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 .
This Final Office Action is responsive to Applicant's amendment filed on 23 December 2025. Applicant’s amendment on 23 December 2025 amended Claims 1, 13, and 17. Currently Claims 1-9, 11, and 13-20 are pending and have been examined. Claims 10, 12, and 21 were previously canceled. The Examiner notes that the 101 rejection was has been maintained.
Examiner’s Note
The Examiner Notes that the claims would be in consideration for allowance once the 101 rejection has been overcome.
Response to Arguments
Applicant's arguments filed 23 December 2025 have been fully considered but they are not persuasive.
The Applicant argues on pages 3-4 that “In revised Prong Two, the MPEP states that a claim which "integrates the judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception." Further, if "[t]he claim as a whole integrates the judicial exception into a practical application, in which case the claim is not directed to a judicial exception (Step 2A: NO) and is eligible" MPEP 2106.04(d). In other words, when the "claim as a whole integrates the recited judicial exception into a practical application of the exception," that claim should be determined to be patent-eligible. Amended independent Claim 1 recites a computer-implemented method comprising: identifying historical shelfware information for software products for different customers of a software provider; Applicant respectfully submits that the Present Application is directed to the practical application of automatic deployment, in response to a machine learning prediction, of adoption assets that reduce risk of software turning into shelfware and does so through specific technical operations that require advanced computing methods to perform. Furthermore, with respect to Ex Parte Desjardins, Applicant respectfully submits that the Present Application also involves training a machine learning model on a series of tasks. Moreover, as with Ex Parte Desjardins, the Present Application describes various technical improvements. For example, with the claimed solution, in response to a machine learning prediction, "resolving cases of potential shelfware so as to avoid shelfware results in a higher resource utilization rate related to the software product" that results in "resource use related to purchased software [being] more efficient, because a likelihood is reduced of wasting resources for distribution, installation, and deployment of software that does not get used." Present Application at [0012]”.
The Examiner respectfully disagrees.
The Examiner has carefully considered Applicant's arguments regarding integration into a practical application under Step 2A Prong Two and finds them unpersuasive for the reasons indicated below.
Applicant argues that amended Claim 1 integrates the judicial exception into a practical application by automatically deploying adoption assets in response to machine learning predictions to reduce shelfware risk. Applicant further argues that the claimed invention provides technical improvements in resource utilization efficiency by reducing wasted computing resources associated with unused software distribution, installation, and deployment.
The Examiner acknowledges that MPEP 2106.04(d) provides that a claim integrates a judicial exception into a practical application when it applies, relies on, or uses the exception in a manner that imposes a meaningful limit on the exception. However, the Examiner must evaluate whether the additional elements, when considered individually and in combination, integrate the abstract idea into a practical application.
With respect to Applicant's assertion regarding resource efficiency improvements, the Examiner notes that the specification describes these benefits primarily in terms of business efficiency rather than technical improvements to computer functionality. Specifically, paragraph [0012] describes reducing "wasted resources for distribution, installation, and deployment of software that does not get used" and achieving "a higher resource utilization rate related to the software product." These benefits represent improvements to business operations and resource allocation decisions rather than improvements to computer technology itself. Under MPEP 2106.05(a), an improvement must be to the functioning of a computer or to another technology or technical field, not merely using computers as tools to perform existing processes more efficiently.
Furthermore, the claimed method of identifying historical information, training machine learning models, generating predictions, and deploying assets in response to predictions represents the application of generic computer functions to implement an abstract idea of risk assessment and mitigation. The mere automation of manual processes through machine learning does not, without more, constitute integration into a practical application. See MPEP 2106.05(f)(2).
Regarding Applicant's citation to Ex Parte Desjardins, the Examiner notes that each case must be evaluated on its own merits based on the specific claim language and supporting disclosure. Without more specific information about how the claimed invention improves computer functionality or technology beyond using computers as tools, the cited decision does not establish patent eligibility for the present claims. The rejection is therefore maintained.
The Applicant argues on page 4 that “Furthermore, as with Ex Parte Desjardins, the Present Application identifies improvements as to how the machine learning model itself operates. The technical solution described in the specification includes training and tuning a plurality of machine learning models, including a different model for each combination of a software provider customer and a product for which shelfware predictions are generated. For example, paragraph [0058] of the Present Application recites that the solution involves "a model building process 424 that can be used to build a model 426 for a logical product for a customer." The technical solution also involves "optimiz[ing] model parameters in a parameter optimization phase 432 (e.g., using hyperparameter tuning." Id. A result of the technical solution is that a plurality of different models are tuned and trained. For instance, the Present Application recites, at paragraph [0059], that "[m]odels for which an accuracy test 434 results in at least a threshold accuracy (e.g., 70% accuracy) can be included in a set of final logical product models 436 (e.g., where each model in the set of final logical product models 426 is trained to predict shelfware for a given logical product for a given customer)."
