DETAILED ACTION
Response to Amendment
This Final office action is in response to Applicant’s amendment filed 4/15/2026. Claims 1 and 9-19 have been amended. Claims 1-20 are pending.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Applicant's arguments filed 4/15/2026 have been fully considered but they are not persuasive.
Drawings
The drawings received on 4/15/2026 are accepted.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claims are directed to an abstract idea without significantly more.
Here, under Step 1 of the Alice analysis, method claims 1-20 are directed to a series of steps. Thus the claims are directed to a process.
Under Step 2A Prong One of the analysis, the claimed invention is directed to an abstract idea without significantly more. The claims recite managing just-in-time bagel production, including receiving, generating, fine-tuning, and providing steps.
The limitations of receiving, generating, fine-tuning, and providing, are a process that, under its broadest reasonable interpretation, covers organizing human activity concepts, but for the recitation of generic computer components.
Specifically, independent claim 1 recites receiving daily bagel inventory predictions for one or more future dates including a target date from historical inventory data, the daily bagel inventory predictions including bagel types and corresponding quantities for the target date; receiving updated historical inventory data corresponding to one or more previous prediction dates; fine-tuning the inventory prediction machine learning model based on ground truth data correlated to the one or more previous prediction dates; generating, using the fine-tuned inventory prediction machine learning model, updated daily bagel inventory predictions for the one or more future dates including the target date; generating an initial bagel production plan for the target date based on the daily bagel inventory predictions, a consumption function, and oven bagel capacity, wherein the initial bagel production plan includes sets of bagels to be cooked at designated times on the target date; generating one or more updated bagel production plans during the target date based on receiving real-time bagel inventory data; and providing an updated bagel production plan for preparing and cooking bagels in one or more ovens at the designated times on the target date according to the updated bagel production plan.
Independent claim 9 recites providing historical inventory data to generate bagel inventory predictions for one or more future dates including a target date, the bagel inventory predictions including bagel types and corresponding quantities for the target date; generating based on the bagel inventory predictions: a bagel preparation plan for the target date that includes a quantity of standard bagel dough; and a bagel production plan for the target date that includes: a first set of bagels of one or more bagel types to begin processing at a first time on the target date for oven-fresh distribution; a second set of bagels of different bagel types to begin processing at a second time on the target date for oven-fresh distribution, wherein the bagel production plan is generated based on the bagel inventory predictions, corresponding consumption function, future orders for bagels on the target date, and oven bagel capacity; wherein the BAS analyzes the bagel types from the bagel inventory predictions using the corresponding consumption functions to generate an initial production plan indicating how much of each bagel type to prepare at each of multiple time intervals, and wherein the oven bagel capacity includes a number of bagels that can be cooked in an oven at a time; providing a current production of the bagel types and a current bagel inventory to the BAS at multiple times throughout the target date; and based on incorporating the current production and the current bagel inventory, updating the initial production plan into a real-time production plan for a current or future time interval; and providing the real-time production plan for preparing and cooking bagels according to the real-time production plan in one or more ovens.
Independent claim 18 recites generating updated bagel inventory predictions for a target date based on historical inventory data, including updated historical inventory data corresponding to the one or more previous prediction dates, the updated bagel inventory predictions including a bagel type and a bagel quantity for the target date, wherein the target date is a future day when the updated bagel inventory predictions are received; generating based on the updated bagel inventory predictions: a bagel preparation plan for the target date that includes a quantity of standard bagel dough; a bagel production plan for the target date that includes: a first number of bagels of the bagel type to begin processing at a first time on the target date for oven-fresh distribution; and a second number of bagels of the bagel type to begin processing at a second time on the target date for oven-fresh distribution, wherein the bagel production plan is generated based on the updated bagel inventory predictions of the bagel type, a consumption function for the bagel type, future orders for bagels of the bagel type, and oven capacity for bagels; and providing the bagel production plan for preparing and cooking bagels of the bagel type according to the bagel production plan.
