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 .
Status of Claims
This action is in reply to the communications filed on September 18, 2025. The Applicants’ Amendment and Request for Reconsideration has been received and entered.
Claims 1, 3-12, 14-17, and 19-20 are currently pending and have been examined. Claims 1, 3-4, 7, 9, 12, 14-15, 17, and 10-20 have been amended.
Response to Arguments
Applicants’ amendments necessitated any new grounds of rejection.
Applicants’ arguments regarding the rejection under 35 USC 101 have been fully considered but they are not persuasive. Applicants argue at page 14 of Applicants’ Reply dated September 18, 2025 (hereinafter “Applicants’ Reply”) that scanning a machine readable code is not a method of organizing a human activity because it is not a sales activity and that instead “the machine-readable code is scanned to interpret the patterns of data embedded in the machine-readable code, which identifies the order. Thus, the claims do not merely cover a method of organizing human activity and instead describe technical features that require the use of a computing device to decode information from the technical features.” The Examiner respectfully disagrees.
Per MPEP 2106.04(d), in order to determine if a claim integrates the judicial exception into a practical application, the considerations set forth in MPEP 2106.05 (a)-(c) and (e)-(h) are evaluated. MPEP 2106.04(d) clearly states that “a specific way of achieving a result is not a stand-alone consideration... However, the specificity of the claim limitations is relevant to the evaluation of several considerations including the use of a particular machine, particular transformation and whether the limitations are mere instructions to apply an exception.” The Examiner notes that the considerations include improvements to computer functionality, improvements to any other technology or technical field, and a particular machine or transformation.
Further, per MPEP 2106.05(a), in order to constitute a technical improvement, the specification "must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but 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), the examiner should not determine the claim improves technology." Further, per MPEP 2106.05(a), "if the specification sets forth an improvement in technology, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement."
Per MPEP 2106.05(a), improvements to computer functionality include a modification of conventional Internet hyperlink protocol to dynamically produce a dual-source hybrid webpage; inventive distribution of functionality within a network to filter Internet content; a method of rendering a halftone digital image; a distributed network architecture operating in an unconventional fashion to reduce network congestion while generating networking accounting data records; a memory system having programmable operational characteristics that are configurable based on the type of processor, which can be used with different types of processors without a tradeoff in processor performance; technical details as to how to transmit images over a cellular network or append classification information to digital image data; a particular structure of a server that stores organized digital images; a particular way of programming or designing software to create menus; a method that generates a security profile that identifies both hostile and potentially hostile operations, and can protect the user against both previously unknown viruses and "obfuscated code," which is an improvement over traditional virus scanning; an improved user interface for electronic devices that displays an application summary of unlaunched applications, where the particular data in the summary is selectable by a user to launch the respective application; a specific interface and implementation for navigating complex three-dimensional spreadsheets using techniques unique to computers; and a specific method of restricting software operation within a license.
Per MPEP 2106.05(a), some examples that the courts have said “may not be sufficient to show an improvement in computer-functionality” include generating restaurant menus with functionally claimed features; accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer; mere automation of manual processes, such as using a generic computer to process an application for financing a purchase; recording, transmitting, and archiving digital images by use of conventional or generic technology in a nascent but well-known environment, without any assertion that the invention reflects an inventive solution to any problem presented by combining a camera and a cellular telephone; affixing a barcode to a mail object in order to more reliably identify the sender and speed up mail processing, without any limitations specifying the technical details of the barcode or how it is generated or processed; instructions to display two sets of information on a computer display in a non-interfering manner, without any limitations specifying how to achieve the desired result; providing historical usage information to users while they are inputting data, in order to improve the quality and organization of information added to a database, because "an improvement to the information stored by a database is not equivalent to an improvement in the database’s functionality”; and arranging transactional information on a graphical user interface in a manner that assists traders in processing information more quickly.
With this guidance in mind, the Examiner respectfully asserts that scanning the machine-readable code is, at most, mere automation of a manual process. Per claim 1, the receipt of the scan of the machine-readable code is only “indicative of the shopper being positioned for check out.” In response to this indication that the shopper is ready, the order is input to the risk model. It is the determining that the shopper is ready for checkout by merely receiving the scan rather than, for example, something particular in the embedded patterns of data, that triggers the activation of another process on the computer, i.e., causing the order to be input to the risk model. Thus, the scanning of the code is not a technical improvement or a practical application of the abstract idea.
