Prosecution Insights
Last updated: October 02, 2026
Application No. 18/841,846

Systems and Methods for Digitally Transforming Economic, Organizational and/or Industrial Content and/or Processes

Non-Final OA §103§112
Filed
Aug 27, 2024
Priority
Apr 29, 2022 — DE 10 2022 204 257.3 +1 more
Examiner
LHYMN, SARAH
Art Unit
2613
Tech Center
2600 — Communications
Assignee
Siemens Aktiengesellschaft
OA Round
1 (Non-Final)
66%
Grant Probability
Favorable
1-2
OA Rounds
3m
Est. Remaining
81%
With Interview

Examiner Intelligence

Grants 66% — above average
66%
Career Allowance Rate
369 granted / 560 resolved
+3.9% vs TC avg
Moderate +15% lift
Without
With
+15.0%
Interview Lift
resolved cases with interview
Typical timeline
2y 4m
Avg Prosecution
29 currently pending
Career history
590
Total Applications
across all art units

Statute-Specific Performance

§101
6.2%
-33.8% vs TC avg
§103
65.3%
+25.3% vs TC avg
§102
6.4%
-33.6% vs TC avg
§112
15.2%
-24.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 560 resolved cases

Office Action

§103 §112
DETAILED ACTION 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 . Claim Interpretation The following is a quotation of 35 U.S.C. 112(f): (f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph: An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof. The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked. As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph: (A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function; (B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and (C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function. Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function. Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function. Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “modules” in claim 1 (claimed to perform functions in claim 1; given structure in claim 5; but only in that claim 5). Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. Claim Rejections - 35 USC § 112(b) The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claims 1-8 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Claim 7 depends from independent claim 1, and recites: “wherein the recording language for generating a digital representation as the result of the data editing by the AI is selected from the programming languages BPMN, UML, and EPC.” However, there is no “ a data editing by the AI” recited in claim 1. So “the data editing” does not have antecedent basis, but also is unclear what the data editing refers to. The AI in claim 1 carries out: pattern analysis, pattern recognition and/or pattern prediction. Is this “data editing” (of which, the pattern analysis, recognition and/or prediction reasonably does not correspond to data editing). In any event, it is unclear what claim 7 refers to in claim 1. When reviewing Applicant’s 08/27/2024 preliminary amendment to the claims, it appears that Applicant deleted “data editing” from claim 1, but did not make similar deletion to claim 7. For examination purposes, claim 7 will be interpreted that generating a digital representation is selected from one of the 3 claimed programming languages. The dependent claims inherit the indefiniteness of claim 1. Clarification and correction are required. Claims 9-14 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Independent claim 9 recites, in part: communicating the AI-developed solutions and/or questions and any digital representations present to a processor However, there is no “an AI-developed solutions and/or questions” recited earlier in claim. Therefore, in addition to antecedent basis issues, it is unclear what these solutions and/or questions are from. The step prior to this was “editing the processed user-specific data with the AI”. Also, by “any digital representations” – what also does this refer to? The edited content? Also, what is the difference between “AI-developed solutions” and “digital representations”? More indefiniteness in claim 9: displaying the AI-developed proposals of digital representations to the users. This is the final step of 9, “the AI-developed proposals…” also lacks antecedent basis. Claim 9 is missing words necessary to understand what all of the steps are. For examination purposes, the examiner is interpreting the communicating step of claim 9 to communicate to the user the final product (digital representation), and/or questions to the user. The remaining claims inherit the indefiniteness. Clarification and correction are required. Claims 9, 10, 13 and 14 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Claim 9 has yet another indefiniteness issue. Independent claim 9 recites, in part: generating user-specific data with corresponding modules; processing the user-specific data for feeding into a neural network having an Artificial Intelligence (AI); editing the processed user-specific data with the AI Claim 10 (which depends from claim 9), recites: the method as claimed in claim 9, carried out at the same time as capturing and/or recording the