That is, other than reciting an inventory prediction machine learning model, a processor, a dynamic production system, a baking automation system, and a client device, the claim limitations merely cover managing personal behavior, including following rules or instructions, thus falling within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Under Step 2A Prong Two, the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception. This judicial exception is not integrated into a practical application. The claims include an inventory prediction machine learning model, a processor, a dynamic production system, a baking automation system, and a client device. The inventory prediction machine learning model, processor, dynamic production system, baking automation system, and client device in the steps is recited at a high-level of generality, such that it amounts 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. As a result, the claims are directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of an inventory prediction machine learning model, a processor, a dynamic production system, a baking automation system, and a client device amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
None of the dependent claims recite additional limitations that are sufficient to amount to significantly more than the abstract idea. Claims 2-5 recite additional receiving, updating and providing steps. Claims 6-8 recite an additional updating step, and further describe the dynamic production system and the bagel preparation plan. Similarly, dependent claims 10-17, 19 and 20 recite additional details that further restrict/define the abstract idea. A more detailed abstract idea remains an abstract idea.
Under step 2B of the analysis, the claims include, inter alia, an inventory prediction machine learning model, a processor, a dynamic production system, a baking automation system, and a client device.
As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount 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 on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
There isn’t any improvement to another technology or technical field, or the functioning of the computer itself. Moreover, individually, there are not any meaningful limitations beyond generally linking the abstract idea to a particular technological environment, i.e., implementation via a computer system. Further, taken as a combination, the limitations add nothing more than what is present when the limitations are considered individually. There is no indication that the combination provides any effect regarding the functioning of the computer or any improvement to another technology.
In addition, as discussed in paragraph 0180 of the specification, “In various implementations, the computer system 1200 represents one or more of the client devices, server devices, or other computing devices described above. For example, the computer system 1200 may refer to various types of network devices capable of accessing data on a network, a cloud computing system, or another system. For instance, a client device may refer to a mobile device such as a mobile telephone, a smartphone, a personal digital assistant (PDA), a tablet, a laptop, or a wearable computing device (e.g., a headset or smartwatch). A client device may also refer to a non-mobile device such as a desktop computer, a server node (e.g., from another cloud computing system), or another non-portable device.”
As such, this disclosure supports the finding that no more than a general purpose computer, performing generic computer functions, is required by the claims.
Viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. See Alice Corporation Pty. Ltd. v. CLS Bank Int’l et al., No. 13-298 (U.S. June 19, 2014).
Response to Arguments
In the Remarks, Applicant argues Currently amended independent claims 1 and 18 also do not fall within either the certain- methods-of-organizing-human-activity grouping or the mental-process grouping. The Office Action's characterization of the claims as "managing just-in-time bagel production" overgeneralizes the amended claims and does not account for the specific machine-learning limitations now recited. As amended, independent claims 1 and 18 do not merely recite a business objective or a set of human instructions for deciding what bagels to prepare. Rather, they recite a particularized machine-learning implementation involving updated historical inventory data corresponding to previous prediction dates, ground-truth-correlated fine-tuning of an inventory prediction machine learning model, and generation of updated future-date bagel inventory predictions that are then used in downstream preparation and production planning. Those limitations are not commercial interactions, legal interactions, or management of personal behavior, nor are they observations, evaluations, judgments, or opinions that can practically be performed in the human mind. See MPEP § 2106.04(a)(2)(II)-(III); see also the August 4, 2025 Memorandum (reminding examiners not to expand the abstract-idea groupings beyond their proper bounds).
Even if the Office were to continue to view independent claims 1 and 18 as somehow implicating an abstract idea, the amended claims integrate any such idea into practical applications. The Specification identifies a concrete technical problem: bagel production is a multi-day process with precise timing requirements and a short freshness window, while existing systems are inefficient and inflexible. As amended, independent claims 1 and 18 reflect the practical solution disclosed in the
Specification more concretely than the claims addressed in the Office Action. Independent claim 1 recites an updated machine-learning loop tied to prior prediction dates and ground truth data, followed by use of the updated predictions in initial and updated bagel production plans. Independent claim 18 likewise recites a fine-tuned machine-learning model generating updated target-date bagel inventory predictions and then, based on the updated predictions, generating a bagel preparation plan and a timed bagel production plan for efficient distribution. Those claim limitations do more than merely apply an abstract idea on a generic computer. They recite a particular machine-learning update and prediction pipeline used in a specific production- planning workflow directed to a timing-sensitive food-production problem. Under current USPTO guidance, that is a practical application.