Applicants further argue at page 14 of Applicants’ Reply that claim 1 “describes using a risk model that is a ‘machine learning model trained to map input features vectors to an output metric derived from observed data of historical orders’.” Applicants further argue at page 15 that the “system applying the risk model may bypass generating user interfaces for auditors to verify items in an order, thus saving computer resources and improving system throughput.” The Examiner respectfully disagrees.
First, as the Examiner noted in at least the previous Office Action, at paragraph [0061] of Applicants’ published application, Applicants disclose “The risk model 404 may model the risk (e.g., fraud or mistake) and/or benefits (e.g., checkout efficiency) associated with conducting different scopes of audit in order to determine the audit decision. In one or more embodiments, the risk model 404 may comprise a rule-based model comprising a set of rules for making an audit decision based on the various factors described herein. The rules may be customizable to different warehouses 210. The risk model 404 may include separate sets of rules for determining whether to conduct an audit and for determining the scope of the audit.” At paragraph [0062] of Applicants’ published application, Applicants disclose “In another embodiment, the risk model 404 comprises a machine learning model trained on historical data to infer an optimal audit decision.” While Applicants do not list any particular types of machine learning models to be used for the risk model, at paragraph [0050] of Applicants’ published application, Applicants list various machine learning models to be used for the item availability model, such as a neural network, boosted tree, gradient boosted tree, or random forest model. In all of the cases (rule-based and machine learning), Applicants do not describe the particulars of the named models, indicating that the models are sufficiently well-known. Thus, the Examiner interprets the risk model as a well-understood, routine, or conventional element that cannot impart eligibility.
Further, regarding Applicants’ assertions regarding “saving computer resources and improving system throughput,” per MPEP 2106.05(a), in order to constitute a technical improvement, the specification "must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but 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), the examiner should not determine the claim improves technology."
With this in mind, the Examiner respectfully asserts that the above alleged improvements constitute a bare assertion of an improvement without the detail necessary for the alleged improvement to be apparent to a person of ordinary skill in the art. For example, Applicants reference “saving computer resources and improving system throughput” without any discussion of what resources are saved, what constitutes throughput, and how the limitations described in the claims contribute to these alleged improvements. Absent any such discussion or evidence, there is no difference in the operation of the computer thus no technological improvement.
Thus, the rejection is maintained.
Applicants’ remaining arguments have been fully considered but they have either been addressed above or they are directed to the instantly amended claims and thus are moot in view of the new grounds of rejection.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1, 3-12, 14-17, and 19-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1, 3-12, 14-17, and 19-20: Claim 1 recites “scanning, via the shopper mobile application, a machine-readable code embedded with patterns of data identifying the one or more items of the order.” This limitation is unclear. It is unclear what “scanning, via the shopper mobile application” means. Does this mean that the shopper mobile application performs the scan? Or does this mean that the computer system performs the scan of a code presented by the shopper mobile application on an interface of the second mobile device? For purposes of examination, the Examiner is interpreting this limitation as reciting that the computer system performs the scan of a code presented by the shopper mobile application on an interface of the second mobile device.
Further, claim 1 recites “in response to receiving a first indication via the user interface controls, the second mobile device to present a user interface for obtaining a reason for the discrepancy according to the auditor.” The second mobile device corresponds to the shopper mobile application. Is the user interface for obtaining a reason for the discrepancy according to the auditor presented on the shopper mobile application/second mobile device? Or is it presented on the third mobile device, which corresponds to the auditor mobile application? For purposes of examination, the Examiner is interpreting the user interface as being presented on the third mobile device.
Further, claim 1 recites “receiving, via the auditor mobile application from the auditor mobile application, verification of presence of each of the one or more items from the order.” It is unclear what is meant by “receiving, via the auditor mobile application from the auditor mobile application.” Is it the computer system that is doing the receiving? If so, is the verification received via the auditor mobile application or from the auditor mobile application and what is the difference between these two scenarios? For purposes of examination, the Examiner is interpreting this portion of claim 1 as reciting “receiving, from the auditor mobile application, verification of presence of each of the one or more items from the order.”
