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 .
Status of Claims
The office action is in response to the Pre-Appeal Conference Decision mailed on April 30, 2026.
Claims 1 - 21 are pending and have been examined.
This action is made NON-FINAL.
Response to Arguments
Applicant’s 101 arguments filed on August 6th, 2025 and on March 4, 2026 have been fully considered but they are not persuasive.
Regarding applicant’s arguments against the 101 rejection of claims 1 – 21 on pages 1 – 2: Applicant’s arguments directed to Step 2A Prong 1 and Step 2A Prong 2 analyses were considered. However, these arguments are not persuasive and the Examiner respectfully disagrees for the following reasons:
For Step 2A Prong 1 and Prong 2 starting on pg. 6: The Applicant argues that pending claim 1 recites additional elements that integrate the exception into a practical application of that exception and are not directed to mental processes nor a method of organizing human activity of “customer, relations, service personalization, interpersonal behavior adjustments.” However, the Examiner finds this argument unpersuasive and respectfully disagrees. Because as the Applicant asserted, the claims require specific technical components working together in order to achieve the invention and that the claims recite improvements to conventional customer service systems by using processing circuitry. However, due to the high level of generality that the computer is recited, their corresponding claim limitations are still considered to be invoking “computers merely as a tool” to perform the business process in which it is merely adding the words “apply it” to the judicial exception (see MPEP 2106.05(a)(I) and 2106.05(f)(2) & (3)). Therefore, these limitations and their additional elements, individually and in combination, are not “significantly more” as these are recited in a high level of generality that cannot provide an inventive concept at Step 2B, and are not integrating the abstract idea into a practical application (see MPEP 2106.05).
Regarding the Applicant’s arguments of rejection under 35 U.S.C. § 102 to Wang for pending claims on pages 7 – 8: Applicant’s arguments filed in the pre-appeal brief filed March 4, 2026 have been fully considered. Upon further review, the Examiner agrees that the prior rejection under 35 U.S.C. § 102 to Wang was improper due to reliance on a reference that does not qualify as prior art with respect to the claimed invention because of an incorrect effective date.
Accordingly, the rejection of claims 1 – 21 under 35 U.S.C. § 102 set forth in the final OA mailed on December 15, 2025 is not maintained and is hereby withdrawn. Notwithstanding the withdrawal of the previous rejection, the Examiner has conducted a further search and consideration of the claimed subject matter. Based on this additional search, new grounds of rejection under 35 U.S.C. § 102 and § 103 are set forth below. Applicant is advised that the newly cited references properly qualify as prior art and are applied in a manner that addresses the previously noted deficiencies.
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.
Claim 1 – 21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more, and therefore does not recite patent-eligible subject matter. Firstly, it should be stated that claim 1 is being used as the most representative of the independent claim set.
Step 2A Prong 1: The abstract idea is defined by the elements of:
detecting presence of a customer at a geographic location associated with an institution;
determining, using processing circuitry, a customer sentiment of the customer, at the geographic location, prior to interaction of the customer with an employee of the institution based on analysis of a characteristic of the customer;
generating, based on the determining, a customer-specific interaction recommendation for interacting with the customer at the geographic location, during an interaction with the employee of the institution;
rendering a dashboard for display on a user interface, the dashboard including the customer- specific interaction recommendation and
displaying the dashboard on the user interface of a display-of the employee.
These limitations describe a method and a system for observing, collecting, and analyzing information—activities that fall within the “mental processes” and “certain methods of organizing human activity” groupings of abstract ideas, specifically “managing social interactions, relationships, and strategies for influencing behavior”. These limitations, describe a method and a system for providing consumer sentiment analysis in order to further assist employees within a retail branch of a business to satisfy client needs. These are human/social interventions or generic information-processing strategies expressed at a high level and are therefore within established categories of abstract ideas (mental processes and methods of organizing human activity). The specification (e.g., ¶0008) supports this characterization by disclosing “Systems and techniques described herein may be used to determine customer sentiment as customers enter a retail branch of a business” as well as “Certain needs of the customer can be predicted based on facial recognition or other user input indictive of sentiment. Sentiment can be used separately or in combination with compliance data or other data available to business employees at the branch.”
