Prosecution Insights
Last updated: April 19, 2026
Application No. 18/372,434

INTERACTIVE QUERY FACILITATION

Final Rejection §103
Filed
Sep 25, 2023
Examiner
SHAH, ANTIM G
Art Unit
2693
Tech Center
2600 — Communications
Assignee
Zoom Video Communications, Inc.
OA Round
2 (Final)
74%
Grant Probability
Favorable
3-4
OA Rounds
3y 3m
To Grant
99%
With Interview

Examiner Intelligence

Grants 74% — above average
74%
Career Allow Rate
430 granted / 580 resolved
+12.1% vs TC avg
Strong +39% interview lift
Without
With
+39.2%
Interview Lift
resolved cases with interview
Typical timeline
3y 3m
Avg Prosecution
15 currently pending
Career history
595
Total Applications
across all art units

Statute-Specific Performance

§101
8.4%
-31.6% vs TC avg
§103
48.4%
+8.4% vs TC avg
§102
20.4%
-19.6% vs TC avg
§112
13.2%
-26.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 580 resolved cases

Office Action

§103
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 . Response to Amendment Applicants’ amendment filed on 10/28/25 has been entered. Claims 1, 7, 10, 13, 16, 19 have been amended. No claims have been canceled. No new claims have been added. Claims 1-20 are still pending in this application, with claims 1, 10, 16 being independent. 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 for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 2023/0115098 to Miller et al. (“Miller”) in view of U.S. Patent Application Publication No. 2021/0326742 to Rosset et al. (“Rosset”). As to claims 1, 10 and 16, Miller discloses a method, a system and a non-transitory computer-readable medium, the method comprising: receiving an initial query about a virtual communication session from a user [Fig. 4: 406, paragraphs 0018, 0023, 0026, 0030, 0076]; accessing virtual communication data associated with the virtual communication session [Fig. 4: 406, paragraphs 0018, 0023, 0026, 0030, 0076]; executing a first pre-trained generative artificial intelligence (AI) model to generate an initial response to the initial query based on the virtual communication data [paragraph 0076: returning the results of the user’s query]; generating a first set of follow-up queries based on the initial response using a second pre-trained generative AI model [paragraphs 0006, 0073-74, 0076-77]; receiving a selection of a first follow-up query out of the first set of follow-up queries [paragraphs 0073, 0077]; and providing a first response to the first follow-up query using the first pre-trained generative AI model [paragraph 0077 : “the selected query may be executed against live transcript 414, and a query results may be returned”]. Miller does not expressly disclose executing a second pre-trained generative AI model to generate a first set of follow-up queries based on the initial response and providing a first response to the first follow-up query using the first pre-trained generative AI model. Even though, it is extremely obvious and well known in the art when generating the follow-up query the original query of the user is also taken into account and also the query responses are generated using a first pre-trained generative AI model. Miller also does not expressly disclose obtaining user feedback data associated with the first set of follow-up queries based on the selection of the first follow-up query: and fine-tuning the second pre-trained generative AI model based on the user feedback data to obtain a second fine-tuned generative AI model. In the same or similar field of invention, Rosset discloses features of executing a second pre-trained generative AI model to generate a first set of follow-up queries based on the initial response, providing a first response to the first follow-up query using the first pre-trained generative AI model [Rosset paragraphs 0005-0006, 0052-0053] and obtaining user feedback data associated with the first set of follow-up queries based on the selection of the first follow-up query [Rosset Fig. 11: 1110, 1112—1116, paragraphs 0107-0112] and fine-tuning the second pre-trained generative AI model based on the user feedback data to obtain a second fine-tuned generative AI model [Rosset Fig. 11, paragraphs 0107-0112, 0115-0118]. It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify Miller to have above features as taught by Rosset. The suggestion/motivation would have been to provide a computer-implemented technique for assisting a user in interacting with a query-processing system. The technique uses a suggestion-generating system to provide one or more suggestions to a user in response to at least a last-submitted query provided by the user [Rosset paragraph 0003]. As to claim 2, Miller discloses wherein the virtual communication session is an online chat session, and wherein the virtual communication data comprises multiple chat messages in the online chat session [paragraphs 0030-31, 0044-45, 0055, 0057]. As to claim 3, Miller discloses wherein the virtual communication session is a virtual conference, and wherein the virtual communication data comprises a transcript for the virtual conference [paragraphs 0005-0006, 0076-0076]. As to claim 4, Miller discloses wherein the virtual communication session is an email thread, and wherein the virtual communication data comprises a sequence of emails [paragraphs 0084]. As to claims 5, 11 and 17, Miller discloses prior to receiving an initial query about the virtual communication session from a user, training a first generative AI model to obtain the first pre-trained generative AI model using a set of question-answer pairs as a first set of training output and a set of communication data as a first set of training input [Fig. 3, paragraphs 0065, 0070]; and training a second generative AI model to obtain the second pre-trained generative AI model using a sequence of questions as a second set of training output and the set of communication data as a second set of training input [Fig. 3, paragraphs 0065, 0070, 0073]. As to claims 6, 12 and 18, Miller discloses providing the initial response to the user; and providing the initial response to the second pre-trained generative AI model [paragraphs 0065, 0070]. As to claims 7, 13 and 19, Miller discloses receiving user feedback about the first set of follow-up queries; retraining the second pre-trained generative AI model based on the user feedback to obtain a second retrained generative AI model; and regenerating the first set of follow-up queries using the second retrained generative Al model [paragraph 0065, 0073]. As to claims 8, 14 and 20, Miller discloses receiving a follow-up query created by the user; and generating an answer to the follow-up query using the first pre-trained generative Al model [paragraphs 0076-0077, Fig. 4]. As to claims 9 and 15, Miller discloses generating a second set of follow-up queries based on the first response using the second pre-trained generative AI model; and receiving a selection of a second follow-up query out of the second set of follow-up queries; and providing a second response to the second follow-up query using the first pre-trained generative AI model [paragraphs 0076-77, Fig. 4]. Further, Rosset discloses features of generating a first set of follow-up queries based on the initial response using a second pre-trained generative AI model and providing a first response to the first follow-up query using the first pre-trained generative AI model [Rosset paragraphs 0005-0006, 0052-0053]. In addition, the same motivation is used as the rejection of claims 1 and 10. Response to Arguments Applicant's arguments filed on 10/28/25 with respect to 103 rejection have been fully considered but they are not persuasive. On page 12 of applicant’s remark, the applicant argues the following: “Applicant respectfully traverses the rejection of claims 1, 10, and 16 under 35 U.S.C. § 103 as allegedly being unpatentable over Miller and Rosset. Neither Miller nor Rosset discloses or makes obvious the following feature as specified in amended claim 1: "obtaining user feedback data associated with the first set of follow-up queries based on the selection of the first follow-up query; and fine-tuning the second pre-trained generative AI model based on the user feedback data to obtain a second fine-tuned generative AI model." “For at least the above reasons, Applicant submits that claim 1 is allowable over Miller and Rosset. ” Examiner respectfully disagrees with Applicant's arguments for the following reasons: Rosset clearly disclose obtaining user feedback data associated with the first set of follow-up queries based on the selection of the first follow-up query [Fig. 11: 1110, 1112-1116, paragraphs 0107-0112] and fine-tuning the second pre-trained generative AI model based on the user feedback data to obtain a second fine-tuned generative AI model [Fig. 11, paragraphs 0107-0112, 0115-0118]. As per Rosset, feedback systems such as a manual labeling system/click-based example-generating system/relative-CTR example-generating system/query sequence-generating system provide feedbacks from users to fine-tune pre-trained model [Fig. 11, paragraphs 0107-0118]. Thus, Miller in view of Rosset all the limitation of claim 1. 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 ANTIM G SHAH whose telephone number is (571)270-5214. The examiner can normally be reached Mon-Fri 7:30am-4pm. 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, Ahmad Matar can be reached at 571-272-7488. 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. /ANTIM G SHAH/Primary Examiner, Art Unit 2693
Read full office action

