Prosecution Insights
Last updated: April 19, 2026
Application No. 18/983,069

SELF-HEALING MULTIMEDIA EMPLOYMENT GENERATIVE AI SYSTEM

Non-Final OA §101§102
Filed
Dec 16, 2024
Examiner
SUMMERS, KIERSTEN V
Art Unit
3626
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Peozzle Corporation
OA Round
1 (Non-Final)
12%
Grant Probability
At Risk
1-2
OA Rounds
3y 11m
To Grant
27%
With Interview

Examiner Intelligence

Grants only 12% of cases
12%
Career Allow Rate
36 granted / 296 resolved
-39.8% vs TC avg
Strong +15% interview lift
Without
With
+15.1%
Interview Lift
resolved cases with interview
Typical timeline
3y 11m
Avg Prosecution
56 currently pending
Career history
352
Total Applications
across all art units

Statute-Specific Performance

§101
30.5%
-9.5% vs TC avg
§103
32.5%
-7.5% vs TC avg
§102
13.2%
-26.8% vs TC avg
§112
20.4%
-19.6% vs TC avg
Black line = Tech Center average estimate • Based on career data from 296 resolved cases

Office Action

§101 §102
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 . DETAILED ACTION Status of the Application The following is a Non-Final Office Action in response to communication received on 12/16/2024. Claim 1 is pending in this office action. As of the date of this communication no Information Disclosure Statement (IDS) has been filed on behalf of this case. Information Disclosure Statement The listing of references in the specification is not a proper information disclosure statement. 37 CFR 1.98(b) requires a list of all patents, publications, or other information submitted for consideration by the Office, and MPEP § 609.04(a) states, "the list may not be incorporated into the specification but must be submitted in a separate paper." Therefore, unless the references have been cited by the examiner on form PTO-892, they have not been considered. Specifically see Applicant’s specification at page 1. Claim Interpretation Claim 1 is interpreted as a process as the claims recite a computer implemented (“generative AI system computing device”) method. Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) generating improved over time (self healing) multi-media employment information using special purpose rules including quality and bias checks. The broad recitation of the claims recite human activities related to employment. Employment is subject matter related to managing personal behavior or relationships or interactions between people (including social activities, teaching and following rules or instructions). Subject matter related to managing personal behavior or relationships or interactions between people (including social activities, teaching and following rules or instructions) this is a certain method of organizing human activities. See MPEP 2106.04(a). Further the claims are recited at such a high level of generality that the claims recite observations, evaluations, judgement and opinions a human could perform. Specifically a human could reasonably and practically generate improved over time (e.g. self healing) multi-media employment information using special purpose rules including quality and bias checks, as broadly recited in the claims. Accordingly, the claims recite a mental process (see MPEP 2106.04(a)). Certain methods of organizing human activity and mental processes are in the groupings of enumerated abstracts ideas, and hence the claims recite an abstract idea. This judicial exception is not integrated into a practical application because the claims merely recite limitations that are not indicative of integration into a practical application in that the claims merely recite: (1) Adding the words “apply it” ( or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)) and (2) Generally linking the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)). Specifically as recited in the claims: Examiner notes that the Examiner has bolded and underlined additional elements for distinction. Limitations not bolded and underlined are considered a part of the abstract idea. 1. A self-healing multi-media employment content generative AI system computing device implemented method comprising: generating self-healing multi-media employment content using AI, which includes special purpose software components of the self-healing multi-media employment content generative AI system; and generating self-healing multi-media employment content using AI, which includes special purpose software components of a self-healing multi-media employment content quality check and bias check AI system. As per claim 1, the claims recite limitations or activities a human or humans could perform. Specifically a human or humans could generate improved over time (e.g. self healing) multi-media employment information using special purpose rules including quality and bias checks, as broadly recited in the claims. These rules can be special purpose as they are used for this specific application. The additional elements that these limitations as broadly recited in the claims that could be performed by a human or humans are instead broadly being recited as being performed by computers specifically “AI system computing device”, “software components”, and “AI” merely results in apply it. Here the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks or simply adding a general purpose computer or computer components after the fact to an abstract idea does not integrate a judicial exception into a practical application or provide significantly more. Further here the claim recites only the idea of a solution or outcome, i.e. the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". Instead