As amended, claim 9 recites a baking automation system (BAS) that generates a bagel preparation plan and a bagel production plan based on bagel inventory predictions. The Office Action's Step 2A, Prong One analysis rested on the view that, other than reciting an inventory prediction machine learning model, a dynamic production system, a baking automation system, and a client device, the claim limitations merely covered managing personal behavior, including following rules or instructions. That analysis no longer fits the amended claim language. The Specification explains that the dynamic production system generates an initial bagel production plan based on bagel inventory predictions, consumption functions, and cook capacity, and generates updated bagel production plans throughout the target date based on real-time changes, including current inventory and current production information. Those limitations are not commercial interactions, legal interactions, or management of personal behavior. Nor are they merely "rules" that a human follows. Rather, they are processor-based control operations that rely on repeated ingestion of production-state information during the target date and dynamic modification of future interval-based production outputs. A human mind is not equipped to practically perform that claimed sequence as a whole, particularly in the real-time, multi-interval manner recited. See MPEP § 2106.04(a)(2)(II)-(III).
Independent claim 9 also satisfies Step 2A, Prong Two. Amended independent claim 9 reflects a particular solution to that problem: a processor- based BAS that uses corresponding consumption functions to generate an initial production plan indicating how much of each bagel type to prepare at each of multiple time intervals, then incorporates current production and current bagel inventory at multiple times throughout the target date to update the initial production plan into a real-time production plan for a current or future time interval, and then provides that real-time production plan to a client device for preparing and cooking bagels in one or more ovens. That is a concrete implementation, not merely the idea of "better planning." The August 4, 2025 Memorandum explains that this is the relevant inquiry at Step 2A, Prong Two.
Additionally, given the amendments to independent claim 9, the Office Action's reasoning no longer applies. The Office Action concluded that the claim language amounted to no more than mere instructions to apply the alleged exception using a generic computer component and therefore did not integrate the abstract idea into a practical application. Id., 5-6. As amended, however, currently amended independent claim 9 recites a specific BAS configuration and real- time production-control workflow rooted in the timing-sensitive, capacity-constrained bagel- production environment described in the specification. Thus, currently amended independent claim 9, viewed as a whole, integrates any alleged exception into the practical application of dynamic, interval-based, real-time bagel production control.
Applicant does not concede that any amended claim recites a judicial exception that is not integrated into a practical application. Even so, the amended claims also recite significantly more than the alleged exception. The Office Action concluded that the additional elements amount only to generic computer implementation and that the combination adds nothing more than the limitations considered individually. But current USPTO guidance requires evaluation of the claim as a whole, including the ordered combination of limitations, and recognizes that a meaningful combination of limitations may amount to significantly more even where some elements are known individually.
The ordered combinations of the claims are more particular and more technologically grounded than the claims addressed in the Office Action. Applicant respectfully submits that they amount to significantly more than the alleged abstract idea. Finally, the Office Action itself states that none of the prior art of record, individually or in combination, teaches the key independent-claim features of pending claims 1, 9, and 18. Id., 8-9. Applicant recognizes that novelty is not the test under § 101. Even so, that statement underscores that the claims are not simply reciting a routine, conventional practice at a high level of generality. At minimum, the present record does not support the conclusion that the amended ordered combinations are no more than generic or conventional computer implementation. The Examiner respectfully disagrees.
Regarding Step 2A Prong One, the paragraph 0023 of specification recites that “For example, the dynamic production system provides a production user interface that guides the user through the various steps to prepare and cook bagels and automatically updates (including both frontend and backend updates) based on user input. Other bagel production systems do not provide these types of seamless and interactive user interfaces that reduce menu complexity and lead to efficiency gains throughout the bagel production process.”