user-specific data. Claims 9 and 10 respectfully have the following indefiniteness issues: In claim 10, what is carried out at the same time? All of the method of claim 9? Only part of claim 9? In claim 10, there is no “capturing and/or recording” in claim 9. So, there is antecedent basis issues, and indefiniteness issues. Should this be “generating”? Claim 10 needs to be amended to clarify not just what is being carried out at the same time, but in view of the way claim 9 is written, and assuming claim 10 should have read “generating” instead of “capturing and/or recording”, it seems that the user-specific data actually needs to have been captured, recorded or generated, such that the processing, editing, communicating and displaying steps can be done (basically, for the rest of the steps to be performed). So, for the capturing, recording or generating to be done “at the same time”, did Applicant respectfully intend to mean that *new* or *additional* user-specific data can be captured or recorded, etc., while *previously* captured or recorded data is being processed in the steps of claim 9? If this is the case, the claims require amendment to remove the indefiniteness. For examination purposes, claim 10 is being interpreted that new or additional user-specific data can be captured or recorded or generated, while previously obtained user-specific data is processed, per claim 9. Clarification and correction are respectfully required; the dependent claims inherit the indefiniteness of claim 9. Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claim(s) 1, 5 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Schaefer (U.S. Patent App. Pub. No. 2021/0073530 A1). Regarding claim 1: Schaefer teaches: a system (claim 9, system) for automatically transforming economic, organizational and/or industrial content and/or processes capturable by natural language into a digital representation (claim 9, system can transform an encoded image comprising a handwritten drawing into a digital structured model; see also para. 12, in one non-limiting example, the handwritten drawing can be a business process sketch), the system comprising: one or more modules for capturing and/or recording user- specific data (e.g. para. 12, whiteboard, or para. 46, microphone) ; a first processor (claim 9, at least one of the “one or more processors”) to process captured data (claim 9, para. 24, to digitally encode an image) for forwarding (para 24, the digitally encoded image can be sent/forwarded); a first interface from the first processor to a second processor (claim 9, at least one of the “one or more processors”, in combination with para. 24, receipt by wired, wireless and/or any other type of connection, teaches interface between processors) associated with a neural network having an Artificial Intelligence (AI) trained to carry out pattern analysis, pattern recognition, and/or pattern prediction on the basis of the processed user- specific recording data (Fig. 1: 112, machine learning components, which includes features shown in Fig. 2. Fig. 2: 210, 220, 230, teach pattern analysis, recognition and/or prediction. And see Fig. 3, which teaches that Fig. 2: 210 can be a trained neural network); and a second interface to transmit results from the second processor to the first processor to generate a digital representation made available to the user via a display module (para. 24, interfaces and first processor as also mapped above, in combination with claim 9 and Fig. 1: 104, digital structured model (digital representation) is generated, which can be viewed via Fig. 8: 840 display). It would have been obvious for one of ordinary skill in the art to have further modified the applied reference(-s), in view of same, to have obtained the above, and the results of the modification would have been obvious and predictable to one of ordinary skill in the art as of the effective filing date of the claimed invention. See MPEP §2143(A). That is, to modify the system of Schaefer such that it employs two processors (taught by Schaefer), in the communication manner as mapped above. Such a modification is within the purview of one of ordinary skill, and is taught by Schaefer as at least one system environment to practice the teachings of Schaefer. The prior art included each element recited in claim 1, although not necessarily in a single embodiment, with the only difference being between the claimed element and the prior art being the lack of actual combination of certain elements in a single prior art embodiment, as mapped and described above. One of ordinary skill in the art could have combined the elements as claimed by known methods, and in that combination, each element merely performs the same function as it does separately. One of ordinary skill in the art would have also recognized that the results of the combination were predictable as of the effective filing date of the claimed invention. Regarding claim 5: Schaefer teaches: the system as claimed in claim 1, wherein one of the one or more modules