DETAILED ACTION
1. The present application, filed on or after March 13, 2013, is being examined under the first inventor to file provisions of the AIA .
This is a first Continuation application with a claim of priority to a co-pending parent Application No. 18/609,691, filed March 19, 2024. Priority is also claimed to provisional application no. 63/499,620, filed May 2, 2023. However, this claim of priority is provisionally denied, subject to Applicant’s arguments, as this provisional is substantially different from the current Application.
NOTE: Interviews are encouraged at any stage of prosecution, especially in this case since this is a continuation of a related co-pending parent application.
Please use the AIR form, the link for which is found at the end of this Action, for scheduling an interview if such is desired.
Response to Amendment
2.. An Amendment was filed May 11, 2026 (hereinafter “Amendment”) and has been entered into the record and fully considered. The Amendment was filed in response to a Non-Final Rejection dated February 12, 2026.
Despite the Amendment to the Claims and Applicant’s remarks, the Rejections set forth in the Non-Final Rejection are hereby maintained; although, the Rejection under §103 is based on new grounds necessitated by the Amendment.
An explanation of the maintained Rejections and a response to Applicant’s arguments are set forth below. Please see the “Conclusion” section of this Action below for important information regarding responding to this Action.
The IDS’s filed in this Application on May 13, 2026, and March 16, 2026, have been considered.
The provisional double patenting Rejection in the Non-Final Rejection is hereby WITHDRAWN in view of the new claims set forth in the Amendment.
STATUS OF CLAIMS:
In the Amendment, Claims 1 – 55 were cancelled and Claims 56 – 76 were added as new Claims.
Thus, Claims 56 – 76 are pending and examined below. The pending Claims are substantially different from previous claim sets. Nevertheless, the Rejections set forth under the Non-Final Rejection are maintained as explained below.
Objection to the Dependent Claims
Each one of the dependent Claims is objected to as depending from a cancelled Claim.
Correction is required.
Claim Rejections – 35 USC § 101
3. 35 USC § 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture and composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
A. Rejection Based on Abstract Idea
Claims 56 - 76 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without significantly more. Furthermore, this rejection is based on the 2019 Revised Patent Subject Matter Eligibility Guidance (2019 PEG).
B. Statutory Categories
Independent Claim 56 is a method claim and therefore falls into the statutory category of a “process.” Claim 63 is a system claim which recites various computer hardware components such as a processor and a memory and it therefore falls into the statutory category of “machine/manufacture.” Claim 70 is a non-transitory CRM Claim and therefore falls into the category of “machine/manufacture.”
C. The Claim Recites an Abstract Idea
Claim 56 is illustrative of the rejection of all claims on the grounds of abstract idea.
Claim 56 recites the limitation:
“receiving event data from a plurality of event sources; collecting the event data in an event hub with a plurality of microservices, wherein at least a first microservice of the plurality of microservices supports a first type of software and at least a second microservice of the plurality of microservices supports a second type of software;.”
This limitation, as drafted, is a process that, under its broadest reasonable interpretation, constitutes a method of organizing human activity, specifically, fundamental economic principles or practices. That is, analyzing this limitation in the context of the claim as a whole, it recites a process that falls within the grouping of abstract ideas comprising certain methods of organizing human activity. Fundamental economic principles or practices are examples of such methods. In this case, the fundamental economic principle or practice is the common practice of collecting event data and transaction data for processing in a microservices type architecture.
This practice occurs millions of times every day.
Furthermore, the mere nominal recitation of a “processor” or “server” or “computing device” or “interface” does not remove the claim from the category of common or abstract methods of organizing human activity. These terms are recited at such a high level of generality as to not alter the designation of reciting an abstract idea.
Thus, Claim 56 recites a judicial exception, namely, an abstract idea.
