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 .
The office action is in response to the application filed on May 19, 2023.
Claims 1-19 are pending and have been examined. Claims 1-19 are rejected.
Response to Amendment
This office action is final and in response to the amendment filed on July 06, 2026, which was in response to the non-final office action mailed April 03, 2026.
The objection of Claim 19 for being a substantial duplicate of claim 10 has been withdrawn as a result of claim 19 being cancelled. The 35 USC § 112(b) rejections on claims 4-7 have been addressed, resolved, and therefore withdrawn.
Claims 1, 4-7, and 10 have been amended.
Claims 1-18 are pending and have been examined. Claims 1-18 are rejected.
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 therefore, subject to the conditions and requirements of this title.
Claims 1-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
Step 1: The claim does not fall within one of the four statutory categories of
invention (process, machine, manufacture, or composition of matter), or,
Step 2: The claim recites a judicial exception, e.g. an abstract idea, without
reciting additional elements that amount to significantly more than the judicial
exception, as determined using the following analysis:
Step 2A, Prong 1: Does the claim recite an abstract idea, law of nature, or
natural phenomenon?
Step 2A, Prong 2: Does the claim recite additional elements that
integrate the judicial exception into a practical application?
Step 2B: Does the claim recite additional elements that amount to significantly
more than the judicial exception?
MPEP 2106.04(a)(2)(I) states: "The mathematical concepts grouping is defined as
mathematical relationships, mathematical formulas or equations, and mathematical
calculations.”
MPEP 2106.04(a)(2)(III) states: "Accordingly, the "mental processes" abstract idea
grouping is defined as concepts performed in the human mind, and examples of mental
processes include observations, evaluations, judgements, and opinions
Further, the MPEP states: "The courts do not distinguish between mental processes that
are performed entirely in the human mind and mental processes that require a human to use a
physical aid (e.g. pen and paper or a slide run) to perform the claim limitation.
Using the two-step inquiry, it is clear that Claims 1-19 are each directed to non-statutory subject matter as shown below:
Please note the following:
The following groups of claims are expressed in different statutory categories:
Claims 1-9 are directed to a method for providing a virtual twin model for the formation of a digital twin linked to a specific entity.
Claims 10-18 are directed to a system comprising of an interactive voice response system (IVR), an electronic database, and a processor configured to carry out a process for providing a virtual twin model for the formation of a digital twin linked to a specific entity.
With respect to Claims 1 and 10, which are independent claims with identical claim limitations:
Step 1: Claim 1 is directed to a method, also known as a process, which is one of the four statutory categories of patentable subject matter. Claims 10 and 19 are directed to a system for providing a virtual twin model for the formation of a digital twin linked to a specific entity, corresponding to an article of manufacture, which is one of the four statutory categories of patentable subject matter.
Step 2A, Prong 1: A judicial exception is recited in the claims as they recite mental processes, which are abstract ideas:
“A method for providing a virtual-twin model of an individual, said virtual-twin model for use with an Interactive Voice Response (IVR) system and for implementing as part of a bot, the method utilizing a computer processor and one or more non-transitory computer-readable media storing computer executable instructions, the instructions that implement the virtual-twin model, the method comprising: deriving legacy e-mail information from an electronic database, said e-mail information associated with an individual team member selected from an entity team;”; Deriving/mining legacy email information associated with an individual team member selected/pinpointed/denoted from an entity team is an abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion) -See MPEP § 2106.04(a)(2)(III).
“flagging a plurality of relevant components from the legacy e-mail information, said plurality of relevant components comprising response information corresponding to future voice overs for using in simulating a voice of the individual team member selected from the entity team;”; Flagging a plurality of relevant components pertaining to simulating future voiceovers from the legacy e-mail information is an abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion) -See MPEP § 2106.04(a)(2)(III).
“and identifying a future voice over opportunity to replace the voice of the team member selected from the entity team,”; Identifying a future voice over opportunity to replace the voice of the selected team member from the entity team is an abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion) -See MPEP § 2106.04(a)(2)(III).
Step 2A, Prong 2: The claims do not recite additional elements that integrate the judicial exception into a practical application:
“transmitting said flagged plurality of relevant components to the bot for updating the virtual-twin model;”; Transmitting flagged relevant components to a bot is considered insignificant extra-solution activity (mere data gathering) - See MPEP 2106.05(g).
“and implementing the plurality of flagged components with respect to said future voice over opportunity for the team member selected from an entity team; said implementing comprising using the flagged components in responding to the future voice over opportunity for the team member selected from an entity team.”; Implementing the plurality of flagged components with respect to said future voice over opportunities for the team member selected from an entity team only amounts to "apply it" and the mere instructions to implement an abstract idea on a computer - See MPEP 2106.05(f)(1).
Step 2B: The claims do not recite additional elements that amount to significantly more than the judicial exception. Transmitting flagged relevant components to a bot constitutes as receiving or transmitting data over a network, e.g., using the internet to gather data and has been recognized as well‐understood, routine, and conventional when claimed in a generic manner." - See MPEP 2106.05(d)(II). Implementing the plurality of flagged components with respect to said future voice over opportunities for the team member selected from an entity team amounts to "apply it" and mere instructions to implement an abstract idea on a computer. The claim limitation fails to recite details of how a solution or outcome to a problem is accomplished because it is unclear how the "AI system" or "machine learning" is used nor does the specification make it clear how these actions are performed - See MPEP 2106.05(f)(1)).
Therefore, Claims 1 and 10 are directed to non-statutory subject matter and rejected.
With respect to Claims 2 and 11, which have identical claim limitations and are dependent upon Claims 1 and 10 respectively:
Step 2A, Prong 1: The claim incorporates the abstract idea of the independent claim. Step 2A, Prong 2: The claims do not recite additional elements that integrate the judicial exception into a practical application:
“The method of claim 1 further comprising instantiating the plurality of flagged components as extended reality (XR)-fully-assembled graphical language binary files.”; Instantiating flagged components as XR graphical language binary files is considered insignificant extra-solution activity (selecting a particular data source to be manipulated) - see MPEP 2106.05(g), in addition to generally links the use of the abstract idea to a particular technological environment or field of use - See MPEP § 2106.05(h).
Step 2B: Instantiating flagged components as XR-fully-assembled graphical language binary files is considered insignificant extra-solution activity specifically selecting a particular data source to be manipulated - see MPEP 2106.05(g). It also generally links the use of the abstract idea (instantiating flagged components as XR-fully-assembled graphical language binary files) to a particular technological environment or field of use (VR/3D-visualization) - see MPEP § 2106.05(h).