comprises: a microphone, a camera, and/or a whiteboard (e.g. para. 12, whiteboard, or para. 46, microphone). It would have been obvious for one of ordinary skill in the art, as of the effective filing date of Applicant’s claims, to have further modified the applied references, in view of same, to have obtained the above, motivated to allow users ability to capture data for processing. Regarding claim 8: Schaefer teaches: the system as claimed in claim 1, wherein the user-specific data comprise one or more existing digital representations (claim 9, the user-specific data can be a digitally encoded image of a handwritten diagram). It would have been obvious for one of ordinary skill in the art, as of the effective filing date of Applicant’s claims, to have further modified the applied references, in view of same, to have obtained the above, motivated to facilitate image processing. Claim(s) 2, 3 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Schaefer in view of Zhang (U.S. Patent App. Pub. No. 2023/0343002 A1). Regarding claim 2: The applied reference(-s) to claim 1 do not proactively teach claim 2. Consider the following. In analogous art, Zhang teaches: the system as claimed in claim 1, wherein the first processor has a program for optical character recognition (para. 65, using OCR for text recognition, in a system analogous to Schaefer). It would have been obvious for one of ordinary skill in the art, as of the effective filing date of Applicant’s claims, to have further modified the applied references, in view of same, to have obtained the above, motivated to make use of known methods to recognize text input. Regarding claim 3: Zhang teaches: the system as claimed in claim 1, wherein the first processor has a program for voice recognition (para. 92). It would have been obvious for one of ordinary skill in the art, as of the effective filing date of Applicant’s claims, to have further modified the applied references, in view of same, to have obtained the above, motivated to make use of known methods to enable user input. Regarding claim 6: Zhang teaches: the system as claimed in claim 1, wherein the AI is connected to a cloud via a programming interface (para. 7, cloud system or para. 43, cloud-based computing, or par. 65, cloud vision API). It would have been obvious for one of ordinary skill in the art, as of the effective filing date of Applicant’s claims, to have further modified the applied references, in view of same, to have obtained the above, motivated to make use of known methods to store and retain data. Claim(s) 4 is rejected under 35 U.S.C. 103 as being unpatentable over Schaefer in view of Li (CN113220885A) (all citations to English language machine translation made available with this Office Action). Regarding claim 4: The applied reference(-s) to claim 1 do not teach claim 4. Consider the following. In analogous art, Li teaches: the system as claimed in claim 1, wherein the first processor has a program for mood analysis (page 5, natural language processing (“NLP”) in artificial intelligence includes what Applicant claims as “mood analysis”. This is described in the context of economic/financial moods. See also page 6, NLP for semantic understanding and public opinion analysis). It would have been obvious for one of ordinary skill in the art, as of the effective filing date of Applicant’s claims, to have further modified the applied references, in view of same, to have obtained the above, motivated to make use of known methods of natural language processing to better process same. Claim(s) 7 is rejected under 35 U.S.C. 103 as being unpatentable over Schaefer in view of Schäfer, B., & Stuckenschmidt, H. (2021, September). DiagramNet: hand-drawn diagram recognition using visual arrow-relation detection. In International Conference on Document Analysis and Recognition (pp. 614-630). Cham: Springer International Publishing (“Schafer”). Regarding claim 7: It would have been obvious for one of ordinary skill in the art to have further modified the applied reference(-s), in view of same, to have obtained: the system as claimed in claim 1, wherein the recording language for generating a digital representation as the result of the data editing by the AI is selected from the programming languages BPMN, UML, and EPC, and the results of the modification would have been obvious and predictable to one of ordinary skill in the art as of the effective filing date of the claimed invention. See MPEP §2143(A). Schafer, related to hand-drawn diagram recognition (Abstract) teaches BPMN as a recording language for generating digital representations using AI (Schafer, see e.g. p 615, hdBPMN dataset; Sections 3.1, 3.3, 4). Modifying the applied reference(-s), in view of Schafer, to have included BPMN as a recording language, as a known modeling language, when processing natural language inputs, per both Schaefer and Schafer, is all of taught and suggested by the prior art, with additional motivation to incorporate a modeling language known to users. One