Step 2A Prong 2: For independent claims 1, 15 and 19, The judicial exception is not integrated into a practical application because the claims and their additional feature element(s) of one or more processors (claim 15), one or more systems (claim 15), a device (claim 15), and a display (claim 15), individually and in combination, merely are used as a tool to perform the abstract idea (refer to MPEP 2106.05(f)). These element features including the computer used are recited at a high level of generality and are performed generally to apply the abstract idea without placing any limits on how these steps are performed distinctively from generic computer components and without having each function to generally “apply it” to a computer. See MPEP 2106.05(f). Thus, the additional elements do not apply, rely on, or use the abstract idea in a meaningful way beyond linking it to a generic computing environment.
Step 2B: For independent claims 1, 15 and 19, the claims are evaluated to determine whether they recite additional elements that amount to significantly more than the judicial exception (e.g., an inventive concept). As indicated in the Step 2A Prong 2 analysis, the additional element(s) in the claims amount to no more than mere instructions to apply the exception using generic computer components and a general link to a field of use. Mere instructions to apply an exception using generic computer components and a general link to a field of use cannot provide an inventive concept. The same analysis applies here in 2B analysis and does not provide an inventive concept.
Regarding the Dependent claims, these claims cover or fall under the same abstract idea of a method of organizing human activity and mental processes. They describe additional limitations steps of:
Claims 2 – 14, 16 – 18, and 20 – 21: further describes the abstract idea of the method for identifying and analyzing a customer as well as their mood based on facial recognition and voice recognition, predicting a customer need based on regulatory data, as well as generating a sales recommendation. Thus, being directed to the abstract idea group of mental processes as these functions encompass observation, evaluation, judgment, and opinion and can be performed mentally or in pen and paper.
Step 2A Prong 2 and Step 2B: For dependent claims, these claims do not include additional elements, but further instruct one to practice the abstract idea by using general computer components that merely are used as a tool. Thus, it amounts no more than mere instructions to apply the exception using a generic computer component (MPEP 2106.05(f)). Therefore, these claim limitations amount to no more than mere instructions to apply the exception using generic computer components and or computing technologies (e.g., that are merely deployed to be used as a tool; see MPEP 2106.05(f)). Additionally, these elements and their limitations are “merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application” (MPEP 2106.05(h)).
Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Therefore, claims 1 – 21 are rejected under 35 U.S.C. § 101 for being directed to an abstract idea without sufficient integration into a practical application, and the additional elements do not add significantly more than the judicial exception.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1 – 4, 8 – 13, and 15 - 21 are rejected under 35 U.S.C. 102 as being unpatentable over Davis (U.S. Pub No. 20170337602 A1).
Regarding claims 1 and 19:
Davis discloses:
detecting presence of a customer at a geographic location associated with an institution; [¶0023]: The customer recognition system is paired with a camera that picks up live feed of an institution having the capabilities of detecting customers and their facial expression type.
determining, using processing circuitry, a customer sentiment of the customer, at the geographic location, prior to interaction of the customer with an employee of the institution based on analysis of a characteristic of the customer; [Fig. 1; ¶¶0080 and 0081]: The customer recognition system is paired with a camera that picks up live feed of an institution having the capabilities of detecting customers and their facial expression type.
generating, based on the determining, a customer-specific interaction recommendation for interacting with the customer at the geographic location, during an interaction with the employee of the institution; [¶¶0090, 0092-0094]: Upon reading customer behavior via the live camera feed, the customer recognition system is able to predict customer needs based on pre-interaction and post-interaction with an employee.
rendering a dashboard for display on a user interface, the dashboard including the customer- specific interaction recommendation and [¶¶0093 and 0097]: recommendation information is prepared for presentation on the merchant device and/or customer facing device.
displaying the dashboard on the user interface of a display-of the employee. [¶0093]: recommendation information is displayed on the merchant device.
Regarding claims 2 and 16:
Davis discloses:
identifying the customer based on facial recognition. [¶0023]: The customer recognition system is paired with a camera that picks up live feed of an institution having the capabilities of detecting customers and their facial expression type.
Regarding claims 3 and 17:
Davis discloses:
wherein the characteristic includes on at least one of a facial expression, a gait, or a pace of the customer. [¶0023]: The customer recognition system is paired with a camera that picks up live feed of an institution having the capabilities of detecting customers and their facial expression type.