D. The Claim Does Not Integrate the Abstract Idea into a Practical Application
Moreover, this judicial exception is not integrated into a practical application. The possible “additional limitations” recited in the Claim that must be considered are as follows:
interpreting the event data with a plurality of topic listeners by:
identifying one or more risk signals based on the event data; and
creating or updating one or more composite risk signals based on the event data and the one or more risk signals by:
analyzing the event data using one or more internal logic rules to determine if the one or more composite risk signals need to be triggered or updated;
forming a plurality of discrete source signals based on the event data;and
aggregating the plurality of discrete source signals to create or update the one or more composite risk signals;
generating one or more additional risk signals using machine learning based on the one or more composite risk signals and the event data by:
providing the one or more risk signals and the one or more composite risk signals to a machine learning model as input data;
training or updating the machine learning model with training data, wherein the training data includes the event data, one or more risk factors, and one or more series of event data or risk factors;
determining, by the machine learning model, patterns in the training data; and generating the one or more additional risk signals based on the patterns in the training data and the input data and using the machine learning model;
transmitting the one or more risk signals, the one or more composite risk signals, and the one or more additional risk signals to a fraud application, the fraud application configured to make a judgment using internalized business logic; and
generating a transaction alert, indicating that a fraudulent activity has occurred, based on the judgment made by the fraud application.
1. Lack of Computer Components and Interaction Among Same
No additional computerized components are mentioned in these limitations. The only computer terms are recited only at a high level of generality. No other particular computer functions or computer component interactions within this system are recited. The few computer-related limitations are wholly generic in nature and are recited at such a high level of generality as to not provide any meaningful limitations on the claim.
The Claim merely recites at a high level the use of a microservices architecture to monitor (e.g. “listen”) event data and transaction data and generate a combined or aggregated risk score for purposes of raising an alert of potential fraud. The use of machine learning is recited at an extremely high level or generic manner. These computerized functions are extremely common. These are high level, broad and abstract concepts. Furthermore, the claim lacks concrete assignments of specific functions among these various components. One example of such concrete assignment is to assign, in the claim, certain functions to specific components and recite them as interacting in specific ways. This is not the case with this Claim.
2. No Technical Solution to a Technical Problem
Analyzing these additional limitations individually, and taking the claim as a whole and as an ordered combination, it is clear that these additional limitations do not serve to integrate the abstract idea into a practical application. They do not recite a technological solution to a technological problem. They do not improve the functioning of the computer system itself or represent an improvement to any technology or technical field. In fact, there are very few computerized system components or functions recited.
Thus, these limitations fail to recite with specificity any technical function or any improvement to the functioning of the computer system itself. Therefore, the claim lacks the specificity required to transform the claim from one claiming only an outcome or a result – generating an alert of potential fraud - to one claiming a specific way of achieving that outcome or result. See MPEP §2106.04(d)(I); 2106.04(d)(1); 2106.05(a)
3. The Claim Recites Mere Instructions to Apply the Abstract Idea
The recitation of these generic components amounts to no more than mere instructions “to apply” the abstract idea exception using generic computer components. It is clear that the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. Furthermore, the claim invokes computers or other machinery merely as a tool to perform an existing process.
As noted above, the only possible computer components are recited at a high level of generality. This means that the abstract idea can be applied to an extremely general field of devices and systems. A claim having broad applicability across many fields of endeavor does not provide meaningful limitations that integrate a judicial exception into a practical application or amount to significantly more. For instance, a claim that generically recites an effect of the abstract idea exception, or claims every mode of accomplishing that idea, amounts to a claim that is merely adding the words "apply it" to the abstract idea. See MPEP §2106.05(f)
Accordingly, the additional elements or limitations listed above do not integrate the abstract idea into a practical application because they do not impose any meaningful limitations on practicing the abstract idea. That is, the additional elements recited in the claim beyond the judicial exception(s) have been evaluated to determine whether those additional elements, considered individually and in combination, integrate the judicial exception(s) into a practical application. They do not.
E. Step 2B: The Claim Does Not Recite Significantly More than the Abstract Idea
This step involves the search for an “inventive concept.” However, it is clear from the case law and the MPEP that the considerations at issue are the same as those considered above with respect to the analysis of a practical application. See MPEP 2106.05(a) – (c) and (e). In other words, these analyses sharply overlap.
Therefore, based on the above analysis, the identified additional limitations do not provide “significantly more” than the abstract idea. The claim is therefore ineligible under §101. The other independent claims are, likewise, ineligible for the same reasons as they are virtually identical to Claim 29.
