DETAILED ACTION
Status of Claims
The following is a FINAL OFFICE ACTION in response to applicant’s amendments to and response for Application #17/199,077, filed on 05/11/2026.
Claims 1-6, 9-15, and 18-24 are now pending and have been examined.
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 1-6, 9-15, and 18-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The rationale for this finding is explained below.
Per Step 1 of the analysis, the claims are analyzed to determine if they are directed to statutory subject matter. Claim 15 claims a method, or process. A method, or process, is a statutory category for patentability. Claim 1 claims a system comprising a processor and a datastore. Therefore, the system is interpreted as an apparatus. An apparatus is a statutory category for patentability. Claim 20 claims a non-transitory computer-readable storage medium. Therefore, the claim is interpreted as an article of manufacture. An article of manufacture is a statutory category for patentability. Further, the claim is in conformity with the Kappos Memorandum of 2010 regarding medium claims, as it includes the phrase “non-transitory.”
Per Step 2A, Prong 1 of the analysis, the examiner must now determine if the claims are directed to an abstract idea or eligible subject matter. In the instant case, the independent claims are directed towards an abstract idea. Specifically, claim 1 is directed to “receive…the current repair data for a vehicle repair, the vehicle repair being a pending vehicle repair and including replacing or repairing a part of a vehicle, select, based on the current repair data and at least one of historical data or an existing repair specification, a predicted material to be used during vehicle repair, the vehicle repair including replacing or repairing a part of the vehicle, predict a quantity of the predicted material to be used during the vehicle repair based on the current repair data and at least one of the historical data or the existing repair specification, generate a predicted material repair (PMR) plan that includes the predicted material and predicted quantity of the predicted material for the vehicle, compare the actual quantity of the actual material to the predicted quantity of the PMR plan, generate, based on the comparison, data indicating whether the vehicle repair was performed according to the PMR plan, and automatically initiate remedial actions based on the generated data, wherein the remedial actions are selected from the group of maintaining inventory levels, generating orders for additional materials, and notifying relevant parties to re-evaluate or redo a repair. Specifically, the claims are directed to a mental process. A human operator with access to the repair data and the information in the data store can mentally make a judgment based on analysis and calculations regarding a quantity and type of material that will be needed for a vehicle repair. The human operator could mentally as part of making a judgment generate a predicted material repair plan and perform at least one action such as approving the plan, initiating the plan, communicating the plan, or other such action. Further, the quantity of actual to predicted material can be compared mentally as part of the analysis, data can be generated, and initiation of remedial actions can be decided as part of a judgment or opinion based on the data analysis. The processor and data store simply use technology to automate the abstract idea. Therefore, the claims are directed to an abstract idea, specifically a mental process.
Per Step 2A, Prong 2 of the analysis, the examiner must now determine if the claims integrate the abstract idea into a practical application. The additional elements of the claims include the recitation of a “processor,” “a datastore,” “a computing device at a vehicle repair facility,” “a network,” a “vehicle repair management system” and a variety of “modules.” However, these components are considered generic recitations of technical elements which are recited at a high level of generality. These components are being used as “tools to automate the abstract idea” (see MPEP 2106.05 (f)), and do not integrate the abstract idea into a practical application. They are not recitations of a special purpose computer or transformation (see MPEP 2106.05 (b) and (c)). The claims also recited the additional element of the datastore storing historical data or existing repair specification. However, absent any further detail, these additional elements are considered “receiving, processing, and /or storage of data, which is listed in the MPEP 2106.05 (d) (II) (iii)-(iv) as an example of conventional computer functioning- see “storing and retrieving information in a memory,” citing Versata Dev Grp v SAP, OIP Techs v Amazon.com, and “electronic recordkeeping,” citing Alice Corp. Therefore, the storing step does not integrate the abstract idea into a practical application. The claims also recited the additional element of “receive data indicating an actual material used during the vehicle repair and an actual quantity of the actual material used during the vehicle repair” and added by amendment “receive, from a computing device at a vehicle repair facility via a network, the current repair data….” However, absent any further detail, this additional element is considered “receiving, processing, and /or storage of data, which is listed in the MPEP 2106.05 (d) (II) (iii)-(iv) as an example of conventional computer functioning- see “receiving and/or transmittal of data over a network,” citing Versata Dev Grp v SAP, OIP Techs v Amazon.com, and buySAFE v Google. Therefore, this additional element does not integrate the abstract idea into a practical application.