of ordinary skill in the art could have combined the elements as claimed by known methods, and in that combination, each element merely performs the same function as it does separately. One of ordinary skill in the art would have also recognized that the results of the combination were predictable as of the effective filing date of the claimed invention. Claim(s) 9, 10 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Schaefer in view of Jin (U.S. Patent App. Pub. No. 2019/0146998 A1). Regarding claim 9: Schaefer teaches: a method for transforming natural language content into a digital representation in an automated manner (claim 1), the method comprising: generating user-specific data (claim 1, handwritten diagram) with corresponding modules (modules: Schaefer, para. 12, whiteboard); processing the user-specific data for feeding into a neural network having an Artificial Intelligence (AI) (Schaefer, claim 1, digitally encoding the handwritten diagram for feeding as Fig. 1: 102 into Fig. 1: 112 machine learning component(s) (more detail on the machine learning component(s) 112 in Figs. 2-3))… communicating the AI-developed solutions and/or questions and any digital representations present to a processor (claim 1, Fig. 1: 104, communicate AI developed solutions and/or questions and any digital representations present to a processor, such as a processor in claim 9 or para. 11) (*claim interpretation: see also 112(b) rejection above; the examiner is interpreting “solutions and/or questions” to be one or both of solutions, and/or questions); and displaying the AI-developed proposals of digital representations to the users (claim 1 and Fig. 1:104, digital structured model for display, via display of para. 46). Schaefer does not proactively teach: editing the processed user-specific data with the AI. Consider the following. In analogous art, Jin teaches editing the processed user-specific data with the AI (para. 159, user can edit the sketch input with AI/neural network). Modifying the applied references, such that the editing is done on the processed user-specific data as per Schaefer, is all of taught and suggested by the prior art, and would have been obvious and predictable to one of ordinary skill in the art as of the effective filing date of the claimed invention. See MPEP §2143(A). The prior art included each element recited in claim 9, although not necessarily in a single embodiment, with the only difference being between the claimed element and the prior art being the lack of actual combination of certain elements in a single prior art embodiment, as mapped and described above. One of ordinary skill in the art could have combined the elements as claimed by known methods, and in that combination, each element merely performs the same function as it does separately. One of ordinary skill in the art would have also recognized that the results of the combination were predictable as of the effective filing date of the claimed invention. Regarding claim 10: Jin teaches: the method as claimed in claim 9, carried out at the same time as capturing and/or recording the user-specific data (para. 149, non-neuromorphic (meaning not related to the neural network), and neuromorphic implementations can be performed at least partially in parallel. See also para. 168, 250, 288, 296, which further teach parallel operations and/or threads). It would have been obvious for one of ordinary skill in the art, as of the effective filing date of Applicant’s claims, to have further modified the applied references, in view of same, to have obtained the above, motivated to facilitate distributed processing and/or speed of results. Regarding claim 13: Jin teaches the method as claimed in claim 9, wherein the AI has access to cloud applications (paras. 183-84, 270). It would have been obvious for one of ordinary skill in the art, as of the effective filing date of Applicant’s claims, to have further modified the applied references, in view of same, to have obtained the above, motivated to make use of known methods to store and retain applications and data. Claim(s) 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Schaefer in view of Jin, and further in view of Sun (CN 1127117085A) (all citations to English language machine translation made available with this Office Action). Regarding claim 14: It would have been obvious for one of ordinary skill in the art to have combined and modified the applied reference(-s), in view of same, to have obtained: the method as claimed in claim 9, wherein the AI raises queries and/or demonstrates gaps in the digital representation to the users by way of the display modules, and the results of the modification would have been obvious and predictable to one of ordinary skill in the art as of the effective filing date of the claimed invention. See MPEP §2143(A). Sun teaches a product solution combination recommendation method based on deep learning (neural networks) (see page 2, Summary of the invention to page 3. See also page 5 and page 