Regarding claim 4:
Davis discloses:
wherein the customer sentiment is detected based on direct input by the customer. [¶0033]: The customer recognition system has the capabilities of communicating directly with the customer via a customer client device in order to detect a customer’s needs.
Regarding claim 7:
Davis discloses:
predicting a customer need based upon regulatory data or a change in regulatory data. [¶0060 -0061]: Trust levels, both binary or multi-level, may be assigned to users based on a plethora of factors, such as age. Accordingly, certain trust levels may be required for a customer to purchase a certain category of product.
Regarding claim 8:
Davis discloses:
wherein the recommendation includes a sales recommendation. [¶0033]: The customer recognition system is paired to a merchant system which notifies and allows merchants to act upon a customer’s needs. Alternatively, [¶0038]: “Examples of merchants include, but are not limited to, merchants providing a specific category of product, merchants providing a broad variety of products, merchants having physical as well as virtual stores, and merchants having only physical stores.”
Regarding claim 9:
Davis discloses:
wherein generating the recommendation includes providing data indicators to a display of an employee of the institution. [¶0036]: The merchant system includes a plethora of in-store customer information and is also paired with a live digital camera to allow merchants to further assist a customer within a location. Additionally, [¶0068]: “The notification can include the image of the customer and the location of the secured customer display to allow the merchant employee to quickly and efficiently provide assistance to the customer.”
Regarding claim 10:
Davis discloses:
wherein detecting customer sentiment includes implementing an artificial intelligence (AI) algorithm. [¶0058]: The customer recognition system may utilize machine learning and/or neural network techniques.
Regarding claim 11:
Davis discloses:
wherein training of the Al algorithm is based on historical interactions with the customer or similar customers. [¶0159]: “the social networking system 802 may determine coefficients using machine-learning algorithms trained on historical actions and past user responses, or data farmed from users by exposing them to various options and measuring responses.”
Regarding claim 12:
Davis discloses:
wherein the geographic location comprises a retail location. [¶0021]: The customer recognition system is implemented within brick-and-mortar locations of an institution.
Regarding claim 13:
Davis discloses:
providing recommendations for subsequent or future interactions. [¶0155]: A coefficient is measured within a social networking system that determines a user’s future actions based on their prior interactions.
Regarding claim 15:
Davis discloses:
a device configured to detect presence of a customer at a geographic location associated with an institution; [¶0023]: The customer recognition system is paired with a camera that picks up live feed of an institution having the capabilities of detecting customers and their facial expression type.
a processor coupled to the device and configured to determine customer sentiment of the customer prior to interaction of the customer with an employee of the institution based on an analysis of a characteristic of the customer; and a [Fig. 1; ¶0023]: The customer recognition system is paired with a camera that picks up live feed of an institution having the capabilities of detecting customers and their facial expression type. Alternatively, [¶0103]: The customer recognition system may be paired to at least one processor.
a display coupled to the processor and configured to provide customer-specific interaction recommendations for interacting with the customer at the geographic location during an interaction with the institution. [¶0033]: Upon reading customer behavior via the live camera feed, the customer recognition system is able to predict customer needs based on pre-interaction and post-interaction with an employee.
wherein the processor is further configured to render a dashboard for display on a user interface, the dashboard including the customer-specific interaction recommendation; and [¶0123]: An I/O interface allows the system to transmit data and present output to a user. Alternatively, [¶0103]: The customer recognition system may be paired to at least one processor.
wherein the display is further configured to display the dashboard on the user interface of a display of the employee. [¶0123]: An I/O interface allows the system to transmit data and present output to a user.
Regarding claim 18:
Davis discloses:
including memory for storing customer history and regulatory data, and wherein the processor is configured to generate the recommendation further based on at least one of the customer history and the regulatory data. [¶0121]: The computing device can comprise of a memory to store necessary information from the customer recognition system.
Regarding claim 20:
Davis discloses:
wherein the operations further include identifying the customer based on facial recognition, and wherein determining customer sentiment is based on customer history of the identified customer. [¶0023]: The customer recognition system is paired with a camera that picks up live feed of an institution having the capabilities of detecting customers and their facial expression type. Further, [¶0159]: trains a machine-learning algorithm based on past user responses and interactions.