Per Step 2B of the analysis, the examiner must now determine if the claims include limitations that are “significantly more” than the abstract idea by demonstrating an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. The additional elements of the claims include the recitation of a “processor,” “a datastore,” “a computing device at a vehicle repair facility,” “a network,” a “vehicle repair management system” and a variety of “modules.” However, these components are considered generic recitations of technical elements which are recited at a high level of generality. These components are being used as “tools to automate the abstract idea” (see MPEP 2106.05 (f)), and are not considered significantly more than the abstract idea itself. They are not recitations of a special purpose computer or transformation (see MPEP 2106.05 (b) and (c)). The claims also recited the additional element of the datastore storing historical data or existing repair specification. However, absent any further detail, these additional elements are considered “receiving, processing, and /or storage of data, which is listed in the MPEP 2106.05 (d) (II) (iii)-(iv) as an example of conventional computer functioning- see “storing and retrieving information in a memory,” citing Versata Dev Grp v SAP, OIP Techs v Amazon.com, and “electronic recordkeeping,” citing Alice Corp. Therefore, the storing step is not considered significantly more. The claims also recited the additional element of “receive data indicating an actual material used during the vehicle repair and an actual quantity of the actual material used during the vehicle repair” and added by amendment “receive, from a computing device at a vehicle repair facility via a network, the current repair data….” However, absent any further detail, this additional element is considered “receiving, processing, and /or storage of data, which is listed in the MPEP 2106.05 (d) (II) (iii)-(iv) as an example of conventional computer functioning- see “receiving and/or transmittal of data over a network,” citing Versata Dev Grp v SAP, OIP Techs v Amazon.com, and buySAFE v Google. Therefore, these additional elements are not considered significantly more than the abstract idea itself.
When considered as an ordered combination, the claims still are considered to be directed to an abstract idea. The claims recite the logical set of steps for determining a predicted material to be used in a vehicle repair, determining a predicted quantity of the material to be used during the repair, determining a repair plan, and performing an action related to the repair plan. Therefore, the ordered combination does not lead to a determination of significantly more.
When considering the dependent claims, claims 2-4 as written are considered conventional computer functioning, and the equivalent of “apply it,” or using a computer as a tool to perform the abstract idea (see MPEP 2106.05 (f)). The claims recited the input and output of the data “into a machine learning model” and “training a machine learning algorithm,” but there is no detail whatsoever as to how the “model” would come up with the output or how the model is trained other than what data is used. The claims are recited at a high level of generality and are therefore the equivalent of “apply it,” or using a computer as a tool. Claim 5 is considered part of the abstract idea as analyzing historical data and taking such as an average of past repairs would be well within what could be considered a mental process of analyzing the data and making a judgment based on the analysis. The use of the processor has been addressed above. Claim 6, namely communicating the plan to a user, could be considered part of the abstract idea, as communicating could be done verbally. Assuming that it is done electronically over some kind of network, then the claim, absent further detail, is considered “receiving and/or transmission of data over a network, which is listed in the MPEP 2106.05 (d) (II) (i) as an example of conventional computer functioning- see “receiving or transmitting data over a network,” citing Symantec, OIP Techs v Amazon.com, and buySAFE v Google. Therefore, this step is not considered significantly more than the abstract idea itself. Claim 9 is considered part of the abstract idea, as the type of material does not change the analysis or the way any of the mental steps would be carried out. Claim 10 is considered to be part of the abstract idea, as determining whether a manufacturer specified material is to be used and comparison to the predicted material and subsequent data output to a third-party is considered part of data analysis and making a judgment which is a mental process. Claim 11 is considered part of the abstract idea, as the repair data including mileage data does not change the analysis or the way any of the mental steps would be carried out. Claim 12 is considered part of the abstract idea, as the type of historical repair data and model year does not change the analysis or the way any of the mental steps would be carried out. Claim 13 is considered part of the abstract idea, as generating an order as the performed action could be done as part of a mental process, absent further detail. Claim 14 is considered part of the abstract idea, as a Markush Group of variables used to predict a quantity of materials does not change the analysis or the way any of the mental steps would be carried out, as it would still involve analysis of data mentally followed by making a judgment on a predicted quantity of materials needed for the repair. Claim 21 is considered part of the abstract idea, as the type of repair data does not change the mental analysis of the repair data. Claims 22-23 added by amendment include “automatically generate an estimated invoice based on the PMR plan…” (claim 22), “automatically generate an actual invoice based on the actual material used and the actual quantity of the actual material used during the vehicle repair…” (claim 23). However, these claims only recite the automation of generating an invoice using the data available. Generating an estimated or actual invoice based on a plan or material and quantity data is considered conventional computer functioning and not significantly more. Further, the examiner takes Official Notice that it is old and well known in the commerce arts to generate an estimated or actual invoice based on actual quantity and type of material or estimated amounts of material quantity and type for a job or repair. There is no improvement to invoice creation, the computer itself, another technology, or the technical field. Claim 24 recited “output at least one of the estimated invoice and the actual invoice….” Absent further detail, this additional element is considered “receiving and/or transmission of data over a network, which is listed in the MPEP 2106.05 (d) (II) (i) as an example of conventional computer functioning- see “receiving or transmitting data over a network,” citing Symantec, OIP Techs v Amazon.com, and buySAFE v Google. Therefore, this additional element is not considered significantly more than the abstract idea itself. The other dependent claims mirror those already discussed above.