6). Modifying the applied references, such to include the neural network capabilities of Sun, to provide solution and recommendations based on business needs, to the model of Schaefer and Jin, (see e.g. Jin, para. 180, data can be manufacturing data, and, para. 154, BPMN is relevant) (*note: Applicant’s specification as filed has very little description of this claim feature), is all of taught and suggested by the prior art, and would have been obvious and predictable to one of ordinary skill, with additional motivation to save time and reduce manual operations. The prior art included each element recited in claim 14, although not necessarily in a single embodiment, with the only difference being between the claimed element and the prior art being the lack of actual combination of certain elements in a single prior art embodiment, as mapped and described above. One of ordinary skill in the art could have combined the elements as claimed by known methods, and in that combination, each element merely performs the same function as it does separately. One of ordinary skill in the art would have also recognized that the results of the combination were predictable as of the effective filing date of the claimed invention. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US-20130325759-A1 Methods and apparatus for performing transformation techniques for data clustering and/or classification US-20040090439-A1 Recognition and interpretation of graphical and diagrammatic representations US-20240193976-A1 Mechanisms are disclosed for machine learning-based diagram label recognition in connection with diagrams represented by unstructured images. US-20240152546-A1 Methods and systems for returning search results based on diagrams as search inputs are disclosed herein. US-20210279532-A1 A computer-implemented method for processing a digital image. The digital image comprises one or more text cells, wherein each of the one or more text cells comprises a string and a bounding box. The method comprises receiving the digital image in a first format, the first format providing access to the strings and the bounding boxes of the one more text cells. US-20170109578-A1 A system, method and computer program product for hand-drawing diagrams including text and non-text elements on a computing device are provided. US-20200184278-A1 System and Method for Extremely Efficient Image and Pattern Recognition and Artificial Intelligence Platform US-20190114302-A1 Sketch entry and interpretation of graphical user interface design US-20190138555-A1 Verification and export of federated areas and job flow objects within federated areas US-20190370288-A1 Handling of data sets during execution of task routines of multiple languages US-20190384790-A1 Staged training of neural networks for improved time series prediction performance US-20200026732-A1 Many task computing with distributed file system US-20200210479-A1 Automated generation of job flow definitions US-20200210647-A1 Techniques are described for automated summarization of extracted insight data. Insight data, for instance, is summarized via headlines that include content describing insight data, such as text, images, animations, and so forth. US-20210090694-A1 Data based cancer research and treatment systems and methods US-20210224051-A1 Per task routine distributed resolver US-20210141623-A1 Automated Message-Based Job Flow Resource Coordination in Container-Supported Many Task Computing US-20220117046-A1 An apparatus includes a processor to: within a performance container, execute a performance routine to derive an order of performance of tasks of a job flow based on dependencies, US-7912720-B1 System and method for building emotional machines US-20220300718-A1 Method, system, electronic device and storage medium for clarification question generation US-20210027018-A1 Generating recommendation information US-20230028912-A1 Automatic Design Assessment and Smart Analysis US-20190049957-A1 Emotional adaptive driving policies for automated driving vehicles * * * * * Any inquiry concerning this communication or earlier communications from the examiner should be directed to Sarah Lhymn whose telephone number is (571)270-0632. The examiner can normally be reached M-F, 9:00 AM to 6:00 PM EST. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Xiao Wu can be reached at 571-272-7761. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. Sarah Lhymn Primary Examiner Art Unit 2613 /Sarah Lhymn/Primary Examiner, Art Unit 2613
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Prosecution Timeline

Aug 27, 2024
Application Filed
Jun 23, 2026
Non-Final Rejection mailed — §103, §112 (current)

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Prosecution Projections

1-2
Expected OA Rounds
66%
Grant Probability
81%
With Interview (+15.0%)
2y 4m (~3m remaining)
Median Time to Grant
Low
PTA Risk
Based on 560 resolved cases by this examiner. Grant probability derived from career allowance rate.

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