Therefore, Claims 2 and 11 are directed to non-statutory subject matter and rejected.
With respect to Claims 3 and 12, which have identical claim limitations and are dependent upon claims 1 and 10 respectively:
Step 2A, Prong 1: A judicial exception is recited in the claims as they recite mental processes, which are abstract ideas:
“The method of claim 1 wherein the flagging the plurality of relevant components from the legacy e-mail information comprises flagging based on sentiment analysis of the plurality of relevant components from the legacy e-mail information,”; Flagging a plurality of relevant components from the legacy e-mail information based on sentiment analysis is an abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion) -See MPEP § 2106.04(a)(2)(III).
Step 2A, Prong 2: The claims do not recite additional elements that integrate the judicial exception into a practical application:
“and tuning the response information corresponding to future voice overs based, at least in part, on the sentiment analysis.”; Tuning the response information corresponding to future voice overs based on sentiment analysis only amounts to "apply it" and the mere instructions to implement an abstract idea on a computer - see MPEP 2106.05(f)(1)
Step 2B: The claims do not recite additional elements that amount to significantly more than the judicial exception. Tuning the response information based on sentiment analysis amounts to "apply it" and mere instructions to implement an abstract idea on a computer. The claim fails to recite details of how a solution or outcome to a problem is accomplished because it is unclear how the "AI system" or "machine learning" is used nor does the specification make it clear how these actions are performed - see MPEP 2106.05(f)(1)).
Therefore, Claims 3 and 12 are directed to non-statutory subject matter and rejected.
With respect to Claims 4 and 13, which have identical claim limitations and are dependent upon Claims 1 and 10 respectively:
Step 2A, Prong 1: A judicial exception is recited in the claims as they recite mental processes, which are abstract ideas:
“The method of claim 1 wherein a formation of the virtual-twin model comprises, at least in part, the flagging the plurality of relevant components from the legacy e-mail information.”; Forming a digital twin based on the flagging of a plurality of relevant components from legacy e-mail information is an abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion) -See MPEP § 2106.04(a)(2)(III).
Step 2A, Prong 2: The claims do not recite additional elements that integrate the judicial exception into a practical application:
Step 2B: The claims do not recite additional elements that amount to significantly more than the judicial exception.
Therefore, Claims 4 and 13 are directed to non-statutory subject matter and rejected.
With respect to Claims 5 and 14, which have identical claim limitations and are dependent upon Claims 1 and 10 respectively:
Step 2A, Prong 1: A judicial exception is recited in the claims as they recite mental processes, which are abstract ideas:
“The method of claim 1 further comprising tagging the virtual-twin model to a specific entity.”; Tagging the digital twin to a specific entity is an abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion) -See MPEP § 2106.04(a)(2)(III).
Step 2A, Prong 2: The claims do not recite additional elements that integrate the judicial exception into a practical application:
Step 2B: The claims do not recite additional elements that amount to significantly more than the judicial exception.
Therefore, Claims 5 and 14 are directed to non-statutory subject matter and rejected.
With respect to Claims 6 and 15, which have identical claim limitations and are dependent upon Claims 5 and 14 respectively:
Step 2A, Prong 1: The claim incorporates the abstract idea of the independent claim. Step 2A, Prong 2: The claims do not recite additional elements that integrate the judicial exception into a practical application:
“The method of claim 5 further comprising using the virtual-twin model to form unique sequences of information associated with the specific entity.”; Using the digital twin to form unique sequences of information associated with a specific entity only amounts to "apply it" and the mere instructions to implement an abstract idea on a computer - See MPEP 2106.05(f)(1) in addition to generally links the use of the abstract idea to a particular technological environment or field of use - See MPEP § 2106.05(h).
Step 2B: Using the digital twin to form unique sequences of information associated with a specific entity amounts to "apply it" and mere instructions to implement an abstract idea on a computer. The claim fails to recite details of how a solution or outcome to a problem is accomplished because it is unclear how the "AI system" or "machine learning" is used nor does the specification make it clear how these actions are performed - see MPEP 2106.05(f)(1)). The usage of a digital twin to form unique sequences of information associated with a specific entity is generally linked to a particular technological environment or field of use (AI/ML) - see MPEP 2106.05(h).
Therefore, Claims 6 and 15 are directed to non-statutory subject matter and rejected.
With respect to Claims 7 and 16, which have identical claim limitations and are dependent upon Claims 1 and 10 respectively:
Step 2A, Prong 1: A judicial exception is recited in the claims as they recite mental processes, which are abstract ideas:
“The method of claim 1 further comprising indexing the virtual-twin model based on generated metadata tags.”; Indexing the digital twin based on generated metadata tags is an abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion) -See MPEP § 2106.04(a)(2)(III).
Step 2A, Prong 2: The claims do not recite additional elements that integrate the judicial exception into a practical application:
Step 2B: The claims do not recite additional elements that amount to significantly more than the judicial exception.
Therefore, Claims 7 and 16 are directed to non-statutory subject matter and rejected.
With respect to Claims 8 and 17, which have identical claim limitations and are dependent upon Claims 7 and 16 respectively:
Step 2A, Prong 1: A judicial exception is recited in the claims as they recite mental processes, which are abstract ideas:
“The method of claim 7 wherein the metadata tags are configured to correspond to an initial response flag, said initial response flag being formed using the flagging the plurality of relevant components.”; Flagging the plurality of relevant components to form initial response flags is an abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion) -See MPEP § 2106.04(a)(2)(III).
Step 2A, Prong 2: The claims do not recite additional elements that integrate the judicial exception into a practical application:
Step 2B: The claims do not recite additional elements that amount to significantly more than the judicial exception.
Therefore, Claims 8 and 17 are directed to non-statutory subject matter and rejected.
With respect to Claims 9 and 18, which have identical claim limitations and are dependent upon Claims 1 and 10 respectively:
Step 2A, Prong 1: The claim incorporates the abstract idea of the independent claim. Step 2A, Prong 2: The claims do not recite additional elements that integrate the judicial exception into a practical application:
“The method of claim 1 further comprising bridging the response information, said bridging using an internet gateway, from a wearable device to a plurality of cloud-based extended reality (XR) servers.”; Bridging the response information using an internet gateway is considered insignificant extra-solution activity (mere data outputting) - See MPEP 2106.05(g).