As with Ex Parte Desjardins, the amended claims reflect the improvements described in the specification. For example, regarding machine learning improvement, the present claims recite "tuning each machine learning model of the plurality of machine learning models by determining, for each machine learning model, machine learning hyperparameters that result in a most accurate shelfware prediction for a particular product and a particular customer, as compared to other machine learning hyperparameters evaluated for the particular product and the particular customer." As a further example, regarding technical improvement of a computer, the present claims recite "in response to determining that the likelihood of the first shelfware risk prediction received from the first trained machine learning model is more than a threshold ... automatically deploying the at least one adoption asset to automatically reduce a shelfware risk of the first software product and reduce a risk of computing resources wasted by shelfware”.
The Examiner respectfully disagrees.
In response to the arguments in the Examiner notes that careful consideration has been given to the Applicant's arguments regarding improvements to machine learning model operation and finds them unpersuasive for the reasons set forth below.
Applicant argues that the claimed invention improves how the machine learning model itself operates by training and tuning a plurality of models, with each model corresponding to a specific customer-product combination, and by performing hyperparameter optimization to achieve threshold accuracy levels. Applicant contends that the claims reflect these improvements and are therefore patent-eligible under Step 2A Prong Two.
The Examiner acknowledges that the specification describes training multiple machine learning models with hyperparameter tuning for different customer-product combinations. However, the claimed limitations regarding "tuning each machine learning model...by determining...machine learning hyperparameters that result in a most accurate shelfware prediction" recite conventional machine learning training techniques that are well-understood, routine, and conventional in the field. Hyperparameter tuning to optimize model accuracy is a standard practice in machine learning development and does not constitute an improvement to machine learning technology itself. See MPEP 2106.05(d) regarding well-understood, routine, conventional activity.
Moreover, the claims do not recite any specific, unconventional machine learning technique or architecture that improves upon existing machine learning methods. The specification describes using standard techniques such as random forest classifiers (paragraph [0058]), grid search for hyperparameter optimization (paragraph [0058]), and accuracy testing (paragraph [0059]). Creating multiple models for different scenarios using conventional training techniques represents routine implementation of machine learning, not an advancement in machine learning technology.
With respect to the "automatically deploying the at least one adoption asset to automatically reduce...computing resources wasted by shelfware" limitation, the Examiner maintains that this recites a desired result or outcome rather than a specific technological improvement to computer functionality. The claim does not specify how the deployment occurs or how it technically reduces resource waste at the computer level. Rather, it describes a business process outcome where better business decisions (deploying adoption assets) lead to better business results (reduced wasted software licenses). The reduction in "computing resources wasted by shelfware" is an indirect consequence of improved business decision-making, not a direct improvement to computer technology or computer operations.
Under MPEP 2106.05(a), to constitute an improvement to computer functionality or another technology, the claim must recite specific technical means or methods that achieve the improvement. The present claims recite the result of reducing wasted resources but do not recite how this is technically achieved beyond applying machine learning predictions to business decisions. This is insufficient to establish integration into a practical application. The rejection under 35 U.S.C. 101 is maintained.
The Applicant argues on pages 5-6 that “In further detail regarding technical improvement, paragraph [0014] of the Present Application recites: With the claimed solution "a proactive determination of shelfware risk can enable a successful and efficient use of resources for mitigation actions during the post-sales window in which mitigation actions are likely to be successful." Id. at [0015]. Applicant notes that the Office Action alleges, on page 8, that the "claims recite a mental process." Applicant respectfully disagrees. The claims specifically recite "automatically identifying, for at least a first top contributing risk factor that contributed to a highest degree to the shelfware risk likelihood of the first shelfware risk prediction, at least one adoption asset" and "automatically deploying the at least one adoption asset to automatically reduce a shelfware risk of the first software product by automatically addressing the first top contributing risk factor."
The Present Application recites, at [0024], that "an automated adoption assistant 130 can automatically identify, from an adoption asset repository 132 (or multiple adoption asset repositories), relevant adoption assets 134 that are relevant for addressing the contributing risk factors 126 or the shelfware risk prediction 115." Furthermore, the Present Application recites, at [0043], that the claimed solution includes "automatic triggering of shelfware containment actions that use deployed adoption assets. The Present Application further recites, at [0023], regarding automatic identification of assets… In addition, the claimed solution can enable timely action that might not otherwise be possible. For example, as described in the Present Application at [0044]”.
The Examiner respectfully disagrees.