Regarding claim 21:
Davis discloses:
the non-transitory computer-readable medium of claim 19, wherein the operations include receiving video or photographic information of the customer and wherein the characteristic includes at least one of a facial expression, a gait, or a pace of the customer provided in the video or photographic information. [¶0125]: A non-transitory computer readable medium is embodied and executable by a variety of computing devices. [¶0023]: The customer recognition system is paired with a camera that picks up live feed of an institution having the capabilities of detecting customers and their facial expression type.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 5 – 6 and 14 are rejected under 35 U.S.C. 102 as being unpatentable over Davis (U.S. Pub No. 20170337602 A1) in view of Vaculin (U.S. Pub No. 20190348063 A1).
Regarding claim 5:
Davis does not disclose identifying a customer based on voice. Thus, Vaculin teaches:
identifying the customer based on voice. [¶0047 - 0048]: A recognition unit is configured to pick up conversation data as well as a speech recognition software component.
It would have been obvious to one of ordinary skill in the art before the earliest effective filing date of the claimed invention to modify the customer recognition system of Davis to further identify and/or analyze the customer based on voice, as taught by Vaculin, in order to improve the accuracy, reliability, and flexibility of customer recognition and customer-service assistance.
Regarding claim 6:
Davis does not disclose wherein the characteristic includes a vocal characteristic indicative of a mood of the customer. Thus, Vaculin teaches:
wherein the characteristic includes a vocal characteristic indicative of a mood of the customer. [¶0047 - 0048]: A recognition unit is configured to pick up conversation data as well as a speech recognition software component. Additionally, Davis also teaches an analysis unit with the capabilities to identify tone of voice from audio data in order to characterize the conversation.
It would have been obvious to one of ordinary skill in the art before the earliest effective filing date of the claimed invention to modify the customer recognition system of Davis to further identify and/or analyze the customer based on voice, as taught by Vaculin, in order to improve the accuracy, reliability, and flexibility of customer recognition and customer-service assistance.
Regarding claim 14:
Though Davis discloses a system for providing recommendations to user’s based on their previous interactions, Davis does not explicitly disclose providing recommendations to a user with similar habits/interactions as another customer. Thus, Vaculin teaches:
providing recommendations for interacting with other customers similar to the customer. [¶0021]: The suggestion system compares data to individuals within the same circumstance/situation in order to provide an answer that may resolve a customer’s concern.
It would have been obvious to one of ordinary skill in the art before the earliest effective filing date of the claimed invention to modify the customer recognition system of Davis to further predict a customer’s needs based on regulatory data change, as taught by Vaculin, in order to improve the accuracy, reliability, and flexibility of customer recognition and customer-service assistance.
Pertinent Art
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Palmer (US20190114569 A1) is pertinent because it is directed to “managing communications and more specifically to systems and methods for generating and managing proactive and intelligent communications.”
Maikhuri (US20240054430 A1) is pertinent because it is directed to “interactions between humans and machines, such as computerized devices, systems, and methods for monitoring and responding to various interactions and actions of a user, via an automated, intelligent personal agent.”
Freedman (US8204884 B2) is pertinent because it is directed to “data analysis storage, retrieval and analysis, in general and to a method, apparatus and system for capturing and analyzing customer interactions including customer and business experience, intelligence and content, in particular.”
Hazy (US20210042854 A1) is pertinent because it is directed to “data analysis and feedback technologies, interactive communication technologies, sensor technologies, mobile device technologies, distributed ledger technologies, monitoring technologies, organizational behavior technologies, optimization technologies, machine learning technologies and more particularly, to a system and method for providing technology-supported-trusted-performance feedback and experiential learning, while ensuring that a user's data remains private to that user.”
Tran (US20180253840 A1) is pertinent because it is related to “image analysis and pattern recognition with a mirror.”
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Bill Chen whose telephone number is (571)270-0660. The examiner can normally be reached Monday - Friday 8:30am - 5:00pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Nathan Uber can be reached on (571) 270-3923. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BILL CHEN/Examiner, Art Unit 3626
/NATHAN C UBER/Supervisory Patent Examiner, Art Unit 3626
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