Step 2B: Bridging the response information using an internet gateway constitutes as receiving or transmitting data over a network, e.g., using the internet to gather data and has been recognized as well‐understood, routine, and conventional when claimed in a generic manner." - See MPEP 2106.05(d)(II)
Therefore, Claims 9 and 18 are directed to non-statutory subject matter and rejected.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
Claims 1, 3-6, 9, 10, 12-15, 18 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Ghosh et. Al, (U.S Patent Application Publication No. US20230308544A1 filed on March 22, 2022, hereinafter “Ghosh”), in view of Hodges et. Al, (U.S Patent Application Publication No. US20180375947A1 filed on June 22, 2018, hereinafter “Hodges”).
With respect to Claim 1:
Ghosh teaches:
“flagging a plurality of relevant components from the legacy e-mail information, said plurality of relevant components comprising response information corresponding to future voice overs for using in simulating a voice of the individual team member selected from the entity team;” (Paragraph [0003] teaches identifying/flagging preferences (relevant components) from the user data that was obtained in order to determine a context/reason (potential future voiceover response related information) to make an IVRS call (response), “The embodiment may further include identifying one or more preferences of the user from the historical data. The embodiment may also include in response to determining the user is occupied, identifying a context of an issue requiring an IVRS call.” Paragraph [0032] discloses that the digital twin associated with the individual can simulate a response, “Referring now to FIGS. 2A and 2B, an operational flowchart for simulating an IVRS call with a digital twin agent of a user in a digital twin agent IVRS call simulation process 200 is depicted according to at least one embodiment.” Paragraph [0033] further teaches gathering individual related characteristics that can develop a digital twin with voice simulation capabilities, “The data relating to the characteristics of the user may include, but is not limited to, physical characteristics (e.g., age, gender, height, hair color, and/or eye color) and social characteristics (e.g., tone of voice...)”) Examiner’s Note: Due to insufficient clarification in the specification of this disclosure, for examination purposes under BRI, "relevant components" has been interpreted as anything that could facilitate and assist in the development of a digital twin.
“transmitting said flagged plurality of relevant components to the bot for updating the virtual-twin model;” (Paragraph [0045] teaches the transmission of individual-related data to a bot for updating the virtual-twin model that will be used to create a digital twin, “IoT devices 118 having this capability may transmit the data directly to the IVR simulation program 110A, 110B via inter-process communication.” Paragraph [0036] discloses that a digital twin can be constructed using relevant components associated with an individual, “According to at least one other embodiment, the digital twin may be built by the IVR simulation program 110A, 110B using known techniques. Similarly, in this embodiment, the digital twin may be built to accurately reflect the user in accordance with the characteristics of the user and the historical data.” Paragraph [0043] depicts updating the virtual-twin model in accordance with one of the individual’s preferences (relevant components), “but may nevertheless want their digital twin agent to interact with the IVRS anyway. In this embodiment, the user may update their status as "occupied".”)
“and identifying a future voice over opportunity to replace the voice of the team member selected from the entity team,” (Paragraph [0015] teaches identifying a context of an issue that could prompt an IVRS call (future voice over opportunity), “and in response to determining the user is occupied based on the data relating to the activities of the user, a context of an issue requiring an IVRS call associated with the IVRS may be identified based on data from one or more internet of things (IoT) devices. Upon identifying the context, the IVRS call may be initiated with the digital twin.” Paragraph [0015] further teaches that said future voice over opportunity can replace the voice of the individual/user/team member at hand, “Upon identifying the context, the IVRS call may be initiated with the digital twin agent representing (i.e., taking the place of) the user…” Paragraph [0031] further discloses that representation/replacement of user/team member includes dynamic activation i.e. (voice representation/interactions), “the IVR simulation program 110A, 110B may be a program capable of receiving data relating to characteristics of the user, activities of the user, and historical data relating to prior IVRS calls, creating a digital twin agent of the user, initiating an IVRS call with the digital twin agent representing the user in interactions with the IVRS, dynamically activating the digital twin agent of the user when the user is busy, seamlessly switching between the digital twin agent and the user…”)
“and implementing the plurality of flagged components with respect to said future voice over opportunity for the team member selected from an entity team; said implementing comprising using the flagged components in responding to the future voice over opportunity for the team member selected from an entity team.” (Paragraph [0046] teaches utilizing the context of the issue (flagged relevant components) as a means of determining what necessitates a call (responding to a future voiceover opportunity) which results in a call being initiated, “The IVR simulation program 110A, 110B, upon identifying the context of the issue requiring the IVRS call, may utilize IVRS profiling and online resources to identify the customer care…Then, at 212, the IVR simulation program 110A, 110B initiates the IVRS call with the digital twin agent representing the user. As used herein, "representing the user" means the digital twin agent takes the place of the user during the IVRS call.”)
Ghosh does not appear to explicitly disclose:
“A method for providing a virtual-twin model of an individual, said virtual-twin model for use with an Interactive Voice Response (IVR) system and for implementing as part of a bot, the method utilizing a computer processor and one or more non-transitory computer-readable media storing computer executable instructions, the instructions that implement the virtual-twin model, the method comprising: deriving legacy e-mail information from an electronic database, said e-mail information associated with an individual team member selected from an entity team;”
“team member selected from the entity team;”
However, Hodges teaches:
“A method for providing a virtual-twin model of an individual, said virtual-twin model for use with an Interactive Voice Response (IVR) system and for implementing as part of a bot, the method utilizing a computer processor and one or more non-transitory computer-readable media storing computer executable instructions, the instructions that implement the virtual-twin model, the method comprising: deriving legacy e-mail information from an electronic database, said e-mail information associated with an individual team member selected from an entity team;” (Paragraph [0071] teaches obtaining information associated with an entity (individual) from a database, “That entity model 21 also receives entity data, if any, from the model datastore 25. As the data in the model datastore 25 changes as a result of new information from the entity data aggregator 28…” Paragraph [0080] further discloses that the information associated with the individual can encompass legacy e-mail types, “Communication-based information can include texts, voicemails, voice conversations, messages on messaging platforms such as Facebook MessengerTM and Apple’s iMessageTM, emails, social media posts and broadcasts, and other social media messaging including photos and direct messages.”)