F. The Dependent Claims Do Not Recite Meaningful Additional Limitations
Similarly, Claim 57 recites the same abstract idea as Claim 56 by virtue of its dependency on Claim 56. Like Claim 56, this claim does not recite sufficient additional elements to integrate the abstract idea into a practical application. Claim 57 merely recites the abstract concept of software formats.
Claim 58 merely recites the abstract concept of increasing the amount of event data.
Claim 59 merely recites the abstract concept of publishing event data to the event hub.
Claim 60 merely recites the abstract concept of publishing event data directly to the hub.
Claim 61 merely recites the abstract concept of collecting event data from an existing database.
Claim 62 merely recites the abstract concept of types of events.
Claims 63 – 76 are virtually identical or analogous variations to various of the aforementioned claims and are ineligible for the same reasons as set forth above.
None of these claims provide any additional meaningful limitations, non-generic computer components, or specific assignments of functionality among those components. Likewise, if at all, these claims recite only generic, computer-related limitations which are recited at such a high level of generality as to be devoid of any meaningful Limitations. These limitations do not recite improvements in the functioning of the computer or to any other technology or technical field.
Therefore, these claims do not include additional elements that are sufficient to integrate the abstract idea into a practical application, nor do they amount to significantly more than the recited abstract idea because the additional elements, when considered both individually and as an ordered combination, constitute only a mere instruction to “apply” the abstract idea.
Thus, Claims 56 - 76 constitute ineligible subject matter under 35 USC § 101 as being directed to an abstract idea without more.
NEW GROUNDS OF REJECTION:
Claim Rejections - 35 USC § 103
4. 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 of this title, 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 56 – 76 are rejected under 35 U.S.C. §103 as being unpatentable over U.S. Patent Publication No. 2024/0338439 to Golkar et al. (hereinafter “Golkar”) in view of U.S. Patent Application No. 2024/0154993 to Andriukhin et al. (hereinafter “Andriukhin”).
The Golkar reference is in the same field of endeavor as the claimed invention – the detection of fraud by monitoring both events and transactions and generating a composite or aggregated risk score and then generating alerts.
The title is: System and method for signal processing for cyber security
Golkar teaches as follows in the Abstract:
“System and method for signal processing for cyber fraud detection are disclosed. The method may include: receiving a trigger signal for fraud detection, the trigger signal comprising an event indicator and entity data associated with an entity profile stored in a database; determining, based on the trigger signal, a risk signal processing model comprising a plurality of risk components, each risk component associated with a respective weighing factor; computing, based on the risk signal processing model, a respective risk signal for each of the plurality of risk components; processing the respective risk signal for each of the plurality of risk components in real time or near real time to generate an aggregated risk signal; and generating, based on the aggregated risk signal, a fraud or cyber security alert signal.” (Emphasis Added)
The purpose of Golkar is on point with the claimed invention - to monitor – i.e. “listen” – for risk signals relating to events and transactions and generate a composite score for purposes of generating an alert signal.
Thus, Golkar addresses the problem of fraud in the same manner as the claimed invention – by storing event signals including transactions in an entity profile database and monitoring future signals associated with that profile:
“[0004] For example, for a hospital or a government agency operating one or more databases storing individual tax records, user accounts may be compromised by cyberattacks, and one or more fraudsters may leverage the stolen information to further transfer private information or financial fund out of the user accounts. There is a need to have real-time signal processing for assessment and validation of one or more digital events, including online transactions, in order to effectively prevent cyber attacks and identity fraud.
[0005] In one embodiment, there is provided a system for online fraud detection. The system comprises at least one processor, and a memory storing instructions which when executed by the at least one processor configure the at least one processor to identify and categorize components of a transaction activity, identify a dataset that links known malicious activity to metrics, identify metrics used to detect abnormal behaviour in the transaction activity, define a range of values for risk scores for each category, determine values for each metric for a digital risk score for each category, define a range of values to indicate a high and low risk for an overall risk score, and combine values from each category.