Further, claim 1 recites “generating routing instructions via the shopper mobile application based on a first location of the second mobile device and a second location received of the first mobile device.” It is unclear how the first and second locations are received/known. For purposes of examination, the Examiner is interpreting the first location is received as part of the scan of the machine readable code, i.e., the location is actually that of the machine-readable code. For purposes of examination, the Examiner is interpreting the second location is received as part of the customer order.
Claims 12 and 17 are rejected for similar reasons.
Claims 3-11, 14-16, and 19-20 inherit the deficiencies of claims 1, 12, and 17.
Claims 4, 15, and 20: Claim 4 recites “wherein the risk model is further applied to at least one of.” There is insufficient antecedent basis for “applying the trained risk model.” Per claim 1, “applying a trained risk model” has been replaced by “in response to detecting the shopper is ready to exit the warehouse based on the receipt scan of the machine-readable code, inputting, to a risk model. For purposes of examination, the Examiner is interpreting this portion of claim 4 as reciting “wherein inputting the order to the risk model is based on”.
Claims 15 and 20 are rejected for similar reasons.
Claim 11: Claim 11 recites “presenting a ranked list of the subset of the one or more items in the order.” It is unclear what is meant by “ranked.” How is the subset ranked, i.e., what metric is used to rank the items? Are they ranked by user preference? Cost? Something else? For purposes of examination, the Examiner is assigning little patentable weight to “ranked” and is interpreting this portion of claim 11 as reciting “presenting a list of the one or more items in the order.”
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, 3-12, 14-17, and 19-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Independent claims 1, 12, and 17 recite a method, a computer program product, and a system for auditing shopping items. With respect to claim 1, claim elements scanning a machine-readable code, detecting that the shopper is ready to exit the warehouse, inputting the order to a risk model, determining to initiate the audit, identifying the order based on an identifier of the order, completing the order, and generating routing instructions, as drafted, illustrate a series of steps that, under their broadest reasonable interpretation, cover a method of organizing a human activity, such as a commercial or legal interaction, i.e., sales activities.
Claims 12 and 17 recite similar limitations.
The judicial exception is not integrated into a practical application. In particular, claims 1, 12, and 17 recite various receiving, sending (transmitting) and presenting (displaying) steps. These elements are considered to recite insignificant extra-solution activity. Further, claim 1 recites one or more processors, claim 12 recites a non-transitory computer-readable storage medium, and claim 17 recites a processor and a non-transitory computer-readable storage medium at a high level of generality, i.e., as generic computer components performing generic computer functions. Accordingly, these additional elements do not impose any meaningful limits on the abstract idea.
Thus, claims 1, 12, and 17 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, claim 1 recites one or more processors, claim 12 recites a non-transitory computer-readable storage medium, and claim 17 recites a processor and a non-transitory computer-readable storage medium at a high level of generality, i.e., as generic computer components performing generic computer functions. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept.
Further, regarding the receiving, transmitting, and displaying elements, per MPEP 2106.05(d}(ll), elements such as receiving, transmitting, or displaying data over a network, i.e., using the internet to gather data, and storing and retrieving information in memory are considered to be computer functions that are well-understood, routine, and conventional functions. See Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1308, 1334, 115 USPG2d 1681,1701 (Fed. Cir, 2015); OIP Techs Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPG2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 785 F.3d 1350, 1355, 112 USPG2d 1093, 1098 (Fed. Cir. 2014) (computer receives and sends information over a network)).
Additionally, the independent claims recite that the order is input into a “risk model” and that “an audit decision” is output from the risk model. At paragraph [0061] of Applicants’ published application, Applicants disclose “The risk model 404 may model the risk (e.g., fraud or mistake) and/or benefits (e.g., checkout efficiency) associated with conducting different scopes of audit in order to determine the audit decision. In one or more embodiments, the risk model 404 may comprise a rule-based model comprising a set of rules for making an audit decision based on the various factors described herein. The rules may be customizable to different warehouses 210. The risk model 404 may include separate sets of rules for determining whether to conduct an audit and for determining the scope of the audit.” At paragraph [0062] of Applicants’ published application, Applicants disclose “In another embodiment, the risk model 404 comprises a machine learning model trained on historical data to infer an optimal audit decision.” While Applicants do not list any particular types of machine learning models to be used for the risk model, at paragraph [0050] of Applicants’ published application, Applicants list various machine learning models to be used for the item availability model, such as a neural network, boosted tree, gradient boosted tree, or random forest model. In all of the cases (rule-based and machine learning), Applicants do not describe the particulars of the named models, indicating that the models are sufficiently well-known. Thus, the Examiner interprets the risk model as a well-understood, routine, or conventional element that cannot impart eligibility.