“team member selected from the entity team;” (Paragraph [0047] discloses that principle users (individuals/individual team members/employees) co-exist within a primary entity (entity team) that is represented by this system, “it will usually be assumed that the primary entity is a business. However, as already noted that is not a requirement of the system 10…or to make use the output of the system 10. Such person or persons are referred to hereinafter as principle users if they represent the primary entity or secondary users if they represent the secondary entities.” Paragraph [0094] further denotes an instance where associated tasks pertaining to specifically selected team members of an entity team (primary entity employees) are dispersed and allocated, “…they can be presented selectively to certain primary entity employees or associates based on knowledge domain, seniority, or other role-based rules.” Paragraph [0103] further discloses selecting/determining a team member (specific employee) from the entity team (primary entity/business), “the primary entity is helped to determine whether a specific employee is over-performing or under performing in their ability to convert secondary entities into customers when handling conversations. Such insights can be given to the primary user, to that employee's manager, or to the employee himself. Feedback from the machine learning system 67…”)
Ghosh and Hodges are analogous art and in the same field of invention because both references pertain to the development of self-evolving digital twins for the improvement of real-time decision making. While Ghosh teaches flagging, transmitting, updating, identifying, and implementing the necessary elements needed to develop a digital twin, Hodges teaches the initial deriving/retrieval of the necessary elements. It would have been obvious to a person having ordinary skill in the art (PHOSITA) before the effective filing date of the claimed invention to implement a part of Claim 1 using the base reference of Ghosh (dynamic activation of a digital twin agent for IVRS related interactions) with the teachings of Hodges (building entity models derived from communication-based information) in order to personalize customer experiences to meet their needs, streamline accessibility to resources, and enhance overall productivity. One of ordinary skill in the art would be motivated to do so because by integrating Hodges' framework into the methods of Ghosh one would be able to, "better understand the impact of its communication-based information on itself and on its customers and partners {[0010] of Hodges}."
Therefore, Claim 1 is rejected.
With respect to Claim 10:
Ghosh teaches:
“flag a plurality of relevant components from the legacy e-mail information, said plurality of relevant components comprising response information corresponding to future voice overs;” (Paragraph [0003] teaches identifying/flagging preferences (relevant components) from the user data that was obtained in order to determine a context/reason (potential future voiceover response related information) to make an IVRS call (response), “The embodiment may further include identifying one or more preferences of the user from the historical data. The embodiment may also include in response to determining the user is occupied, identifying a context of an issue requiring an IVRS call.” Paragraph [0032] discloses that the digital twin associated with the individual can simulate a response, “Referring now to FIGS. 2A and 2B, an operational flowchart for simulating an IVRS call with a digital twin agent of a user in a digital twin agent IVRS call simulation process 200 is depicted according to at least one embodiment.”) Examiner’s Note: Due to insufficient clarification in the specification of this disclosure, for examination purposes under BRI, "relevant components" has been interpreted as anything that could facilitate and assist in the development of a digital twin.
“transmit said flagged plurality of relevant components to the bot for updating a virtual-twin model;” (Paragraph [0045] teaches the transmission of individual-related data for updating the virtual-twin model that will be used to create a digital twin, “IoT devices 118 having this capability may transmit the data directly to the IVR simulation program 110A, 110B via inter-process communication.” Paragraph [0036] discloses that a digital twin can be constructed using relevant components associated with an individual, “According to at least one other embodiment, the digital twin may be built by the IVR simulation program 110A, 110B using known techniques. Similarly, in this embodiment, the digital twin may be built to accurately reflect the user in accordance with the characteristics of the user and the historical data.” Paragraph [0043] depicts updating the virtual-twin model in accordance with one of the individual’s preferences (relevant components), “but may nevertheless want their digital twin agent to interact with the IVRS anyway. In this embodiment, the user may update their status as "occupied".”)
“identify a future voice over opportunity for use in substituting for the individual team member selected from an entity team;” (Paragraph [0015] teaches identifying a context of an issue that could prompt an IVRS call (future voice over opportunity), “and in response to determining the user is occupied based on the data relating to the activities of the user, a context of an issue requiring an IVRS call associated with the IVRS may be identified based on data from one or more internet of things (IoT) devices. Upon identifying the context, the IVRS call may be initiated with the digital twin.” Paragraph [0015] further teaches that said future voice over opportunity can be a substitution for the voice of the individual/user/team member at hand, “Upon identifying the context, the IVRS call may be initiated with the digital twin agent representing (i.e., taking the place of) the user…” Paragraph [0031] further discloses that representation/replacement/substitution of the user/team member includes dynamic activation i.e. (voice representation/interactions), “the IVR simulation program 110A, 110B may be a program capable of receiving data relating to characteristics of the user, activities of the user, and historical data relating to prior IVRS calls, creating a digital twin agent of the user, initiating an IVRS call with the digital twin agent representing the user in interactions with the IVRS, dynamically activating the digital twin agent of the user when the user is busy, seamlessly switching between the digital twin agent and the user…”)
“and implement the plurality of flagged components with respect to said future voice over opportunity; said implementing comprising using the flagged components in responding to the future voice over opportunity.” (Paragraph [0046] teaches utilizing the context of the issue (flagged relevant components) as a means of determining what necessitates a call (responding to a future voiceover opportunity) which results in a call being initiated, “The IVR simulation program 110A, 110B, upon identifying the context of the issue requiring the IVRS call, may utilize IVRS profiling and online resources to identify the customer care…Then, at 212, the IVR simulation program 110A, 110B initiates the IVRS call with the digital twin agent representing the user. As used herein, "representing the user" means the digital twin agent takes the place of the user during the IVRS call.”)
Ghosh does not appear to explicitly disclose:
“A digital twin system in electronic communication with a bot, said bot comprising an Interactive Voice Response system (IVR), the system comprising: a processor, an electronic database, for storing legacy e-mail information associated with an individual's individual team member's electronic communications, said individual team member being selected from an entity team;”
However, Hodges teaches:
“A digital twin system in electronic communication with a bot, said bot comprising an Interactive Voice Response system (IVR), the system comprising: a processor, an electronic database, for storing legacy e-mail information associated with an individual's individual team member's electronic communications, said individual team member being selected from an entity team;” (Paragraph [0070] teaches storing information associated with an entity (individual/selected team member from entity team) in a database, “Refer now to FIG.6 for a data flow 151 that shows how the entity data aggregator 28 aggregates data 103, 105, 107, 109, 111, 113, 115, 117 including communication-based information…The aggregated data is input into the model datastore 25 which stores that data to support future updating of the entity model 21.” Paragraph [0080] further discloses that the information associated with the individual/selected team member can encompass legacy e-mail types, “Communication-based information can include texts, voicemails, voice conversations, messages on messaging platforms such as Facebook MessengerTM and Apple’s iMessageTM, emails, social media posts and broadcasts, and other social media messaging including photos and direct messages.” Paragraph [0047] discloses that principle users (individuals/individual team members/employees) co-exist within a primary entity (entity team) that is represented by this system, “it will usually be assumed that the primary entity is a business. However, as already noted that is not a requirement of the system 10…or to make use the output of the system 10. Such person or persons are referred to hereinafter as principle users if they represent the primary entity or secondary users if they represent the secondary entities.” Paragraph [0094] further denotes an instance where associated tasks pertaining to specifically selected team members of an entity team (primary entity employees) are dispersed and allocated, “…they can be presented selectively to certain primary entity employees or associates based on knowledge domain, seniority, or other role-based rules.” Paragraph [0103] further discloses selecting/determining a team member (specific employee) from the entity team (primary entity/business), “incoming communication-based information with eventual outcomes the primary entity is helped to determine whether a specific employee is over-performing or under performing in their ability to convert secondary entities into customers when handling conversations. Such insights can be given to the primary user, to that employee's manager, or to the employee himself. Feedback from the machine learning system 67…”)
Therefore, Claim 10 is rejected.