[0006] In a further embodiment, the processor may receive a trigger signal for fraud detection. The trigger signal may be one or more of an event indicator and entity data associated with an entity profile stored in a database. The trigger signal may be automatically generated by one or more predetermined event. The predetermined event may be one of: an electronic money transfer, an access request from an external party, a credit history request. The entity profile may be associated with a user account providing access to one or more digital assets. In a further embodiment, the one or more digital assets may be one or more of: digital assets, digital currency, encrypted user data, financial assets, and credit history.” (Emphasis Added)
Moreover, the use of external data as well as event data (i.e. collected during online “sessions” and transactions is well illustrated in Fig. 3:
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Golkar teaches the use of machine learning to generate the aggregated score: see at least Fig. 1 and 0030, 0053.
Furthermore, the use of a microservices architecture is also taught: see at least Fig. 4 and 0108 – 0118. Note the configuration of a “central hub” 410 – referred to as a STOPR - and a layer of “containers” 420, which would clearly indicate to a person of ordinary skill in the art that a microservices architecture is enabled and favored. Note further that both “sign-in attempts” – i.e. events – and transactions are monitored and pass through the hub or STOPR.
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Accordingly, with regard to Claim 1, as outlined above, Golkar in view of Andruikhin teaches:
Broadest reasonable interpretation:
The Claims of a patent application must be “given their broadest reasonable interpretation consistent with the specification.” See MPEP §2111. Under a broadest reasonable interpretation (BRI), words of the claim must be given their plain meaning, unless such meaning is inconsistent with the specification (e.g. the specification gives the term a special meaning). The plain meaning of a term means the ordinary and customary meaning given to the term by those of ordinary skill in the art at the relevant time.
Here, no specialized meaning is detected from the specification; therefore, the plain and ordinary meaning of the Claim terms will be given, with the possible exception of the claim term: “topic listeners,” which clearly refers to the tracking or monitoring of risk signals associated with events and transactions. (See at least 0036.)
Discussion of Cited References:
56. (New) A computer-implemented method, performed by one or more processors, comprising: (See at least Fig. 1)
receiving event data from a plurality of event sources; (See at least Fig. 4 and the sections quoted above. Fig. 3 also teaches that “external data” is received from a plurality of sources.)
collecting the event data in an event hub with a plurality of microservices, wherein at least a first microservice of the plurality of microservices supports a first type of software and at least a second microservice of the plurality of microservices supports a second type of software; (See at least Fig. 4 and the STOPR or hub as discussed above. Each of the “containers” 420 as quoted above are considered to constitute the recited term “microservices,” as set forth in 0110 – 0111. As to various software types, see 0045 - 0046)
interpreting the event data with a plurality of topic listeners by: (See at least 0112 - 0118.)
identifying one or more risk signals based on the event data; and (See at least 0111 – 0120)
creating or updating one or more composite risk signals based on the event data and the one or more risk signals by: (See at least 0121 and the entire section entitled “Digital Risk Score Aggregation.”)
analyzing the event data using one or more internal logic rules to determine if the one or more composite risk signals need to be triggered or updated; (See at least 0063 and 0080 – 0082)
forming a plurality of discrete source signals based on the event data; (See at least Fig. 4 and 0082 – 0088.)
and aggregating the plurality of discrete source signals to create or update the one or more composite risk signals; (See at least 0121 and the entire section entitled “Digital Risk Score Aggregation.”)
generating one or more additional risk signals using machine learning based on the one or more composite risk signals and the event data by: (See at least Fig. 1 and 0030, 0043.)
providing the one or more risk signals and the one or more composite risk signals to a machine learning model as input data; (See at least Fig. 1)
training or updating the machine learning model with training data, wherein the training data includes the event data, one or more risk factors, and one or more series of event data or risk factors; (See at least 0094.)
determining, by the machine learning model, patterns in the training data; and (See at least 0044 – 0048.)
generating the one or more additional risk signals based on the patterns in the training data and the input data and using the machine learning model; (See at least 0052.)
transmitting the one or more risk signals, the one or more composite risk signals, and the one or more additional risk signals to a fraud application, the fraud application configured to make a judgment using internalized business logic; and (See at least Fig. 3 and accompanying description.)
generating a transaction alert, indicating that a fraudulent activity has occurred, based on the judgment made by the fraud application. (See at least 0011 – 0011.)
