Prosecution Insights
Last updated: October 04, 2026
Application No. 19/073,878

Machine Learning Systems and Methods for Automatic Photo Labeling and Filing

Non-Final OA §102
Filed
Mar 07, 2025
Priority
Mar 08, 2024 — provisional 63/562,862
Examiner
LU, ZHIYU
Art Unit
Tech Center
Assignee
Xactware Solutions Inc.
OA Round
1 (Non-Final)
49%
Grant Probability
Moderate
1-2
OA Rounds
2y 3m
Est. Remaining
63%
With Interview

Examiner Intelligence

Grants 49% of resolved cases
49%
Career Allowance Rate
381 granted / 779 resolved
-11.1% vs TC avg
Moderate +14% lift
Without
With
+14.1%
Interview Lift
resolved cases with interview
Typical timeline
3y 10m
Avg Prosecution
44 currently pending
Career history
833
Total Applications
across all art units

Statute-Specific Performance

§101
2.8%
-37.2% vs TC avg
§103
67.5%
+27.5% vs TC avg
§102
11.9%
-28.1% vs TC avg
§112
16.6%
-23.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 779 resolved cases

Office Action

§102
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 Rejections - 35 USC § 102 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. Claim(s) 1-26 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Randolph (US2018/0025451). To claim 1. Randolph teach a machine learning (a preamble with no link to claim body, carry no patentable weight) system for automatic photo labeling and filing, comprising: a computing system; a claims estimation software application executed by the computing system, the claims estimation software application receiving a plurality of claim estimation photos relating to an insurance claim (paragraph 0008); and a photo labelling and filing software module in communication with the claims estimation software application and executed by the computer system (paragraph 0013), the photo labelling and filing software module configured to: retrieve a photo of the plurality of claim estimation photos; process the photo using object recognition to detect one or more features in the photo; generate a label for the photo based on the one or more features detected in the photo; assign the label to the photo (paragraph 0111); determine a photo album of a claim file of the claims estimation software application in which to store the photo; and storing the photo in the photo album of the claim file (paragraph 0113). To claim 14, Randolph teach a machine learning method for automatic photo labeling and filing (as explained in response to claim 1 above). To claims 2 and 15, Randolph teach claims 1 and 14. Randolph teach wherein the claims estimation software application receives user feedback relating to the one or more features detected in the photo (paragraphs 0019-0022, 0054, 0110, 0114, manually by user). To claims 3 and 16, Randolph teach claims 2 and 15. Randolph teach wherein the claims estimation software application refines the one or more features based on the user feedback (paragraphs 0019-0022, 0054, 0110, 0114). To claims 4 and 17, Randolph teach claims 1 and 14. Randolph teach wherein the system generates a user interface screen allowing a user to define, alter, or synchronize one or more profiles and to set preferences associated with an estimate (paragraphs 0019-0022, 0054, 0110, 0114). To claims 5 and 18, Randolph teach claims 1 and 14. Randolph teach wherein the system generates a user interface screen allowing a user to graphically define or sketch a floor plan of a room (paragraphs 0054, 0064, 0067). To claims 6 and 19, Randolph teach claims 5 and 18. Randolph teach wherein the system allows a user to add one or more items to the floor plan of the room (paragraphs 0054, 0064, 0067). To claims 7 and 20, Randolph teach claims 1 and 14. Randolph teach wherein the system allows a user to take a photo of an object in a room (paragraph 0119). To claims 8 and 21, Randolph teach claims 7 and 20. Randolph teach wherein the system automatically generates a label associated with the photo of the object (paragraph 0119). To claims 9 and 22, Randolph teach claims 8 and 22. Randolph teach wherein the system allows a user to take notes relating to the photo of the object (paragraphs 0110, 0114). To claims 10 and 23, Randolph teach claims 9 and 22. Randolph teach wherein the system associates the photo of the object with one or more of a date the photo was taken, an insurance claim number, a name of an insured party, a cause of loss of an object depicted in the photo, a level of a structure in which the object is located, a zone, a room associated with the object, or a description of the object (paragraphs 0110, 0114). To claims 11 and 24, Randolph teach claims 1 and 14. Randolph teach wherein the system displays a photo selection panel for allowing a user to conduct bulk editing of the plurality of claim estimation photos (paragraph 0131). To claims 12 and 25, Randolph teach claims 1 and 14. Randolph teach wherein the system generates a photo selection screen allowing a user to search for one or more photos by specifying a label (paragraph 0151). To claims 13 and 26, Randolph teach claims 1 and 14. Randolph teach wherein the system displays information about an insurance estimate associated with one or more of the plurality of claim estimation photos (paragraph 0057). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to ZHIYU LU whose telephone number is (571)272-2837. The examiner can normally be reached Weekdays: 8:30AM - 5:00PM. 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, Stephen R Koziol can be reached at (408) 918-7630. 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. ZHIYU . LU Primary Examiner Art Unit 2669 /ZHIYU LU/Primary Examiner, Art Unit 2665 September 12, 2026
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Prosecution Timeline

Mar 07, 2025
Application Filed
Sep 16, 2026
Non-Final Rejection mailed — §102 (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

1-2
Expected OA Rounds
49%
Grant Probability
63%
With Interview (+14.1%)
3y 10m (~2y 3m remaining)
Median Time to Grant
Low
PTA Risk
Based on 779 resolved cases by this examiner. Grant probability derived from career allowance rate.

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