing based on human support agent datal. Indyk teaches:
receiving, by the server computer system via the first chat interface responsive to the one or more probing questions, a service request in a first natural language input; executing, by the server computer system, natural language processing of the first natural language input to detect a language used by the user (Indyk [0017) See at least “in one embodiment, a user utters commands processed by a software application. A feature extractor identifies paralinguistic features characterizing the audio input.”
executing, by the server computer system, human support agent analysis of the service request, using the trained machine learning model, to identify a human support agent to automatically route the virtual chat communication session based on the identified human support agent having: a) a linguistic compatibility with the detected language (Indyk [0039][0048][0070][0073]); See [0070] “a server system 700 that routes users to support agents based on paralinguistic features of user audio input,…” See also [0073] “The support routing module 112 compares the baseline attribute levels to the support agent profiles 108 to identify a support agent to assist the user. The support routing module 112 adds the user to an agent queue for a support agent that meets the baseline attributes.”
b) previously engaged in less than a predetermined number of virtual chat communication sessions during a current business day, wherein the trained machine learning model dynamically analyzes, in response to answers provided by the user to the one or more probing questions, stored human support agent data, including stored chat data, associated with a plurality of human support agents, wherein the stored human support agent data resides in a non- transitory memory of the server computer system; (Indyk [0018][0024]) See at least [0018]“If a profile for the user is available, the support routing module may also compare the user profile to the agent profile and base the selection on the comparison.” See also [0134] “Machine-learning engine 302 processes this training set to recognize call agent interactions with similar customers.” Where the learning of past call agent interactions is the stored human support agent data.
automatically routing, via the automated support agent in response to executing the human support agent analysis, the virtual chat communication session from the automated support agent to the identified human support agent (Indyk [0073]) See at least “The support routing module 112 compares the baseline attribute levels to the support agent profiles 108 to identify a support agent to assist the user. The support routing module 112 adds the user to an agent queue for a support agent that meets the baseline attributes..”
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included in the method of a chat support platform that facilitates enhanced chat routing, as taught by Cummins, using human support agent data to route communication, as taught by Indyk, to better aid the customer in getting issues resolved quickly (Indyk [0014]).
Claims 2, 9 and 16
Modified Cummins and Indyk discloses the limitation above. Indyk further teaches:
wherein executing human support agent analysis comprises applying the trained machine learning model to the human support agent data that comprises calendar data, scheduling data, educational data specific to each individual human support agent of the plurality of human support agents, and professional experience data that are specific to each individual human support agent of the plurality of human support agents (Indyk [0028][0030]). See at least [0153] “The support routing module 112 identifies the attribute levels that correspond to the score in the mapping 113. The attribute levels to which the score maps serve as baselines for selecting a support agent to assist the user. The support routing module 112 compares the attribute levels to the support agent profiles 108 to identify a set of support agents who meet ( or exceed) the attribute levels.”
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included in the method of a chat support platform that facilitates enhanced chat routing and an enhanced user chat experience, as taught by Cummins, characteristics of the human agent that inquiries should be routed to, as taught by Indyk, to better aid the customer in getting issues resolved quickly (Indyk [0014]).
Claims 3, 10 and 17
Modified Cummins and Indyk discloses the following. Modified Cummins further teaches:
wherein the virtual chat communication session is automatically routed from the automated support agent to the identified appropriate human support agent by generating and displaying on the client device a second chat interface in a second format different than the first format, the second format comprising a floating action chat icon superimposed on the first chat interface that connects the client device to the identified appropriate human support agent. (Cummins [0067][0155][Claim 1][Figure 8E; 820E]). See [0097] “the Artificial Conversational Entity (ACESAP) has notified the user that they can be connected with a customer representative but that there is a wait or alternatively they can leave their details and the customer representative will call them back. In this instance the ACESAP defaults to the enquiry form to be displayed but if the user elected to be connected to the customer representative then the user may be provided with a VOIP interface such as Google™ Hangouts, Skype™ etc.” Where the second format (icon) is 820E in Figure 8E.
Claims 4 and 11, 18
Modified Cummins and Indyk discloses the following. Modified Cummins further teaches:
wherein the appropriate human support agent is identified based on a current availability of the appropriate human support agent and the appropriate human support agent not having been previously engaged in a predetermined number of virtual chat communication sessions during a current business day (Cummins [0132]). Where the reference teaches analyzing agent call time and resolution success. Cummins does not explicitly disclose current availability of the human support agent. Cummins does teach the support agent history of interactions including call duration. It would have been obvious to a person having ordinary skill in the art at the time the invention was filed that the availability would be considered because it would affect wait times.
Claims 5, 12 and 19
Modified Cummins and Indyk discloses the limitation above. Indyk further teaches:
wherein training the machine learning model using sets of training data comprises iteratively training the machine learning model based on sets of training data that include: the first set of training data; a second set of training data comprising a minimum amount of experience needed for a support agent to respond to specific service requests; a third set of training data comprising sample requests for different types ofSee at least “A predictive model (e.g., a machine-learning model) uses the paralinguistic features to determine a score”
Although the limitation has been addressed in view of prior art, the Examiner notes that the particular type of training sets (i.e. “second set; third set; fourth set” as claimed) is considered non-functional descriptive material, of which does not explicitly alter or impact the steps of the method in such a way as to establish a new and unobvious functional relationship with the method as claimed. As such, the non-functional descriptive material limitation can be given little to no patentable weight. See MPEP 2111.05. The functional limitation is sets of training data. The reference cited teaches this.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included in the method of a chat support platform that facilitates enhanced chat routing and an enhanced user chat experience, as taught by Cummins, multiple data sets to train the system, as taught by Indyk, to better aid the customer in getting issues resolved quickly (Indyk [0014])..