With respect to Claims 3 and 12:
Ghosh does not appear to explicitly disclose:
“The method of claim 1 wherein the flagging based on sentiment analysis of the plurality of relevant components from the legacy e-mail information,”
“tuning the response information corresponding to future voice overs based, at least in part, on the sentiment analysis.”
However, Hodges teaches:
“The method of claim 1 wherein the flagging based on sentiment analysis of the plurality of relevant components from the legacy e-mail information,” (Paragraph [0098] discloses the relevancy of flagging being directly correlated with sentiment analysis, “In order to flag and correct anything that is incorrect or inaccurate; and for providing natural language processing in the form of a sentiment analyzer 61 which detects negative sentiments, confusion, or other signals that an auto-reply answer is not acceptable to the secondary entity.” Paragraph [0118] further discloses that the communication-based information (flagged relevant data) has already undergone sentiment analysis, “As noted above the system 10 applies sentiment analysis via the sentiment analyzer 61 to its communication-based information to determine topics driving positive or negative sentiment.”)
“tuning the response information corresponding to future voice overs based, at least in part, on the sentiment analysis.” (Paragraph [0098] teaches reviewing and correcting (tuning) the replies (response information) based on sentiment analysis, “which detects negative sentiments, confusion, or other signals that an auto-reply answer is not acceptable to the secondary entity and such that the reply answer can be escalated, reviewed, and possibly corrected by the primary user.”)
Therefore, Claims 3 and 12 are rejected.
With respect to Claims 4 and 13:
Ghosh does not appear to explicitly disclose:
“The method of claim 1 wherein a formation of the virtual-twin model comprises, at least in part, the flagging the plurality of relevant components from the legacy e-mail information.”
However, Hodges teaches:
“The method of claim 1 wherein a formation of the virtual-twin model comprises, at least in part, the flagging the plurality of relevant components from the legacy e-mail information.” (Paragraph [0080] discloses flagging/extracting relevant components from the communication information, “While the foregoing examples feature communications with customers, information relevant to building up the entity model 21 can be extracted from the primary entity's communications with others including employees, vendors, partners, potential employees, and other parties.” Paragraph [0073] further teaches forming an entity model (digital twin) based on this flagging, “The process 300 includes monitoring a plurality of user communications from secondary users of a particular entity (step 302). The process 300 then constructs or updates the entity model 21 based on that plurality of communications (step 304).” Paragraph [0084] also discloses making note of flagging additional relevant components prior to forming an entity model (digital twin), “From that the primary entity can determine that it should pay extra attention to related conversations when building up the entity model 21.”)
Therefore, Claims 4 and 13 are rejected.
With respect to Claims 5 and 14:
Ghosh does not appear to explicitly disclose:
“The method of claim 1 further comprising tagging the virtual-twin model to a specific entity.”
However, Hodges teaches:
“The method of claim 1 further comprising tagging the virtual-twin model to a specific entity.” (Paragraph [0455] discloses tagging conversations/communications used to develop digital twins to a primary entity (specific entity), “Tagging can be performed manually or automatically. Once tagged those conversations are used in the machine learning engine 67 which then learns the characteristics of each message and conversation.” Paragraph [0078] further discloses tagging a primary entity to an entity model (digital twin) that encapsulates information associated with said primary entity, “The entity model 21 encompasses many facts about the primary entity including who its customers and partners are, what matters to the primary entity, its customers and partners, and the tone, personality, and style that the primary entity wishes to convey. Such facts are applied to and extracted from the entity model 21 and are kept up to date by way of communication-based information that is applied to the system 10.”)
Therefore, Claims 5 and 14 are rejected.
With respect to Claims 6 and 15:
Ghosh does not appear to explicitly disclose:
“The method of claim 5 further comprising using the virtual-twin model to form unique sequences of information associated with the specific entity.”
However, Hodges teaches:
“The method of claim 5 further comprising using the virtual-twin model to form unique sequences of information associated with the specific entity.” (Paragraph [0023] teaches using the primary entity’s model (specific entity’s digital twin) to form unique responses (sequences of information) to a secondary entity, “sending a response to the at least one secondary entity from the primary entity, wherein the sent response is the automatically generated response or a primary user response. The process then continues by scoring the automatically generated response by determining if the sent response corresponds to the automatically generated response. The entity model is then updated based on the scoring.”)
Therefore, Claims 6 and 15 are rejected.
With respect to Claims 9 and 18:
Ghosh teaches:
“The method of claim 1 further comprising bridging the response information, said bridging using an internet gateway, from a wearable device to a plurality of cloud-based extended reality (XR) servers.” (Paragraph [0029] discloses the presence of cloud-based infrastructure in relation to bridging response information, “The server 112 may also operate in a cloud computing service model, such as Software as a Service (SaaS), Platform as a Service (PaaS), or Infrastructure as a Service (IaaS).” Paragraph [0030] teaches the utilization of augmented reality (AR) glasses as an example of a device that can bridge the transmitting/receiving of data over an internet gateway, “IoT Device 118 may be a wearable device (e.g., a smartwatch, AR glasses), IoT sensors in a smart home, a virtual assistant device, and/or any other IoT Device 118 known in the art for gathering information about the user and reporting technical issues that is capable of connecting to the communication network 114, and transmitting and receiving data with the client computing device 102 and the server 112.”)
Therefore, Claims 9 and 18 are rejected.
Claims 2 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Ghosh et. Al, (U.S Patent Application Publication No. US20230308544A1 filed on March 22, 2022, hereinafter “Ghosh”), in view of Hodges et. Al, (U.S Patent Application Publication No. US20180375947A1 filed on June 22, 2018, hereinafter “Hodges”), as applied to claims 1, 10, and 19 above, and in further view of Tu et. Al, (TwinXR: Method for using digital twin descriptions in industrial eXtended reality applications, published January, 2023, hereinafter “Tu”).