Prosecution Timeline

Sep 25, 2023
Application Filed
Jul 25, 2025
Non-Final Rejection — §103
Oct 28, 2025
Response Filed
Jan 30, 2026
Final Rejection — §103 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12598258
A METHOD AND PROCESS FOR A VOICE COMMUNICATION SYSTEM BETWEEN BUSINESSES AND CUSTOMERS USING EXISTING TELEPHONY AND OVER DATA NETWORKS
2y 5m to grant Granted Apr 07, 2026
Patent 12591745
METHOD AND SYSTEM FOR FINE-TUNING NEURAL CONDITIONAL LANGUAGE MODELS USING CONSTRAINTS
2y 5m to grant Granted Mar 31, 2026
Patent 12592990
Method and Apparatus for Processing Caller Ring Back Tone, Storage Medium, and Electronic Device
2y 5m to grant Granted Mar 31, 2026
Patent 12587600
Method for managing the routing of a call intended for a first communication terminal, method for routing said call and corresponding devices.
2y 5m to grant Granted Mar 24, 2026
Patent 12585678
Using Language Model To Automatically Generate List Of Items At An Online System Based on a Constraint
2y 5m to grant Granted Mar 24, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

3-4
Expected OA Rounds
74%
Grant Probability
99%
With Interview (+39.2%)
3y 3m
Median Time to Grant
Moderate
PTA Risk
Based on 580 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month