Therefore, Golkar appears to teach all of the essential limitations of Claim 56; however, out of an abundance of caution, Andriukhin is cited for its teachings related to a microservices architecture.
Thus, Andriukhin is in the same field of endeavor as the claimed invention and Golkar and solves the alleged fraud problem in the exact same manner – using a microservices architecture and logical rules applied to monitored signals:
The title is: Scalable reporting system for security analytics
The Abstract reads as follows:
“The disclosure includes systems and methodologies for managing and evaluating the security posture of microservices in software development environments. The system addresses the challenges of fragmented and time-consuming security management processes by providing a unified and automated approach. It includes an abstraction process that transforms and standardizes security data from multiple Application Security tools into a centralized platform. The abstraction process simplifies the complexity of managing security across diverse microservices and enables efficient risk assessment and mitigation strategies. By integrating historical data and leveraging forecasting analysis, the system predicts potential security risks and trends, facilitating proactive vulnerability identification and resolution. The system's automation capabilities reduce manual effort, minimize human error, and streamline the security management workflow. It promotes collaboration among development and security teams, enhances overall security, and contributes to the production of more secure and reliable software products.” (Emphasis Added)
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the signal processing system of Golkar, which teaches the use of containerized machine learning processes, to add the microservices architecture features of Andriukhin. The motivation to make this modification comes from Golkar. It teaches, as quoted and illustrated above, that a containerized approach is preferred. It would greatly enhance the efficiency and convenience of the system of Golkar to add the microservices features of Andriukhin.
With regard to Claims 57 – 62, Golkar in view of Andriukhin teaches:
57. (New) The method of claim 32, wherein the event data is received from the plurality of event sources in a plurality of software formats. (See at least Golkar: 0046.)
58. (New) The method of claim 32, wherein the number of microservices in the plurality of microservices may be increased to increase the amount of event data the plurality of microservices can process. (See at least 0049.)
59. (New) The method of claim 32, wherein at least one additional event source may be added to the plurality of event sources by publishing event data to the event hub. (See at least Figs. 3 and 4 and sections quoted above.)
60. (New) The method of claim 32, wherein the event data is collected in the event hub by configuring one or more upstream systems to publish the event data directly to the event hub. (See at least Fig. 4 and sections quoted above.)
61. (New) The method of claim 32, wherein the event data is collected in the event hub by implementing consumers that emit event data to the event hub by leveraging an existing repository in which the event data is already stored. (See at least Fig. 4 and 0006.)
62. (New) The method of claim 32, wherein the one or more composite risk signals include at least one of: a recent call, a recent login, a recent device enrollment, a recent demographic change, a recent email risk elevation, a recent device risk elevation, a recent confirmed fraud, a recent beneficiary change, a recent high value transaction, a presence on an internal hotfile, or a presence on a national shared database. (See at least 0013 and 0022.)
With regard to Claim 63, this claim is essentially identical to Claim 56 and is obvious for the same reasons as set forth in that claim.
With regard to Claim 64, this claim is essentially identical to Claim 57 and is obvious for the same reasons as set forth in that claim.
With regard to Claim 65, this claim is essentially identical to Claim 58 and is obvious for the same reasons as set forth in that claim.
With regard to Claim 66, this claim is essentially identical to Claim 59 and is obvious for the same reasons as set forth in that claim.
With regard to Claim 67, this claim is essentially identical to Claim 60 and is obvious for the same reasons as set forth in that claim.
With regard to Claim 68, this claim is essentially identical to Claim 61 and is obvious for the same reasons as set forth in that claim.
With regard to Claim 69, this claim is essentially identical to Claim 62 and is obvious for the same reasons as set forth in that claim.
With regard to Claim 70, this claim is essentially identical to Claim 56 and is obvious for the same reasons as set forth in that claim.
With regard to Claim 71, this claim is essentially identical to Claim 57 and is obvious for the same reasons as set forth in that claim.
With regard to Claim 72, this claim is essentially identical to Claim 58 and is obvious for the same reasons as set forth in that claim.
