Prosecution Insights
Last updated: April 19, 2026
Application No. 18/396,839

ARTIFICIAL INTELLIGENCE BASED COMMUNICATION ASSISTANCE

Final Rejection §102§103
Filed
Dec 27, 2023
Examiner
MUELLER, PAUL JOSEPH
Art Unit
2657
Tech Center
2600 — Communications
Assignee
Zoom Video Communications, Inc.
OA Round
2 (Final)
76%
Grant Probability
Favorable
3-4
OA Rounds
3y 0m
To Grant
99%
With Interview

Examiner Intelligence

Grants 76% — above average
76%
Career Allow Rate
97 granted / 128 resolved
+13.8% vs TC avg
Strong +35% interview lift
Without
With
+34.6%
Interview Lift
resolved cases with interview
Typical timeline
3y 0m
Avg Prosecution
25 currently pending
Career history
153
Total Applications
across all art units

Statute-Specific Performance

§101
13.2%
-26.8% vs TC avg
§103
62.2%
+22.2% vs TC avg
§102
7.4%
-32.6% vs TC avg
§112
14.8%
-25.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 128 resolved cases

Office Action

§102 §103
DETAILED ACTION Introduction This office action is in response to Applicant’s submission filed on January 16, 2026. Claims 1-3, 5, 10-12 and 15-16 have been amended. Claims 1-20 are pending in the application. As such, claims 1-20 have been examined. 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 . Drawings The drawings were received on December 27, 2023. These drawings have been accepted and considered by the Examiner. Response to Amendments and Arguments In view of the amendments to the claims, the amendments to claims 1-3, 5, 10-12 and 15-16, have been acknowledged and entered. In view of the amendments to the claims, the objection to claim 5 has been withdrawn. In view of the arguments and amendments to the claims, the rejections to claim 1-20 under 35 U.S.C. 101 have been withdrawn. In view of the arguments and amendments to the claims, the rejections to claims 1-20 under 35 U.S.C. 102 and 103 have been withdrawn. In light of the amendments to the claims, new grounds for rejection for claims 1-20 under 35 U.S.C. 102 and 103 are provided in the response below. New grounds for rejection is based at least upon the following new elements: accessing live communication data associated with the communication session; executing a pre-trained artificial intelligence (AI) model to generate a communication assistance message for the first participant at least based on the live communication dataduring the communication session, wherein the communication assistance message comprises information for the first participant to facilitate communication with the second participant during the communication session. Applicant’s arguments regarding the prior art rejections under 35 U.S.C 103, received on January 16, 2026, have been fully considered. Applicant’s arguments with respect to claims 1-20 have been considered, are directed to the newly amended matter in the claims, are not considered to be persuasive, and are addressed accordingly in the updated rejection rationale below. Claim Rejections - 35 USC § 102 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claims 1, 4, 10 and 15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Rodriguez Bravo et al. (US Patent Pub. No. 20230290348 A1), hereinafter Rodriguez. Regarding claims 1, 10 and 15, Rodriguez teaches a method, a system, and a non-transitory computer-readable medium (Rodriguez in [0003, 0004, 0005] teaches a method, a system, and a CRM for using an AI assistant during a meeting) comprising: [claim 10 only] a communications interface (Rodriguez in [0072, Fig. 6] teaches using devices with communication interfaces); [claim 10 only] a non-transitory computer-readable medium (Rodriguez in [0022] teaches using a computer readable storage medium or media, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire; and [claim 10 only] one or more processors communicatively coupled to the communications interface and the non-transitory computer-readable medium, the one or more processors configured to execute processor-executable instructions stored in the non-transitory computer-readable medium to (Rodriguez in [0026] teaches using processors which execute instructions): [claim 15 only] comprising processor-executable instructions configured to cause one or more processors to (Rodriguez in [0026] teaches using processors which execute instructions): establishing a communication session related to a predetermined topic between a first participant and a second participant (Rodriguez in [0076] teaches a facilitator, e.g., primary user, initiates the conference call, and there is an agenda for the meeting); receiving an assistance request from a client device associated with the first participant (Rodriguez in [0069, Fig. 5] teaches the primary user uses a personal device to communicate with the AI assistant, and in [0081] teaches the primary user may speak a command to the AI assistant); accessing live communication data associated with the communication session (Rodriguez in [0074] teaches the AI assistant monitors the conference call for context information in order to process commands properly, and in [0004] teaches identify by the Primary AI Assistant a possible scheduling or task item based on keywords and phrases spoken during the conference call, and wherein the prompting is performed during the conference call); executing a pre-trained artificial intelligence (AI) model to generate a communication assistance message for the first participant at least based on the live communication data during the communication session (Rodriguez in [0078] teaches the AI assistant provides a summary of the conference call along with actions that should be taken, and in [0004] teaches identify by the Primary AI Assistant a possible scheduling or task item based on keywords and phrases spoken during the conference call, and wherein the prompting is performed during the conference call); wherein the communication assistance message comprises information for the first participant to facilitate communication with the second participant during the communication session (Rodriguez in [0004] teaches identify by the Primary AI Assistant a possible scheduling or task item based on keywords and phrases spoken during the conference call, and wherein the prompting is performed during the conference call [note: here the scheduling facilitates communication by allowing the first participant to positively confirm a meeting or task has been created]); and providing the communication assistance message to the client device associated with the first participant during