Therefore, claims 1-6, 9-15, and 18-24 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. See Alice Corporation Pty. Ltd. Vs. CLS Bank International et al., 2014 (please reference link to updated publicly available Alice memo at http://www.uspto.gov/patents/announce/alice_pec_25jun2014.pdf as well as the USPTO January 2019 Updated Patent Eligibility Guidance.)
Response to Arguments
Regarding the rejections based on 35 USC 101:
Regarding the applicant’s argument on pages 8-9 of the response that the claims cannot be performed in the human mind because the operations are machine-based and expressly tied to specialized software modules executing on hardware and that the claims include automatic initiation of remedial actions:
The rationale is not a basis for eligibility. An abstract idea can still be implemented on a computer. Court decisions such as OIP Techs v Amazon.com, buySAFE v Google, and countless others recite multiple components such as servers, networks, databases, processors, and interfaces that in conjunction perform the various operations in such as an ecommerce system yet the claims were still found to recite an abstract idea.
Further, simply reciting “automatic” does not make claims eligible. If an abstract idea is implemented in a particular technological environment using generic components such as a computer and software, the claims are still considered to recite an abstract idea, and the “automatic” portion is treated in the Step 2A, Prong 2 and Step 2B analyses. The standards laid out in 2106.05 (f) include that the claims must show more than the equivalent of “apply it,” or using a computer as a tool to implement the abstract idea, but must include an improvement to the computer itself, another technology, or the technical field.
Regarding the applicant’s argument on page 9 of the response that the claims integrate the abstract idea into a practical application because they result in the automatic initiation of remedial actions that affect the physical world and improve the process of vehicle repair management…ensures that the correct materials and quantities are used, thereby increasing safety and reliability of vehicle repairs…automates inventory management and order generation, which improves the efficiency and accuracy of the repair process:
The MPEP at 2106.05 (f) gives criteria for claims integrating an abstract idea into a practical application as including “an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field.” The examiner sees no such improvement here. “Vehicle repair management” is not a technical field, but a business practice or a mental process. There is no technical process or improved computer functioning that is involved in the “correct materials and quantities.” In fact, the applicant even says that the claims AUTOMATE inventory management and order generation, which are clearly not technical fields but part of routine business practice. The fact that the automatically initiated actions affect the physical world does not change the analysis. The abstract idea can be a mental process and still have an affect on the physical world. Do not all mathematical calculations that result in some kind of judgment or decision eventually affect the physical world if they are applied to a particular physical environment? Court decisions such as OIP Techs v Amazon.com and buySAFE v Google include e-commerce systems that clearly affect the ordering, shipping and delivery of products, but they were still found to be directed to abstract ideas.
Regarding the applicant’s argument on page 10 of the response that the claims do not broadly preempt the concept of predicting materials for vehicle repair:
As the Federal Circuit pointed out in Ariosa Diagnostics, Inc. v. Sequenom, Inc. (Fed. Cir. June 12, 2015, #2014-1139, 2014-1144), “while preemption may signal patent ineligible subject matter, the absence of complete preemption does not demonstrate patent eligibility. ... Where a patent' s claims are deemed only to disclose patent ineligible subject matter under the Mayo framework, as they are in this case, preemption concerns are fully addressed and made moot” (slip op. pp. 14-15). Similarly, in OIP Technologies, Inc. vs. Amazon.com, Inc. (Fed. Cir., June 11,2015, #2012-1696), the Federal Circuit held “that the claims do not preempt all price optimization or may be limited to price optimization in the e-commerce setting do not make them any less abstract. See buySAFE, Inc. v.Google, Inc., 765 F.3d 1350, 1355 (Fed. Cir. 2014) (collecting cases); Accenture, 728 F.3d at 1345”.