the claims recite only a result-oriented solution and lacked details as to how a computer performs the modifications, which is equivalent to the words "apply it". Here Applicant does not recite as broadly recited in the claims an improvement in AI rather Applicant is merely reciting using an “AI system computing device”, “software components”, and “AI”, to implement the abstract idea that could otherwise be performed by a human or humans generating and updating rules over time that include quality and bias checks as broadly recited in the claims which is equivalent to the words apply it (see MPEP 2106.05(f)). Further limitations that could be performed by a human or humans that instead recite these limitations being performed by ““AI system computing device”, “software components”, and “AI”, merely generally links the use of the judicial exception to the field of computers (see MPEP 2106.05(h)). The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims merely recite limitations that are not indicative of an inventive concept (“significantly more”) in that the claims merely recite: (1) Adding the words “apply it” ( or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)) and (2) Generally linking the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)), as detailed above with respect to the practical application step. 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. Claim(s) 1 is rejected under 35 U.S.C. 102(a)(1) as being unpatentable over Scarborough et al. (United States Patent Application Publication Number: US 2012/0078804). As per claim 1, Scarborough et al. teaches A self-healing (see paragraphs 0016, 0097, 0114, and 0121, Examiner’s note: system is adaptive so ineffective predictors can be removed (see paragraph 0016), can adapt to changing conditions like demographics, economic, job content, or job effectiveness (see paragraph 0097), further teaches an old algorithm is archived and a new model is deployed (see paragraph 0114). Examiner notes that “self-healing” is interpreted as updating the model or AI over time). multi-media (see paragraph 0070, Examiner’s note: multi- media or text). employment content generative AI system computing device implemented method comprising: (see paragraphs 0012 and 0046, Examiner’s note: automated employee selection system and method (see paragraph 0012), the predictive model is an artificial intelligence model (see paragraph 0046), and the model can be implemented by software running on a computer (See paragraph 0046)). generating self-healing multi-media employment content using AI, (see paragraphs 0016, 0097, and 0114, Examiner’s note: system is adaptive so ineffective predictors can be removed (see paragraph 0016), can adapt to changing conditions like demographics, economic, job content, or job effectiveness (see paragraph 0097), further teaches an old algorithm is archived and a new model is deployed (see paragraph 0114)). which includes special purpose software components of the self-healing multi-media employment content generative AI system; (see paragraphs 0121 and 0206-0207, Examiner’s note: Further teaches the model is converted to software code, which is interpreted as “special purpose software components”). and generating self-healing multi-media employment content using AI, which includes special purpose software components of a self-healing multi-media employment content quality check (see paragraphs 0016 and 0149-0150, Examiner’s note: teaches using a quality check of information based on experts or data or ineffectiveness). and bias check AI system (see paragraph 0161, 0205, and 0249, Examiner’s note: teaches determining biases by comparing them to groups and removing them through various ways like filters or dropping them when deemed improper) Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: Danson et al. (United States Patent Application Publication Number: US 2015/0046357) teaches a system and method for evaluating job candidates, which include machine learning (see paragraph 0032) of multi media content (See paragraph 0030) which updates based on feedback (see paragraph 0049) Pattabiraman et al. (United States Patent Application Publication Number: US 2018/0322463) teaches a system of increasing a user’s interaction with job posting (See abstract) based on machine learning (see paragraph 0091) and updating over time based on real time feedback (see paragraph 0023) Mondal et al. (United States Patent Application Publication Number: US 2020/0184422) teaches a system for screening potential candidates for employment (see abstract) based on machine learning (see paragraphs 0039-0041) where the models control bias (see paragraph 0031) Any inquiry concerning this communication or earlier communications from the examiner should be directed to KIERSTEN SUMMERS whose telephone number is (571)272-6542. The examiner can normally be reached Monday - Friday 7-3:30. 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, Nathan Uber can be reached on 5712703923. 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. /KIERSTEN V SUMMERS/Primary Examiner, Art Unit 3626
Read full office action

Prosecution Timeline

Dec 16, 2024
Application Filed
Nov 20, 2025
Non-Final Rejection — §101, §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
12%
Grant Probability
27%
With Interview (+15.1%)
3y 11m
Median Time to Grant
Low
PTA Risk
Based on 296 resolved cases by this examiner. Grant probability derived from career allow rate.

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