Moreover, paragraph 0053 recites that “Additionally, the dynamic production system 206 includes the user interface manager 218, which implements user interface updates associated with the dynamic production system 206. For example, the user interface manager 218 provides the bagel inventory predictions 222 and the preparation plans 224 to the production client device 236 for bagels to be prepared according to a bagel preparation plan or a bagel production plan.”
Additionally, paragraph 0074 recites “Additionally, as shown, the BAS 306 provides the target date bagel preparation plan 324 to the production client device 236. For example, the BAS 306 provides the target date bagel preparation plan 324 to a client application on the production client device 236, which displays it to a user making the raw bagel dough”, while paragraph 0090 recites that “FIG. 3B shows the BAS 306 providing the initial bagel production plan 326 to the production client device 236. In various implementations, users follow the initial bagel production plan 326 to make initial preparations for bagel production on the target day, such as preparing trays with raw rolled dough ready to be baked or further processed at times specified in the initial bagel production plan 326.”
Similarly, independent claims 1, 9 and 18 recite generating, using a processor, one or more updated bagel production plans during the target date based on receiving real-time bagel inventory data; providing an updated bagel production plan for preparing and cooking bagels in one or more ovens at the designated times on the target date according to the updated bagel production plan; generating, by a baking automation system (BAS) using a processor, based on the bagel inventory predictions; providing the real-time production plan to a client device for preparing and cooking bagels according to the real-time production plan in one or more ovens; generating, using a processor and based on the updated bagel inventory predictions; and providing the bagel production plan for preparing and cooking bagels of the bagel type according to the bagel production plan.
Following, and contrary to Applicant’s assertion, other than reciting an inventory prediction machine learning model, a processor, a dynamic production system, a baking automation system, and a client device, the claim limitations merely cover managing personal behavior, including following rules or instructions, thus falling within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Regarding Step 2A Prong Two, as an initial point, independent method claims 1, 9 and 18 fail to recite that each step is implemented by a computing component (e.g., processor). Instead, Applicant has amended the claims to include a processor merely implementing one step of each of the method claims. As a result, it unclear whether all the critical steps of the method claims are implemented by the processor.
Moreover, under Step 2A Prong Two, the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception. This evaluation is performed by (a) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (b) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. 2019 PEG Section III(A)(2), 84 Fed. Reg. at 54-55. Besides the abstract idea, the claims include an inventory prediction machine learning model, a processor, a dynamic production system, a baking automation system, and a client device.
The an inventory prediction machine learning model, a processor, a dynamic production system, a baking automation system, and a client device in the steps is recited at a high-level of generality, such that it amounts no more than mere instructions to apply the exception using a generic computer component. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis. See MPEP 2106.05(I) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224-26 (2014).
Even when viewed in combination, the additional elements in the claims do no more than use computer components as a tool (i.e., an inventory prediction machine learning model, a processor, a dynamic production system, a baking automation system, and a client device). There is no change to the computers and/or other technology recited in the claims, thus the claims do not improve computer functionality or other technology. See, e.g., Trading Technologies Int’l v. IBG, Inc., 921 F.3d 1084, 1093 (Fed. Cir. 2019) (using a computer to provide a trader with more information to facilitate market trades improved the business process of market trading, but not the computer) and the cases discussed in MPEP 2106.05(a)(I), particularly FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095 (Fed. Cir. 2016) (accelerating a process of analyzing audit log data is not an improvement when the increased speed comes solely from the capabilities of a general-purpose computer) and Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055 (Fed. Cir. 2017) (using a generic computer to automate a process of applying to finance a purchase is not an improvement to the computer’s functionality). Accordingly, the claim as a whole does not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception.
Moreover, while claims 1, 10 and 18 recite “fine-tuning the inventory prediction machine learning model” and “using an inventory prediction machine learning model fine-tuned”, respectively, there are no limitations indicating that the machine learning model is initially trained, thus it unclear whether the fine-tuning is the initial training or an improvement thereof. As a result, since the claim language fails to describe an initial training of the machine learning model, the fine-tuning does not amount to significantly more than the abstract idea.