With regard to Claim 73, this claim is essentially identical to Claim 59 and is obvious for the same reasons as set forth in that claim.
With regard to Claim 74, this claim is essentially identical to Claim 60 and is obvious for the same reasons as set forth in that claim.
With regard to Claim 75, this claim is essentially identical to Claim 61 and is obvious for the same reasons as set forth in that claim.
With regard to Claim 76, this claim is essentially identical to Claim 62 and is obvious for the same reasons as set forth in that claim.
Response to Arguments
5. Applicant's arguments set forth in the Remarks section of the Amendment have been fully considered but they are not persuasive.
With regard to section 101 rejection, Applicant argues, in part, as follows:
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However, the current Rejection under §101 is not based on “mental process,” but rather on the basis of certain methods of organizing human activity, namely, fundamental economic principles or practices. Thus, Applicant’s arguments are moot.
With respect to §103, Applicant argues as follows:
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Applicant’s argument is curious. Applicant has completely cancelled all previous Claims and adds substantially different Claims – and then argues that the prior art cited against the cancelled Claims is inapplicable. Thus, the new grounds of Rejection – based on a combination of completely new prior art references - is set forth above and renders Applicant’s arguments moot.
Conclusion
6. Applicant should carefully consider the following in connection with this Office Action:
A. Finality
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office Action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07. 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 extension fee 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 date of this final action.
B. Search and Prior Art
The search conducted in connection with this Office Action, as well as any previous Actions, encompassed the inventive concepts as defined in the Applicant’s specification. That is, the search(es) included concepts and features which are defined by the pending claims but also pertinent to significant although unclaimed subject matter. Accordingly, such search(es) were directed to the defined invention as well as the general state of the art, including references which are in the same field of endeavor as the present application as well as related fields (e.g. use of a combined or aggregated fraud score comprised of both events and transactions). Indeed, there is a plethora of prior art in these fields.
Therefore, in addition to prior art references cited and applied in connection with this and any previous Office Actions, the following prior art is also made of record but not relied upon in the current rejection:
U.S. Patent Publication No.2019/0333069 to Noble et al. This reference relates to the concept of microservices.
U.S. Patent Publication No. 2024/0144275 to Ammatanda et al. This reference relates to the concept of a depot where event data is published by the tenants of a microservices.
C. Responding to this Office Action
In view of the foregoing explanation of the scope of searches conducted in connection with the examination of this application, in preparing any response to this Action, Applicant is encouraged to carefully review the entire disclosures of the above-cited, unapplied references, as well as any previously cited references. It is likely that one or more such references disclose or suggest features which Applicant may seek to claim. Moreover, for the same reasons, Applicant is encouraged to review the entire disclosures of the references applied in the foregoing rejections and not just the sections mentioned.
D. Interviews and Compact Prosecution
The Office strongly encourages interviews as an important aspect of compact prosecution. Statistics and studies have shown that prosecution can be greatly advanced by way of interviews. Indeed, in many instances, during the course of one or more interviews, the Examiner and Applicant may reach an agreement on eligible and allowable subject matter that is supported by the specification.
Interviews are especially welcomed by this examiner at any stage of the prosecution process. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool (e.g. TEAMS). To facilitate the scheduling of an interview, the Examiner requests the use of the AIR form as follows:
USPTO Automated Interview Request http://www.uspto.gov/interviewpractice.
Other forms of interview requests filed in this application may result in a delay in scheduling the interview because of the time required to appear on the Examiner's docket. Thus, the use of the AIR form is strongly encouraged.
E. Communicating with the Office
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM BUNKER whose telephone number is (571)272-0017. The examiner can normally be reached on M - F 8:30AM - 5:30PM, Pacific.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Abhishek Vyas, can be reached at 571-270-1836. Information regarding the status of an application, whether published or unpublished, may be obtained from the “Patent Center” system. For more information about the Patent Center system, see https://patentcenter.uspto.gov/
/William (Bill) Bunker/
U.S. Patent Examiner
AU 3691
(571) 272-0017 - office
william.bunker@uspto.gov
August 27, 2026
/ABHISHEK VYAS/Supervisory Patent Examiner, Art Unit 3691
Prosecution Insights