With respect to Claims 2 and 11:
The combination of Ghosh and Hodges does not appear to explicitly disclose:
“The method of claim 1 further comprising instantiating the plurality of flagged components as extended reality (XR)-fully-assembled graphical language binary files.”
However, Tu teaches:
“The method of claim 1 further comprising instantiating the plurality of flagged components as extended reality (XR)-fully-assembled graphical language binary files.” ([PG.4 Sec. 2.1.2 DT document layer paragraph. 1] teaches acquiring/instantiating parameter values (necessary flagged components), “These parameter values with DT features then flow to the XR application and are linked to other XR components, which eventually customize an instantiated application.” [PG.4 Sec. 2.1.2 DT document layer paragraph 2] further teaches instantiating digital twin related parameters and XR components that are unique to said digital twin whilst formatting them in YAML/JSON, “Under this standard, each DT document describes the metadata and features of a single DT in the format of YAML and JSON.”) Examiner’s Note: YAML/JSON file types are human-readable data serialization languages/formats that can include binary data forms/types as well as be used to represent XR graphical languages.
The combination of Ghosh and Hodges in addition to Tu are analogous art and in the same field of invention because all three references pertain to advancing digital twin models to be more efficient, immersive, scalable, and interoperable. Where Ghosh-Hodges teaches acquiring the necessary flagged components needed to compile training data for the virtual/digital-twin model but not representing the training data in a XR-graphical language binary file format, Tu teaches instantiating the flagged components of data as extended reality (XR)-fully-assembled graphical language binary files. It would have been obvious to a person having ordinary skill in the art (PHOSITA) before the effective filing date of the claimed invention to combine the base reference of Ghosh (dynamic activation of a digital twin agent for IVRS related interaction) with the teachings of Hodges (continuously updating entity models derived from communication-based information) and further with the teachings of Tu (leveraging the gap between digital twin technology and extended reality in the Metaverse) in order to optimize operational data-driven decision making, enhance performance monitoring, and facilitate remote collaboration to deliver better solutions. One of ordinary skill in the art would be motivated to do so because by integrating Tu's framework into the methods of Ghosh and Hodges one could, " achieve higher efficiency, scalability, interchangeability, and interoperability, which are fundamental characteristics of Industry 5.0 towards the Metaverse. The advantages of the TwinXR method are manifested in both directions: DTs optimize and scale XR application development, while TwinXR-compatible applications also unlock and demonstrate the potential of DTs for data interchange and system interoperation. {Page 10. Sec. 4.1 Synergies between DTs and XR of Tu}.”
Therefore, Claims 2 and 11 are rejected.
Claims 7, 8, 16, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Ghosh et. Al, (U.S Patent Application Publication No. US20230308544A1 filed on March 22, 2022, hereinafter “Ghosh”), in view of Hodges et. Al, (U.S Patent Application Publication No. US20180375947A1 filed on June 22, 2018, hereinafter “Hodges”), as applied to claims 1, 10, and 19 above, and in further view of Grehant, (U.S Patent Application Publication No. US20170193049A1 filed on December 30, 2016).
With respect to Claims 7 and 16:
The combination of Ghosh and Hodges does not appear to explicitly disclose:
“The method of claim 1 further comprising indexing the virtual-twin model based on generated metadata tags.”
However, Grehant teaches:
“The method of claim 1 further comprising indexing the virtual-twin model based on generated metadata tags.” (Paragraph [0093] discloses that the observation metadata used to train the digital models is what determines how the models are indexed, “Variables of the observations used to train each model are indexed in the form of metadata of the model. This means that models are searchable based on the values of the variables of the observations used to train them.” Paragraph [0094] further discusses the indexing of the digital twin, “such that each variable is referenced as an attribute of the model in the index, and each value on that variable corresponding to an observation used to train the model is listed in the values of that attribute.”)
The combination of Ghosh and Hodges in addition to Grehant are analogous art and in the same field of invention because all three references pertain to heightening the responsiveness and manageability of digital twins whilst reducing memory footprint and enabling rapid identification of data. Where Ghosh-Hodges teaches setting up the foundational composition of a self-evolving digital twin to provide actionable insight and personalized assistance, Grehant teaches indexing said digital twin to further simulate AI-driven customer support scenarios. It would have been obvious to a person having ordinary skill in the art (PHOSITA) before the effective filing date of the claimed invention to combine the base reference of Ghosh (dynamic activation of a digital twin agent for IVRS related interaction) with the teachings of Hodges (continuously updating entity models derived from communication-based information) and further with the teachings of Grehant (retrieving model outcomes in the course of an event) in order to tailor user experiences to provide traceability aspects, adaptive efficiency, and context-aware decisions-making. One of ordinary skill in the art would be motivated to do so because by integrating Grehant's framework into the methods of Ghosh and Hodges one could state, “An advantage of training a machine learning model on options evaluated by simulations, and indexing the machine learning model instead of indexing the simulation model, is that the machine learning model will generally be quicker to execute (to assess possible options) as compared to a full simulation. The advantage of pre-computing and indexing a machine learning model is that it is not necessary to train the model in the course of the action (thus saving time). {[0119] of Grehant}.”
Therefore, Claims 7 and 16 are rejected.
With respect to Claims 8 and 17:
The combination of Ghosh and Hodges does not appear to explicitly disclose:
“The method of claim 7 wherein the metadata tags are configured to correspond to an initial response flag, said initial response flag being formed using the flagging the plurality of relevant components.”
However, Grehant teaches:
“The method of claim 7 wherein the metadata tags are configured to correspond to an initial response flag, said initial response flag being formed using the flagging the plurality of relevant components.” (Paragraph [0028]-[0030] disclose the components that are related to (initial response flag), “[0028] providing variables of a first set of observations of similar events; [0029] providing a multiplicity of models; [0030] indexing the multiplicity of models with the variables of the first set of observations;” Paragraph [0053] teaches (metadata tagging), “indexing the multiplicity of models further comprises adding, for each model of the multiplicity, the values of all observations used to train the said each model in the metadata of the said each model of the multiplicity;” Paragraph [0073] teaches overall (flagging), “The observations and the target variables form (and are referred to as) a set of tagged data. It is to be understood that each target variables are accompanied of a value so-called target value.” Paragraph [0083] teaches the relevancy of observations (relevant components that are flagged), “the machine learning algorithm will learn to produce target values consistent with those of observations with which it was trained, in response to new observations similar to those with which it was trained.” Paragraph [0121] further teaches (relevant components), “For instance, models trained to assess abort modes will take in input observations that specify the abort mode (in one variable) and the context in which it is selected (in the other variables). It is the context that makes the abort mode relevant or not, and the relevance of each abort mode in their respective contexts is assessed by the outcome of the model when receiving the corresponding observations in input.”) Examiner’s Note: The observation data is used to generate outcomes/responses [Grehant 0048] as a result of training the model. In this case, the first set of observations used to generate a response correlate to an "initial response flag". This observation data is also denoted by variables and is referred to as tagged data which correlates to "metadata tagging". Thus, the "formation of this initial response flag" is done by "flagging relevant components" which is done by selecting/considering the input observations' context.