In response to the arguments it is noted that the Examiner has carefully considered Applicant's arguments regarding technical improvements and mental process allegations, and finds them unpersuasive for the reasons set forth below.
Applicant argues that the claims do not recite a mental process because they recite "automatically identifying" and "automatically deploying" adoption assets, and cites specification paragraphs describing automated adoption assistance and automatic triggering of shelfware containment actions. Applicant further argues that the proactive determination of shelfware risk enables efficient use of resources during a post-sales window.
With respect to the mental process consideration, the Examiner acknowledges that the claims recite automation through use of computers. However, the mere use of a computer to automate what could otherwise be performed as a mental process does not automatically render the claims patent-eligible. Under MPEP 2106.04(a)(2)(III), concepts performed in the mind but for practical application are being performed by a computer are still considered abstract ideas that fall within the mental process grouping. The underlying concept of evaluating risk factors and selecting appropriate resources to address those risk factors can be performed in the human mind or with pen and paper, even if such performance would be time-consuming or impractical.
The process of: (1) analyzing historical data to identify patterns, (2) applying those patterns to predict future outcomes, (3) identifying factors contributing to a prediction, (4) matching resources to address those factors, and (5) deploying those resources, represents a fundamental economic practice and method of organizing human activity that could be performed mentally or manually. The automation of this process through computers does not transform the abstract idea into something patent-eligible without additional elements that integrate the exception into a practical application.
Regarding the "technical improvement" argument based on proactive determination and efficient resource use, the Examiner reiterates that the specification describes improvements to business processes and business decision-making rather than improvements to computer technology. Paragraph [0015]'s discussion of "successful and efficient use of resources for mitigation actions during the post-sales window" describes improved business operations timing and resource allocation. Similarly, paragraph [0044]'s discussion of enabling "timely action that might not otherwise be possible" describes improved business process outcomes, not improvements to computer functionality or another technology.
The claimed "automatically identifying" and "automatically deploying" limitations represent the application of generic computer functions (data retrieval, pattern matching, and data transmission) to implement the abstract idea. Under MPEP 2106.05(f), merely applying the abstract idea using a generic computer does not amount to significantly more than the abstract idea itself, nor does it integrate the abstract idea into a practical application. The rejection under 35 U.S.C. 101 is maintained.
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.
Claims 1-9, 11, and 13-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter because the claim(s) 1-9, 11, and 13-20as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea. The claim(s) 1-9, 11, and 13-20 is/are directed to the abstract idea of determining shelfware based on risk prediction without significantly more than the judicial exception itself.
Step 1
Regarding Step 1 of the Subject Matter Eligibility Test for Products and Processes (from the January 2019 §101 Examination Guidelines), claim(s) (1-9, and 11) is/are directed to a method, claim(s) (13-16) is/ are directed to a system, and claims(s) (17-20) is/are directed to a non-transitory storage medium and therefore the claims recites a series of steps and, therefore the claims are viewed as falling in statutory categories.
Step 2A Prong 1
The claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) a mental process. Specifically, the independent claims 1, 13, and 17 recite a mental process: as drafted, the claim recites the limitation of identify shelfware based on risk prediction which is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting processors nothing in the claim precludes the determining and tuning steps from practically being performed in the human mind. For example, but for the processors language, the claim encompasses the determining and tuning shelfware based on risk prediction manually.
The mere nominal recitation of a generic processors does not take the claim limitation out of the mental processes grouping. This limitation is a mental process. While the Guidance provides that claims do not recite a mental process when they contain limitations that can practically be performed in the human mind, for instance when the human mind is not equipped to perform the claim limitations (network monitoring, data encryption for communication, rendering images). Therefore, these limitations are viewed as a mental process. The specification makes it clear that the claimed invention is directed to the mental activity of data gathering, and data analysis to determine determining shelfware”.
Step 2A Prong 2
Specifically, the determined judicial exception is not integrated into a practical application because the generically recited computer elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer and additionally that data gathering steps required to use the correlation do not add a meaningful limitation to the method as they are insignificant extra-solution activity.
The claim recites the additional element(s): that a processor is used to perform the determining and tuning steps. The processor in the step is recited at a high level of generality, i.e., as a generic processor performing a generic computer function of processing data (identify shelfware based on risk prediction). This generic processor limitation is no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to the abstract idea.
The claim recites the additional element(s): identifying shelfware, determining to generate, tuning each machine learning model, identifying a first trained machine learning model, receiving a risk prediction, identifying a top contributing factor, deploying one adoption asset, and providing the shelfware risk performs the determining and tuning steps. The identifying, determining, tuning, identifying, receiving, determining, identifying, deploying, and providing steps are recited at a high level of generality (i.e., as a general means of managing data for use in the determining step), and amounts to mere data manipulation, which is a form of insignificant extra-solution activity. The processor that performs the determining and tuning steps is also recited at a high level of generality, and merely automates the determining and tuning steps. Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer component (the processors).