Additionally, as discussed above, the baking automation system (BAS) described in independent claim 9 does no more than use computer components as a tool. There is no change to the computers and/or other technology recited in the claims, thus the claims do not improve computer functionality or other technology. See, e.g., Trading Technologies Int’l v. IBG, Inc., 921 F.3d 1084, 1093 (Fed. Cir. 2019) (using a computer to provide a trader with more information to facilitate market trades improved the business process of market trading, but not the computer) and the cases discussed in MPEP 2106.05(a)(I), particularly FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095 (Fed. Cir. 2016) (accelerating a process of analyzing audit log data is not an improvement when the increased speed comes solely from the capabilities of a general-purpose computer) and Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055 (Fed. Cir. 2017) (using a generic computer to automate a process of applying to finance a purchase is not an improvement to the computer’s functionality). Accordingly, the claim as a whole does not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception.
Furthermore, and as alluded to by Applicant, a rejection under 35 U.S.C. § 102 and/or 35 U.S.C. §103, or lack thereof, has no bearing on a 35 USC § 101 analysis to determine subject matter eligibility. As discussed in MPEP §2106.05 I, “In addition, the search for an inventive concept is different from an obviousness analysis under 35 U.S.C. 103. See, e.g., BASCOM Global Internet v. AT&T Mobility LLC, 827 F.3d 1341, 1350, 119 USPQ2d 1236, 1242 (Fed. Cir. 2016) ("The inventive concept inquiry requires more than recognizing that each claim element, by itself, was known in the art….[A]n inventive concept can be found in the non-conventional and non-generic arrangement of known, conventional pieces."). Specifically, lack of novelty under 35 U.S.C. 102 or obviousness under 35 U.S.C. 103 of a claimed invention does not necessarily indicate that additional elements are well-understood, routine, conventional elements. Because they are separate and distinct requirements from eligibility, patentability of the claimed invention under 35 U.S.C. 102 and 103 with respect to the prior art is neither required for, nor a guarantee of, patent eligibility under 35 U.S.C. 101. The distinction between eligibility (under 35 U.S.C. 101) and patentability over the art (under 35 U.S.C. 102 and/or 103 ) is further discussed in MPEP § 2106.05(d).”
Following, under step 2B of the analysis, the claims include, inter alia, an inventory prediction machine learning model, a processor, a dynamic production system, a baking automation system, and a client device. As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount 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 on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
There isn’t any improvement to another technology or technical field, or the functioning of the computer itself. Moreover, individually, there are not any meaningful limitations beyond generally linking the abstract idea to a particular technological environment, i.e., implementation via a computer system. Further, taken as a combination, the limitations add nothing more than what is present when the limitations are considered individually. There is no indication that the combination provides any effect regarding the functioning of the computer or any improvement to another technology.
In addition, as discussed in paragraph 0180 of the specification, “In various implementations, the computer system 1200 represents one or more of the client devices, server devices, or other computing devices described above. For example, the computer system 1200 may refer to various types of network devices capable of accessing data on a network, a cloud computing system, or another system. For instance, a client device may refer to a mobile device such as a mobile telephone, a smartphone, a personal digital assistant (PDA), a tablet, a laptop, or a wearable computing device (e.g., a headset or smartwatch). A client device may also refer to a non-mobile device such as a desktop computer, a server node (e.g., from another cloud computing system), or another non-portable device.” As such, this disclosure supports the finding that no more than a general purpose computer, performing generic computer functions, is required by the claims.
Lastly, and contrary to Applicant’s assertion, dependent claims 3, 12, 16, and 20 fail to recite additional limitations that are sufficient to amount to significantly more than the abstract idea. Rather, dependent claims 3, 12, 16, and 20 further describe the updated bagel production plan; recite additional providing and updating steps; further describe the real-time production plan; and further describe the bagel preparation plan, respectively. As such, these dependent claims merely recite additional details that further restrict and/or define the abstract idea, where a more detailed abstract idea remains an abstract idea.
Conclusion
THIS ACTION IS MADE FINAL. 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 ANDRE D BOYCE whose telephone number is (571)272-6726. The examiner can normally be reached M-F 10a-6:30p.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rutao (Rob) Wu can be reached at (571) 272-6045. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ANDRE D BOYCE/Primary Examiner, Art Unit 3623 August 6, 2026
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