the communication session (Rodriguez in [0081] teaches the AI assistant provides a summary of the conference call to the primary user). Regarding claim 4, Rodriguez teaches the method of claim 1. Rodriguez further teaches wherein the pre-trained AI model is trained to learn multiple association rules related to the predetermined topic (Rodriguez in [0079] teaches the AI model has been trained on some training data and provides an example of being able to schedule meetings [here the topic is meetings and the rules are for scheduling the meetings]). Claim Rejections - 35 USC § 103 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claims 2, 11 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Rodriguez in view of Ozcaglar et al. (US Patent Pub. No. 20200402015 A1), hereinafter Ozcaglar. Regarding claims 2, 11 and 16, Rodriguez teaches the method, system, and non-transitory computer-readable medium of claims 1, 10 and 15. Rodriguez teaches generating the communication assistance message for the first participant based on the live communication data associated with the communication session (see claim 1 rejection). Rodriguez does not teach, however Ozcaglar teaches further comprising: [claim 11 only] wherein the one or more processors are configured to execute further processor-executable instructions stored in the non-transitory computer-readable medium to: [claim 16 only] further comprising processor-executable instructions configured to cause one or more processors to: receiving profile data associated with the second participant, wherein the profile data comprises a gender, a job title, and an organization of the second participant (Ozcaglar in [0032] teaches using a profile of a member which includes gender, age range, nationality, location, language), professional (e.g., job title, professional summary, professional headline, employer, industry, experience, skills, seniority level, professional endorsements), social (e.g., organizations to which the user belongs, geographic area of residence), and/or educational (e.g., degree, university attended, certifications, licenses) attributes); and [generating the communication assistance message for the first participant] based on the profile data associated with the second participant [and the live communication data associated with the communication session] (Ozcaglar in [0025-0026] teaches generating recommendations based on the profile information). Ozcaglar is considered to be analogous to the claimed invention because it is in the same field of systems which use profile information by a machine learning model to perform tasks. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rodriguez further in view of Ozcaglar to allow for generating recommendations based on the profile information. Motivation to do so would allow for a recruiter and/or another moderator involved in hiring for or placing jobs or opportunities to specify parameters related to candidates for an opportunity and/or a number of related opportunities (Ozcaglar [0041]). Claims 3 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Rodriguez in view of Patel et al. (US Patent Pub. No. 20220271962 A1), hereinafter Patel. Regarding claims 3 and 12, Rodriguez teaches the method and system of claims 1 and 10. Rodriguez further teaches wherein the live communication data comprises audio data associated with the communication session (Rodriguez in [0074] teaches the AI assistant monitors the conference call for context information in order to process commands properly, and in [0063] teaches the AI assistant receives audio input from a conference call). Rodriguez does not teach, however Patel teaches wherein the method further comprises [claim 12 only] wherein the one or more processors are configured to execute further processor-executable instructions stored in the non-transitory computer-readable medium to: converting the audio data to text data (Patel in [0047] teaches a user may define an audio of a meeting is to be recorded, the video of the meeting is to be recorded, and a transcript of the recording should be prepared). Patel is considered to be analogous to the claimed invention because it is in the same field of systems which use AI to perform tasks. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rodriguez further in view of Patel to allow for generating a transcript of a meeting. Motivation to do so would allow for a user to define the manner in which a notification is to be provided (e.g., visually, audibly, and/or the like), enable or disable the intelligent meeting assistant system for some or all virtual meetings, assign priorities to trigger phrases/conditions, and/or configure various other settings (Patel [0015]). Claims 5, 13 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Rodriguez in view of Khoury et al. (US Patent Pub. No. 20210224858 A1), hereinafter Khoury. Regarding claims 5, 13 and 17, Rodriguez teaches the method, system, and non-transitory computer-readable medium of claims 4, 10 and 15. Rodriguez further teaches [claims 13 and 17 only] wherein the pre-trained AI model is trained to learn multiple association rules related to the predetermined topic (Rodriguez in [0079] teaches the AI model has been trained on some training data and provides an example of being able to schedule meetings [here the topic is meetings and the rules are for scheduling the meetings]), wherein generating a communication assistance message for the first participant by analyzing the live communication data associated with the communication session using a pre-trained AI model comprises: [claim 13 only] wherein the one or more processors are configured to execute further processor-executable instructions stored in the non-transitory computer-readable medium to: [claim 17 only] further comprising processor-executable instructions configured to cause one or more processors to: identifying one or more keywords from a set of communication data corresponding to the second participant (Rodriguez in [0078] teaches Juan (second participant) suggests having another meeting, and the AI assistant proceeds to schedule the new meeting based on the keywords spoken by Juan); and identifying a matching association rule for the set of communication data corresponding to the second participant (Rodriguez in [0078] teaches Juan (second participant) suggests having another meeting, and the AI assistant proceeds to schedule the new meeting based on the keywords spoken by Juan [here the rule of scheduling is matched to the words spoken by Juan]); and generating the communication assistance message based on the matching association rule (Rodriguez in [0078] teaches the AI Assistant generates the scheduling item and provides it to the appropriate participant). Rodriguez does not teach, however Khoury teaches mapping the one or more keywords to the multiple association rules (Khoury in [0351] teaches rules being mapped to responses based on keywords). Khoury is considered to be analogous to the claimed invention because it is in the same field of systems which use AI to perform tasks. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rodriguez further in view of Khoury to allow for mapping rules to responses based on keywords. Motivation to do so would allow for an approval module to allow a system user to approve or disapprove, and/or to edit, communications prior to its distribution (Khoury [0021]). Claims 6-7 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Rodriguez in view of Ruan (US Patent Pub. No. 20240412051 A1). Regarding claims 6 and 18, Rodriguez teaches the method and non-transitory computer-readable medium of claims 1 and 15. Rodriguez does not teach, however Ruan teaches wherein the pre-trained AI model is an apriori algorithm (Ruan in [0048] teaches using an LLM, and in [0049] teaches using an associated rule learning algorithm (e.g., an Apriori algorithm) within the LLM). Ruan is considered to be analogous to the claimed invention because it is in the same field of systems which use neural network algorithms to perform tasks. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rodriguez further in view of Ruan to allow for using an Apriori algorithm. Motivation to do so would allow for improving hardware consumption and computing performance by performing neural network operations on dense tensors using sparse value information from original tensors (Ruan [Abstract]). Regarding claims 7 and 19, Rodriguez teaches the method and non-transitory computer-readable medium of claims 1 and 15. Rodriguez does not teach, however Ruan teaches wherein the pre-trained AI model is a large language model (Ruan in [0048, 0109] teaches using an LLM). Ruan is considered to be analogous to the claimed invention because it is in the same field of systems which use neural network algorithms to perform tasks. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rodriguez further in view of Ruan to allow for using an LLM. Motivation to do so would allow for improving hardware consumption and computing performance by performing neural network operations on dense tensors using sparse value information from original tensors (Ruan [Abstract]). Claims 8-9, 14 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Rodriguez in view of Gao et al. (US Patent Pub. No. 20230064763 A1), hereinafter Gao. Regarding claim 8, Rodriguez teaches the method of claim 1. Rodriguez does not teach, however Gao teaches wherein the communication assistance message comprises a recommended action for the first participant (Gao in [0054] teaches provides a set of recommended actions along with a particular support document). Gao is considered to be analogous to the claimed invention because it is in the same field of systems which use AI to make recommendations. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rodriguez further in view of Gao to allow for providing a set of recommended actions along with a particular support document. Motivation to do so would allow for providing relevant steps and clear checklist items, as well as collaborative intelligence to ease and facilitate a technology adoption process (Gao [0020]). Regarding claim 9, Rodriguez, as modified above, teaches the method of claim 8. Rodriguez, as modified above, does not teach, however Gao teaches wherein the communication assistance message comprises supporting documents associated with the recommended action for the first participant (Gao in [0054] teaches provides a set of recommended actions along with a particular support document). Gao is considered to be analogous to the claimed invention because it is in the same field of systems which use AI to make recommendations. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rodriguez, as modified above, further in view of Gao to allow for providing a set of recommended actions along with a particular support document. Motivation to do so would allow for providing relevant steps and clear checklist items, as well as collaborative intelligence to ease and facilitate a technology adoption process (Gao [0020]). Regarding claims 14 and 20, Rodriguez teaches the system and non-transitory computer-readable medium of claims 10 and 15. wherein the communication assistance message comprises a recommended action for the first participant and supporting documents associated with the recommended action for the first participant (Gao in [0054] teaches provides a set of recommended actions along with a particular support document). Gao is considered to be analogous to the claimed invention because it is in the same field of systems which use AI to make recommendations. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rodriguez further in view of Gao to allow for providing a set of recommended actions along with a particular support document. Motivation to do so would allow for providing relevant steps and clear checklist items, as well as collaborative intelligence to ease and facilitate a technology adoption process (Gao [0020]). Conclusion 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(a). 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 PAUL J. MUELLER whose telephone number is (571)272-1875. The examiner can normally be reached M-F 9:00am-5:00pm (Eastern). 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, Daniel C. Washburn can be reached at 571-272-5551. 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. PAUL MUELLER Examiner Art Unit 2657 /PAUL J. MUELLER/Examiner, Art Unit 2657 /DANIEL C WASHBURN/Supervisory Patent Examiner, Art Unit 2657
Read full office action

Prosecution Timeline

Dec 27, 2023
Application Filed
Sep 17, 2025
Non-Final Rejection — §102, §103
Jan 16, 2026
Response Filed
Feb 06, 2026
Final Rejection — §102, §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
76%
Grant Probability
99%
With Interview (+34.6%)
3y 0m
Median Time to Grant
Moderate
PTA Risk
Based on 128 resolved cases by this examiner. Grant probability derived from career allow rate.

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