Regarding the applicant’s argument on pages 10-11 of the response that the claims are similar to the patent eligible claims in Example 47 of the July 2024 Subject Matter Eligibility Examples:
While the examiner appreciates the similarities, the examiner does not see the same level of technical detail as in the example.
In the current claims, there is no similar technical process. The prediction is recited at a high level of generality, and at best the machine learning in the dependent claims is recited as being already “trained” and then used with no detail. The rest of the steps are comparing and generating steps, with the last step literally as recited “automatically” initiating remedial actions that are routine business practices such as generating orders for additional materials. There is no technical detail in how these processes are performed.
In Example 47, there are very specific technical steps to describe the initial identification of the anomaly in network traffic and what is done on a technical level in real time, and then future traffic from the source address is blocked.
detecting one or more anomalies in network traffic using the trained ANN;
(c) determining at least one detected anomaly is associated with one or more malicious network packets;
(d) detecting a source address associated with the one or more malicious network packets in real time;
(e) dropping the one or more malicious network packets in real time; and
(f) blocking future traffic from the source address.
The examiner does not see similar technical detail in the current claims as amended.
Regarding the applicant’s argument on page 11 of the response that the automatic initiation of specific remedial actions by the inventory management module…is a practical application regardless of whether the domain is characterized as business or technical:
The applicant seems to be using the plain meaning of “practical” in this argument. The step 2A, Prong 2 analysis is using a specific meaning of “practical” to not include any application of the abstract idea whatsoever that could be considered to be useful or have some kind of real-world result. But, as is stated in the MPEP 2106.05, the claims are determined to integrate the abstract idea into a practical application when the claims include “an improvement to the computer itself, another technology, or the technical field.” The examiner sees no such improvement in the current claims.
Regarding the applicant’s argument on page 11 of the response that the claims are eligible under Step 2B:
The applicant gives no reasoning to support their assertion other than that the claim steps are not conventional, routine, or well-understood. But, the examiner points out that the Step 2B analysis is not of the claims as a whole, but of the additional elements beyond the abstract idea itself. Therefore, each and every element of the claims need not be shown to be conventional, routine, or well-understood in order for the claims to be considered patent ineligible.
Regarding the applicant’s argument on page 12 of the response that the training and use of the trained ANN supports eligibility:
The examiner disagrees. The training of the model is only recited at a very high level, only describing generally what data is used for training. There is no detail at all as to a set of training steps. Further, the “use” of the model is only to perform a couple of mental steps that are instead done by the model. There is no detail at all as to how the model is used. Starting in August 2024 and in more recent Memorandums the USPTO has laid out eligibility in terms of claims with machine learning and AI. As with Example 47, which the applicant references, including a couple of general broadly recited training and use steps that include machine learning and AI does not lead to claim eligibility. CLAIM 2 of example 47 is considered INELIGIBLE even though it shows more detail as to the training and use of the model than the current claims:
A method of using an artificial neural network (ANN) comprising:
(a) receiving, at a computer, continuous training data;
(b) discretizing, by the computer, the continuous training data to generate input data;
(c) training, by the computer, the ANN based on the input data and a selected training algorithm to generate a trained ANN, wherein the selected training algorithm includes a backpropagation algorithm and a gradient descent algorithm;
(d) detecting one or more anomalies in a data set using the trained ANN;
(e) analyzing the one or more detected anomalies using the trained ANN to generate anomaly data; and
(f) outputting the anomaly data from the trained ANN.
Therefore, the arguments are not persuasive and the rejection is sustained.
Conclusion
Applicant amendment(s) necessitated the new grounds of rejection set forth in this Office Action. Therefore, 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 extension fee 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 date of this final action.
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to Luis A. Brown whose telephone number is 571.270.1394. The Examiner can normally be reached on M-F 8:30am-4:30pm EST. If attempts to reach the examiner by telephone are unsuccessful, the Examiner’s supervisor, JESSICA LEMIEUX can be reached at 571.270.3445.
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/LUIS A BROWN/ Primary Examiner, Art Unit 3626
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