The Examiner has further determined that the claims as a whole does not integrate a judicial exception into a practical application in order to provide an improvement in the functioning of a computer or an improvement to other technology or technical field. It has been determined that based on the disclosure does not provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. It has not been provided clearly in the disclosure that the alleged improvement would be apparent to one of ordinary skill in the art, but is instead in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art, and therefore does not improve the technology). Second, in the instance, which in this case it is not clear that the specification sets forth an improvement in technology, the claim must not reflect the disclosed improvement (the claims must include components or steps of the invention that provide the improvement described in the specification).
For further clarification the Examiner points out that the claim(s) 1-9, 11, and 13-20 recite(s) identifying shelfware, determining to generate, tuning each machine learning model, identifying a first trained machine learning model, receiving a risk prediction, determining the likelihood, identifying a top contributing factor, deploying one adoption asset, and providing the shelfware risk which are viewed as an abstract idea in the form of a mental process. This judicial exception is not integrated into a practical application because the use of a computer for identifying, determining, tuning, identifying, determining, receiving, identifying, deploying, and providing which is the abstract idea steps of valuing an idea (using analyzed data to determine shelfware based on risk prediction) in the manner of “apply it”.
Thus, the claims recites an abstract idea directed to a mental process (i.e. to calculate the marketing for a user based on consumer interactions). Using a computer to obtaining, classifying, quantifying, generation, identifying, and determining the data resulting from this kind of mathematically-based, mental process merely implements the abstract idea in the manner of “apply it”
The dependent claims recite elements that narrow the metes and bounds of the abstract idea but do not provide ‘something more’.
The dependent claims do not remedy these deficiencies.
Claims 11 recite limitations which further limit the claimed analysis of data.
Claims 5, 9, and 18 recites limitations directed to claim language viewed insignificantly extra solution activity.
Claims 2-4, 6-8, 14-16, 19, and 20 recites limitations directed to claim language viewed non-functional data labels.
Thus, the problem the claimed invention is directed to answering the question based on gathered and analyzed information about the status of software to determine if it is shelfware. This is not a technical or technological problem but is rather in the realm of software management and therefore an abstract idea.
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed with respect to Step 2A Prong Two, the additional element in the claim amounts to no more than mere instructions to apply the exception using a generic computer component.
The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. This is the case because in order for the claims to be viewed as significantly more the claims must incorporate the integral use of a machine to achieve performance of a method, in contrast to where the machine is merely an object on which the method operates, which does not provide significantly more in order for a machine to add significantly more, it must play a significant part in permitting the claimed method to be performed, rather than function solely as an obvious mechanism for permitting a solution to be achieved more quickly. Whether its involvement is extra-solution activity or a field-of-use, i.e., the extent to which (or how) the machine or apparatus imposes meaningful limits on the claim. Use of a machine that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not provide significantly more. Additionally, another consideration when determining whether a claim recites significantly more is whether the claim effects a transformation or reduction of a particular article to a different state or thing. "[T]ransformation and reduction of an article ‘to a different state or thing’ is the clue to patentability of a process claim that does not include particular machines. All together the above analysis shows there is not improvement in computer functionality, or improvement to any other technology or technical field. The claim is ineligible.
Additionally, with respect to the Berkheimer as noted above the same analysis applies to the 2B where the claims are viewed as applying it and as such no further analysis is required. However, with respect to the claims that are viewed as extra solution or post solution activity the Examiner notes that the claims are viewed as well-understood, routine, and conventional because a citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s). An appropriate publication could include a book, manual, review article, or other source that describes the state of the art and discusses what is well-known and in common use in the relevant industry. The claim is ineligible.
The dependent claims recite elements that narrow the metes and bounds of the abstract idea but do not provide ‘something more’. Specifically, the dependent claims do not remedy these deficiencies of the independent claims.
With respect to the legal concept of prima facie case being a procedural tool of patent examination, which allocates the burdens going forward between the examiner and the applicant. MPEP § 2106.07 discusses the requirements of a prima facie case of ineligibility. In particular, the initial burden was on the Examiner and believed to be properly provided as to explain why the claim(s) are ineligible for patenting because of the above provided rejection which clearly and specifically points out in accordance with properly providing the requirement satisfying the initial burden of proof based on the Guidance from the United States Patent and Trademark Office and the burden now shifts to the applicant.
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.
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/S.S.S/Examiner, Art Unit 3625
/BETH V BOSWELL/Supervisory Patent Examiner, Art Unit 3625