Prosecution Insights
Last updated: April 19, 2026
Application No. 17/844,011

SYSTEM FOR USERS TO INCREASE AND MONETIZE LIVESTREAM AUDIENCE ENGAGEMENT

Final Rejection §112
Filed
Jun 19, 2022
Examiner
KRAISINGER, EMILY MARIE
Art Unit
3626
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Lakshmanan Narayan
OA Round
6 (Final)
30%
Grant Probability
At Risk
7-8
OA Rounds
2y 4m
To Grant
76%
With Interview

Examiner Intelligence

Grants only 30% of cases
30%
Career Allow Rate
16 granted / 54 resolved
-22.4% vs TC avg
Strong +47% interview lift
Without
With
+46.6%
Interview Lift
resolved cases with interview
Typical timeline
2y 4m
Avg Prosecution
39 currently pending
Career history
93
Total Applications
across all art units

Statute-Specific Performance

§101
45.2%
+5.2% vs TC avg
§103
34.4%
-5.6% vs TC avg
§102
10.2%
-29.8% vs TC avg
§112
8.8%
-31.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 54 resolved cases

Office Action

§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 . Status of Claims Claims 1-3, and 9-17 have been examined in this Final Rejection and are pending. Claims 4-8, and 18-20 were previously canceled. Priority Application 17/844,011 filed 06/19/2022 claims priority to provisional application 63/212,700 filed 06/20/2021. Claim Rejections - 35 USC § 112 The following is a quotation of the first paragraph of 35 U.S.C. 112(a): (a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention. The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112: The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention. Claim(s) 1-3, and 9-17 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. Lack of Written Description/Not in Specification Claim 1 recites: "a recurrent neural network (RNN) comprising a hidden state memory", "modifying, during runtime, the hidden state memory based on one or more streaming parameters including buffer occupancy or text arrival rate" "selectively persisting a subset of prior hidden states identified as context-critical while discarding non-critical hidden states to maintain a bounded state size" "generating output text prior to receipt of an end-of-sequence indicator" "a plurality of cloud-based edge nodes configured to receive partial text segments from at least one source in real time" "a stream segmentation module executing on each edge node, the module configured to generate variable-length text segments based on semantic boundary detection" "a distributed ordering controller configured to dynamically assign, based on measured inter-node latency, a sequence-assignment role to a selected edge node" "a reconciliation engine configured to merge text segments received from multiple edge nodes using a conflict-free replicated data structure" "a client interface configured to stream the merged text segments in sequence as they are generated". Claim 15 recites: a plurality of cloud-based edge nodes configured to receive partial text segments from at least one source in real time; a stream segmentation module executing on each edge node, the module configured to generate variable-length text segments based on semantic boundary detection; a distributed ordering controller configured to dynamically assign, based on measured inter-node latency, a sequence-assignment role to a selected edge node a reconciliation engine configured to merge text segments received from multiple edge nodes using a conflict-free replicated data structure: a client interface configured to stream the merged text segments in sequence as they are generated As best understood, the portions of the disclosure most closely related to the above indicated recitation are in the specification as filed at 0076, 0087, 0099, 00117, 0068, and 0047. 0076 teaches supervised learning algorithms include but not limited to the AI/ML models, NLP+ algorithms, and outlier detection programs to detect changes in patterns and translate them into actionable recommendations and that AI/ML models may be but not limited to artificial neural networks and support vector machines. The Specification fails to teach a recurrent neural network (RNN), hidden state memory, or parameters including buffer occupancy or text arrival rate. 00122 teaches analyzing comments data for specific keywords and generating a list of usernames related to the specific keywords. The Specification fails to teach generating output text prior to receipt of an end-of-sequence indicator. 0087 teaches that the software takes the comments data from the read module, processes it as per the required engagement tool, and renders it as a visualization that the presenter 209 can share with the audience to engage them by showing a visual representation of their inputs in real time. The Specification fails to teach a plurality of cloud-based edge nodes configured to receive partial text segments from at least one source in real time. 0099 teaches Fig. 12 illustrating a keyword analysis module that enables the StreamAlive 209 software to use NLP to analyze the comments data to identify keywords 1203. Also, an NLP model is created to analyze short form text 1205. The Specification fails to teach a stream segmentation module executing on each edge node, the module configured to generate variable-length text segments based on semantic boundary detection. 00117 teaches the StreamAlive 209 software analyzing the comment data for relevance, frequency of interaction, etc. for each participant, in real time 1403, in other embodiments more parameters are used for analysis. Using sentiment analysis, a score will be assigned for each interaction of each audience member 1405. Then an overall score will be assigned to the audience member 1407 during the livestream. The Specification fails to teach a distributed ordering controller configured to dynamically assign, based on measured inter-node latency, a sequence-assignment role to a selected edge node. 0068 teaches a recommendation engine 615, analytics engine for convert module 617 and features engine 613. The Specification fails to teach a reconciliation engine configured to merge text segments received from multiple edge nodes using a conflict-free replicated data structure. 0047 teaches the audience interacting with the presenter 209 via the chat interface provided by the online meeting / livestreaming software platform 213. The StreamAlive application 207 further captures the chat output of the audience and provides meaningful feedback to the presenter 209 who in turn can better engage with the audience 211. The Specification fails to teach a client interface configured to stream the merged text segments in sequence as they are generated. Accordingly, support in the disclosure is not found for Claim 1, and Claim 15. Dependent Claims 2-3, 9-14, and 16-17 are rejected due to their dependencies on Claim 1, and Claim 15. Subject Matter Distinguishable from Prior Art Claims 1-3, and 9-17 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. § 112 set forth in this Office Action. As previously disclosed in the Non-Final Rejection on 12/26/2024, Claims 1-3, and 9-17 are subject matter distinguishable from prior art. Response to Arguments Applicant's arguments filed 02/10/2026 with respect to 35 U.S.C. § 101, have been fully considered, and are persuasive. The 101 Rejection is withdrawn in light of the amendments, however, the amendments raised a new grounds of rejection under 35 U.S.C. § 112. 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 Emily M Kraisinger whose telephone number is (703)756-4583. The examiner can normally be reached M-F 7:30 AM -4:30 PM. 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, Jessica Lemieux can be reached at 571-270-3445. 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. /E.M.K./Examiner, Art Unit 3626 /JESSICA LEMIEUX/Supervisory Patent Examiner, Art Unit 3626
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Prosecution Timeline

Jun 19, 2022
Application Filed
Mar 11, 2024
Non-Final Rejection — §112
Jun 09, 2024
Response Filed
Aug 20, 2024
Final Rejection — §112
Oct 10, 2024
Response after Non-Final Action
Oct 29, 2024
Examiner Interview (Telephonic)
Oct 30, 2024
Response after Non-Final Action
Nov 21, 2024
Request for Continued Examination
Nov 22, 2024
Response after Non-Final Action
Dec 18, 2024
Non-Final Rejection — §112
Mar 17, 2025
Response Filed
Apr 11, 2025
Final Rejection — §112
Aug 06, 2025
Request for Continued Examination
Aug 11, 2025
Response after Non-Final Action
Sep 09, 2025
Non-Final Rejection — §112
Nov 18, 2025
Examiner Interview Summary
Nov 18, 2025
Applicant Interview (Telephonic)
Feb 10, 2026
Response Filed
Mar 24, 2026
Final Rejection — §112 (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

7-8
Expected OA Rounds
30%
Grant Probability
76%
With Interview (+46.6%)
2y 4m
Median Time to Grant
High
PTA Risk
Based on 54 resolved cases by this examiner. Grant probability derived from career allow rate.

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