Therefore, Claims 8 and 17 are rejected.
Response to Arguments
Applicants’ arguments filed on July 06, 2026, have been fully considered but are not deemed to be fully persuasive as per Examiner’s discretion.
Claim Rejections - 35 USC § 101
A. Applicant argues that the examiner has significantly oversimplified the claimed invention by characterizing individual claim limitations in isolation as mental processes rather than evaluating the claimed invention as a whole. Applicant further argues that said limitations cannot practically be performed in the human mind because the embodiment “continuously updates a deployable virtual-twin model” and because the claims recite an electronic database, computer-readable media, a processor, a bot, IVR integration, and automated future voice-over implementation defining “an automated computer architecture that processes large volumes of legacy electronic communications”. Applicant further relies on Enfish v. Microsoft for the proposition that claims directed at improvements in computer technology are not abstract merely because they process information.
The examiner respectfully disagrees. The claims have been considered as a whole, consistent with MPEP § 2106. The rejection does not evaluate limitations in isolation but identifies the claim as a whole. Identifying the abstract idea recited by a claim is not the same as evaluating limitations in isolation; every element identified in the § 101 rejection above was considered, both individually and as an ordered combination, under Step 2A Prong 2 and Step 2B.
The argument that the volume of legacy e-mail data makes the process impractical to perform mentally is not persuasive. The “practically performed in the mind” inquiry considers whether the claimed concept in nature, is an observation, evaluation, or judgement not whether it could be performed instantaneously or at scale by an unaided human. See Bancorp Servs., LLC v. Sun Life Assurance Co., 687 F.3d 1266 (Fed. Cir. 2012); OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359 (Fed. Cir. 2015) (automating a process, including at scale, does not by itself confer eligibility). Nothing in Claim 1 or 10 precludes the recited “deriving”, “flagging”, and “implementing” steps from being performed as mental evaluation of communication content assisted by generic data-processing tools.
As to Enfish, the examiner reiterates that Enfish’s claims recited a specific self-referential table structure that improved database indexing and search functionality as a technical matter, thus the improvement was reflected in how the data structure itself was technically organized. Applicants’ claims recite no analogous technical data structure or architecture for the virtual-twin model. They recite the functional steps of deriving, flagging, transmitting, and implementing data, without specifying the technical means by which any of these operations are carried out. This places the claims with Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350 (Fed. Cir. 2016) (claims to collecting, analyzing, and using information remain abstract notwithstanding recitation of generic computer components), rather than with Enfish. MPEP § 2106.04(a)(2)(III)(B).
B. Applicant argues that the claims recite a specific computerized workflow (obtaining legacy communications, extracting response information, updating a virtual-twin model, identifying future voice-over opportunities, and automatically deploying the model through an IVR environment) and that this workflow is analogous to USPTO Example 46 (where extracted data is incorporated into a continuously-updated architecture deployed through specific computing components) and USPTO Example 42 (where collected information is transformed, stored, and utilized with a network-based system to perform a technological function), as well as 2024 AI Subject Matter Eligibility Examples, which recognize that AI-related inventions are not directed to an abstract idea merely because they involve collecting, processing, or analyzing data, where that processing is integrated into a practical technological application producing a real-world technological result.
The examiner respectfully disagrees. Example 46 is distinguishable because the claim held eligible in that example recited a specific technical improvement to the underlying digital-twin architecture itself (a rule-based diagnostic process tied to sensor data from a specific physical system, producing a technical diagnostic output that controlled a physical process). Here, the claims recite generic function steps, without reciting any comparable specific technical mechanism for how the virtual-twin model is constructed, how “relevant” components are technically identified, or how a “future voice over opportunity” is technically detected. The mere assertion that a “digital representation” is “created and maintained” does not, by itself, supply the technical specificity that distinguished the claim in Example 46.
Example 42 is likewise distinguishable and not applicable in this instance. Applicant’s claims recite the deployment of a virtual-twin model “through” generically-recited IVR, bot, XR, wearable-device, internet-gateway, and cloud-server environments – i.e. a field of use through which a generic output is delivered – rather than a technical integration comparable to example 42. MPEP § 2106.05(h) (limiting an abstract idea to a particular technological environment does not integrate the idea into a practical application). The 2024 AI Eligibility Examples do not alter this analysis; those examples confirm that AI-related claims remain eligible only where the claimed processing is tied to a specific technically described application producing a technical result.
C. Applicant argues that the invention does not “merely analyze or display information” but rather “creates and maintains” a deployable representation “used by computer systems…on behalf of a specific individual team member selected from an entity team” as amended.
The examiner respectfully disagrees. The amendment adding “individual team member selected from an entity team” narrows the field of use and subject matter of the data being processed (whose e-mail is being analyzed) without adding any new technical step to the claim. The claim recites the identical deriving/flagging/transmitting/identifying/implementing/ sequence before and after amendment. Narrowing the class of data processed, without a corresponding change to the technical operations performed on that data, is precisely field-of-use narrowing that MPEP § 2106.05(h) identifies as insufficient to integrate an abstract idea into a practical application.
D. Applicant argues the claimed sequence (deriving information from legacy communications, extracting response components, transmitting to a bot, updating the virtual-twin model, identifying future deployment opportunities, and implementing responses through an IVR framework) defines how the system operates and how the virtual-twin model is created, maintained, and deployed, such that the claims recite a specific implementation rather than a desired outcome, analogous to McRO, Inc v. Bandai Namco Games America Inc.
The examiner respectfully disagrees. In McRO, eligibility turned on the claims reciting a specific defined set of rules (mapped morph weights and time-based transition rules keyed to phoneme sequences) that replaced the subjective judgment of an animator with an unconventional, automated rule-based process – the rules themselves were the claimed technical improvement. Applicants’ claims recite no comparable rule set. “Flagging a plurality of relevant components” and “identifying a future voice over opportunity” describe the result to be achieved (identification of relevant content; identification of an opportunity) without reciting how relevance or opportunity is technically determined – no algorithm, decision criteria, scoring function, or rule structure is claimed. This is the generic “apply it” pattern the McRO claims were distinguished from, not the pattern McRO itself exemplifies. MPEP § 2106.04(d) (an improvement-based eligibility argument must be reflected in what is actually claimed, not merely asserted in the specification or remarks).