Claims 6, 13 and 18
Modified Cummins and Indyk discloses the limitation above. Indyk further teaches:
wherein the human support agent analysis, using the trained machine learning model, is further configured to identify the appropriate human support agent having the minimum amount of experience needed and specialized training in a specific type ofSee “Provided the user selects to communicate with an agent, the support routing module 112 compares the score for the user to a mapping 113. The mapping 113 associates scores with experience levels, customer-satisfaction levels, or levels of other attributes found in the support agent profiles 108.”
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included in the method of a chat support platform that facilitates enhanced chat routing and an enhanced user chat experience, as taught by Cummins, multiple tiers of service, as taught by Indyk, to provide the best assistance to a customer.
Claims 7, 14 and 20
Modified Cummins Indyk discloses the following. Modified Cummins further teaches:
wherein the set of instructions, when executed by the one or more processors, cause the server computer system to generate and display a widget superimposed on the first chat interface, the widget including a professional profile of the appropriate human support agent, wherein the professional profile comprises: name, job title, location, and contact information. (Cummins [Figure 8F, 870]). Where the profile image of the human agent is displayed.
Although the limitation has been addressed in view of prior art, the Examiner notes that the particular type of profile data (i.e. “name, job title, location, and contact information” as claimed) is considered non-functional descriptive material, of which does not explicitly alter or impact the steps of the method in such a way as to establish a new and unobvious functional relationship with the method as claimed. As such, the non-functional descriptive material limitation can be given little to no patentable weight. See MPEP 2111.05. The functional limitation is displaying a widget of the customer service representative. The reference cited teaches this.
Response to Arguments
Applicant's arguments with respect to the rejection under 35 USC 112 have been fully considered and are persuasive. The rejection has been withdrawn.
Applicant's arguments with respect to the rejection under 35 USC 103 have been fully considered but they are not persuasive.
Applicant Argues: Cummins appears to teach that demographics may be ascertained from the language used by the user. Demographics typically include characteristics of a population (e.g., race, sex, age, etc.) but does not indicate specific language… Cummins fails to teach that active chats are filtered based on a detected language of the user, let alone determining whether a human support agent is linguistically compatible with the detected language for automatically routing the virtual chat communication session.
Examiner agrees and has updated the rejection, in light of the amendments, to cite Indyk (2020/0007687) for the teaching.
Applicant Argues: Can and Yan
Examiner agrees and has updated the rejection, in light of the amendments, to cite Indyk (2020/0007687) for the teaching.
Applicant Argues: Claims 3, 10, and 17
Examiner respectfully disagrees. (Cummins [Figure 8E; 820E]) teaches a first and second chat interface where the icon is interpreted to be reflected on Figure 8E,820E.
Applicant Argues: Claims 4, 11, and 18
Examiner respectfully disagrees. Cummins [0132] teaches analyzing agent call time and resolution success. Cummins does not explicitly disclose current availability of the human support agent. Cummins does teach the support agent history of interactions including call duration. It would have been obvious to a person having ordinary skill in the art at the time the invention was filed that the availability would be considered because it would affect wait times.
Applicant Argues: Claims 5, 12, and 19
Examiner agrees and has updated the rejection, in light of the amendments, to cite Indyk (2020/0007687) for the teaching.
Applicant's arguments with respect to the rejection under 35 USC 101 have been fully considered but they are not persuasive.
Applicant Argues: Here, it is the combination of elements, and not the novel or patentable nature of the limitations individually, that should result in the claim being viewed as containing patentable subject matter. The combination of limitations in the present claims confine the alleged abstract idea to a particular, practical application of the abstract idea that is not well-understood, routine, or conventional activity.
Examiner respectfully disagrees. Applicant’s claims of improving the display do not represent an improvement to a computer-related technology or technological environment, and do not amount to a technology-based solution to a technology-based problem. The interface is not improved, and there is not support for the improvement to the computer other than a general allegation that the claims define a patentable invention. The rejection is maintained.
Applicant Argues: Thus, similar to the holding in BASCOM, when viewed as an ordered combination, the claim limitations amount to significantly more than the abstract idea of "certain methods of organizing human activity," rendering the claim as patent eligible.
The Examiner notes that this claim of significantly more is not representative of an "actual" improvement to the technology itself, but at best is an improvement to the business method or abstract idea itself. Applicant can provide no tangible findings that there was actually anything different and/or improved in the instant system compared to prior "conventional systems", other than a mere allegation and unsubstantiated, conclusory statement that the instant invention improves existing systems and is significantly more than using trained data to output improved data using conventional systems. However, the Examiner respectfully notes that the features of the claimed invention does not represent an improvement, it is merely performing operations with a computer program product. The Applicant cannot point to anything that was specifically done either in the claimed subject matter, the specification, or provided reasoning to show how this is significantly more or provides an improvement to the technology of the conventional system implementation. Moreover, the Examiner respectfully notes that the needed "improvement" in terms of patent eligibility is not one resulting from programming a generic processor to perform a different (or even improved) function, but rather a specific and actual improvement to the machine itself is needed. Based on these findings of fact, the Examiner contends the claims are indeed directed towards an abstract idea and Applicant's arguments to the contrary are considered to be non-persuasive.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RASHIDA R SHORTER whose telephone number is (571)272-9345. The examiner can normally be reached Monday- Friday from 9am- 530pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jessica Lemieux can be reached at (571) 270-3445. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RASHIDA R SHORTER/Primary Examiner, Art Unit 3626
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