Thus, claims 1, 12, and 17 are not patent eligible.
Claims 3-11, 14-16, and 19-20 depend from claims 1, 12, and 17. Claims 3, 14, and 19 are directed to the type of data and are further directed to the abstract idea. Claims 4, 15, and 20 are directed to applying a model and are further directed to the abstract idea. Claims 5 and 16 are directed to scanning the scannable code and are further directed to the abstract idea. Claims 5 and 16 are further directed to presenting the scannable code which, as discussed above, is a computer function that is considered to be well-understood, routine, and conventional. Claim 6 is directed to presenting identification which, as discussed above, is a computer function that is considered to be well-understood, routine, and conventional. Claim 7 is directed to receiving and storing data which, as discussed above, are computer functions that are considered to be well-understood, routine, and conventional. Claims 8-9 are directed to determining the one or more items and are further directed to the abstract idea. Claim 10 is directed to matching product codes and is further directed to the abstract idea. Claim 10 is further directed to receiving codes and presenting controls which, as discussed above, are computer functions that are considered to be well-understood, routine, and conventional. Claim 11 is directed to presenting a ranked list which, as discussed above, is a computer function that is considered to be well-understood, routine, and conventional.
Thus, the claims are not patent eligible.
Potentially Allowable Subject Matter
Claims 1, 3-12, 14-17, and 19-20 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, and 35 USC 101 set forth in this Office Action.
In the event the claims are amended, they will be subject to further examination.
With respect to claim 1, the prior art of record, alone or combined, neither anticipates nor renders obvious, a method comprising, by one or more processors of a computer system: receiving, via a customer mobile application at a first mobile device, an order from a customer for one or more items from a warehouse; sending a dispatch command to a shopper mobile application at a second mobile device, the dispatch command instructing a shopper to travel to the warehouse and acquire the one or more items in the order for the customer; scanning, via the shopper mobile application, a machine-readable code embedded with patterns of data identifying the one or more items of the order, wherein receipt of the scan is indicative of the shopper being positioned for check out at a warehouse; detecting that the shopper is ready to exit the warehouse based on the scan of the machine-readable code received from the shopper mobile application; in response to detecting the shopper is ready to exit the warehouse based on the receipt scan of the machine-readable code, inputting, to a risk model, the order, wherein the risk model is a machine learning model trained to map input feature vectors to an output metric representative of an audit decision derived from observed data of historical orders of items, wherein a subset of the historical orders are associated with order discrepancies and the feature vectors each representing an item of the order identified in the patterns of data of the machine-readable code; receiving, as output from the risk model, the audit decision indicative of whether to initiate an audit of the shopper with respect to the order; determining to initiate the audit based on an output of the risk model; identifying, by an auditor mobile application at a third mobile device, the order based on an identifier of the order presented at a user interface of the second mobile device; presenting, via the auditor mobile application, user interface controls to enable an auditor to indicate a discrepancy in items presented by the shopper and the order; in response to receiving a first indication via the user interface controls, the second mobile device to present a user interface for obtaining a reason for the discrepancy according to the auditor; receiving, via the auditor mobile application from the auditor mobile application , verification of presence of each of the one or more items from the order; and responsive to receiving the verification of the one or more items from the order, completing the order and generating routing instructions via the shopper mobile application based on a first location of the second mobile device and a second location of the first mobile device, wherein the routing instructions indicate how to navigate from the first location to the second location.
With respect to claims 12 and 17, the prior art of record, alone or combined, neither anticipates nor renders obvious, a computer program product and a s computer system reciting similar limitations.
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 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 concerning this communication or earlier communications from the examiner should be directed to ANNE MARIE GEORGALAS whose telephone number is (571)270-1258 E.S.T.. The examiner can normally be reached on Monday-Friday 8:30am-5:00pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Marissa Thein can be reached on 571-272-6764. 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.
/Anne M Georgalas/
Primary Examiner, Art Unit 3689