E. Applicant argues that claims 2 and 11’s recitation of “instantiating the plurality of flagged components as extended reality fully assembled graphical language binary files” constitutes a specific technological implementation enabling interoperability between communication-derived response data, virtual-twin architectures, and XR execution environments, and is therefore not insignificant extra-solution activity.
The examiner respectfully disagrees. Converting previously obtained data from one format into another (converting flagged content into a binary graphical-language file) is a data output/format conversion operation of type MPEP § 2106.05(g) identifies as insignificant extra-solution activity, regardless of whether the destination format is described as “XR” or “graphical”. No claimed detail explains any specific non-generic technical method for performing this conversion (e.g., a particular compression, encoding, or optimization technique) that would distinguish it from routine format conversion. A general assertion that the resulting format is “XR-compatible” does not, without more, establish a technological improvement; it identifies only the field of use (XR environments) to which generic format-converted data is applied. MPEP § 2106.05(h).
F. Applicant argues that claims 3 and 12’s recited sentiment analysis of legacy communications and the use of that analysis to tune future voice-over responses is not directed to a human evaluating emotion but rather is performed as part of the virtual-twin model contributing directly to the functionality of the virtual-twin environment.
The examiner respectfully disagrees. Evaluating the emotional tone or sentiment of communication content is a mental evaluation – the kind of subjective assessment a person routinely performs when reading some correspondence – and does not become technical merely because it is performed by a generic computer and its output is used to adjust a subsequent generic output. MPEP § 2106.04(a)(2)(III) (mental processes include observation, evaluation, judgement, and opinion, even when a generic computer is used to perform them). No claimed step recites a specific technical sentiment-scoring methodology (e.g., a particular linguistic model, feature set, or classifier architecture) that would remove this limitation from the mental process category.
G. Applicant argues, claim-by-claim that claims 4/13 define how the virtual-twin is generated from flagged response components, claims 5/14 establish machine association and retrieval functionality by tagging the twin to a specific entity, claims 6/15 improve operation of the virtual-twin framework by generating unique information sequences associated with a specific entity, claims 7/16 improve storage, retrieval, and accessibility through metadata-tag indexing, claims 8/17 provide digital indexing of response content through initial response flags, and claims 9/18 demonstrate a distributed computing environment and deployment architecture – bridging responses through wearable devise, internet gateways, and cloud-based XR servers – extending beyond a mental process.
The examiner respectfully disagrees as to each claim in this group. Claims 4/13 recite only that the virtual twin is formed “at least in part” from the flagging step already addressed above, this adds no further technical detail and is not persuasive for the reasons stated as to independent claims 1 and 10. Claims 5/14 and 6/15 (“tagging…to a specific entity” and “forming unique sequences of information associated with the specific entity”) recite generic database association/labeling operations, associating a record with an identifier and generating an identifier-linked data sequence is a well-understood, routine database function, not a technical improvement to a computer or network. MPEP § 2106.05(d)(II). Claims 7/16 and 8/17 (metadata-tag indexing) recite conventional indexed-database retrieval. Claims 9/18 (bridging response information via an internet gateway to cloud-based XR servers using a wearable device) recite the generic transmission and receipt of data over a network using off-the-shelf networking and cloud infrastructure, “bridging” data between conventional network nodes, without more, is well-understood, routine, and conventional activity and does not, by virtue of being described as a “distributed computing environment” become a technical improvement. MPEP § 2106.05(d)(II)/MPEP $ 2106.05(h).
H. Regarding Step 2B, the applicant argues that even if the claims recite an abstract idea, they include significantly more because they require a non-conventional combination of legacy e-mail mining, response-information extraction, virtual-twin generation, bot updating, IVR deployment, sentiment-based tuning, metadata indexing, XR implementation, internet-gateway bridging, and cloud-based XR server interaction – an ordered combination for which the Office has not established conventionality and that a conclusion that generic data transmission is conventional does not establish that the claimed ordered combination is conventional.
The examiner respectfully disagrees. As to the individual elements: generic data collection, evaluation, transmission, storage, and retrieval using conventional computer, database, and networking components are each independently well-understood, routine, and conventional, as discussed above with respect to each such element. MPEP § 2106.05(d)(II). As to the ordered combination: applicant’s claims combine these conventional elements in their ordinary expected sequence i.e. (data is collected, then evaluated, then transmitted for storage/model updating, then later retrieved and applied with no unconventional ordering, timing, or interaction among elements alleged or apparent. The Federal Circuit has recognized that an ordered combination of conventional elements performing their ordinary functions in their ordinary sequence does not supply the requisite inventive concept. See Alice Corp. v. CLS Bank Int’l, 573 U.S. 208, 225 (2014).
Therefore, the rejection of claims 1-18 under 35 U.S.C. § 101 are maintained.
Claim Rejections - 35 USC § 103
A. Applicant argues, the claim amendments make clear that the e-mail communications and flagged response components directly relate to, and are indicative of, the communication behavior of “an individual team member selected from an entity team,” and that this was already implicit from the term “responses” in the original claims but has now been made explicit.
The examiner acknowledges the amendment but respectfully disagrees. Under broadest reasonable interpretation, the limitation “individual team member selected from an entity team” does not add any functional claim step. It is a descriptive characterization of whose e-mail data is being processed. Making an explicit characterization of the data source does not, without a corresponding functional claim step, narrow the scope of the claim in a manner that avoids the prior art.
B. Applicant lists, claim elements (a) through (e) verbatim (see pg. 16-17 of applicant Arguments) and argues, Ghosh’s citations do not show or suggest said limitations.
The examiner respectfully disagrees. Individual claim limitations are met by Hodges, not Ghosh, and applicant’s remarks do not address Hodges’ disclosure of these elements entirely. Non-obviousness cannot be established by attacking references individually where a rejection is based on a combination of references. MPEP § 2145(IV); In re Keller, 642 F.2d 413 (CCPA 1981); In re Merck & Co., 800 F.2d 1091 (Fed. Cir. 1986).
Therefore, the rejection of claims 1-18 under 35 U.S.C. § 103 are maintained.
Conclusion
THIS ACTION IS MADE FINAL. 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 NOOR F CHEEMA whose telephone number is (571)272-9642. The examiner can normally be reached Monday-Friday 7:30am-5:00pm alternative Fridays off.
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/N.F.C./ Examiner, Art Unit 2142 /HAIMEI JIANG/Primary Examiner, Art Unit 2142
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