DETAILED ACTION
This is a final office action on the merits in application number 17/935091. This action is in response to Applicant’s Amendments and Arguments dated 1/29/2026. No claims were amended and Claims 9, 10 were previously cancelled. Claims 1-8 and 11-20 are pending and have been examined on the merits.
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 .
Response to Arguments
Applicant asserts on page 13 of their Remarks dated 1/29/26 that the “Declaration of Reza Faturechi under 37 USC 1.132” is evidence that Applicant’s claims disclose a “technical improvement”.
MPEP 716.01(c) recites the evidentiary requirements of a declaration or affidavit.
MPEP 716.01(c)(I) recites:
“TO BE OF PROBATIVE VALUE, ANY OBJECTIVE EVIDENCE SHOULD BE SUPPORTED BY ACTUAL PROOF Objective evidence which must be factually supported by an appropriate affidavit or declaration to be of probative value includes evidence of unexpected results, commercial success, solution of a long-felt need, inoperability of the prior art, invention before the date of the reference, and allegations that the author(s) of the prior art derived the disclosed subject matter from the inventor or at least one joint inventor”.
MPEP 716.01(c)(II) recites:
“Arguments presented by the applicant cannot take the place of evidence in the record”.
MPEP 716.01(c)(III) recites:
“Although factual evidence is preferable to opinion testimony, such testimony is entitled to consideration and some weight so long as the opinion is not on the ultimate legal conclusion at issue. While an opinion as to a legal conclusion is not entitled to any weight, the underlying basis for the opinion may be persuasive… In assessing the probative value of an expert opinion, the examiner must consider the nature of the matter sought to be established, the strength of any opposing evidence, the interest of the expert in the outcome of the case, and the presence or absence of factual support for the expert’s opinion… Although an affidavit or declaration which states only conclusions may have some probative value, such an affidavit or declaration may have little weight when considered in light of all the evidence of record in the application. An affidavit of an applicant as to the advantages of their claimed invention, while less persuasive than that of a disinterested person, cannot be disregarded for this reason alone.
The document “Declaration of Reza Faturechi under 37 USC 1.132” dated 1/29/2026, recites on page 1 that Reza Faturechi is an employee of the Applicant. MPEP 716.01(c)(III) states that Examiner “must” consider “the interest of the expert in the outcome of the case” and clearly Reze Faturechi has a financial interest because they are an employee of the Applicant. Further, this document is offered as “proof” of the “ultimate legal conclusion at issue” – the eligibility of Applicant’s claims, which is expressly prohibited by MPEP 716.01(c)(III). Further, this document does not provide any evidence of unexpected results, commercial success, solution of a long-felt need, inoperability of the prior art, invention before the date of the reference, and allegations that the author(s) of the prior art derived the disclosed subject matter from the inventor or at least one joint inventor” which are the only types of evidence that a declaration or affidavit may support under MPEP 716.01(c). While “Declaration of Reza Faturechi under 37 USC 1.132” has some probative value and is not disregarded, Examiner finds that, when considered in light of all the evidence of record in the application, this document has little weight and is mere attorney opinion not expert testimony and thus it is not “actual proof”. Finally, the “Declaration of Reza Faturechi under 37 USC 1.132” describe theoretical combinatorics problems and various algorithms but none of these are specifically claimed nor disclosed or implied anywhere in the specification. The “Declaration of Reza Faturechi under 37 USC 1.132” does not supplement or explain elements specifically claimed, disclosed or implied in the specification but appears to attempt to add new matter that was not in the original disclosure.
Applicant asserts on page 13 of the Remarks dated 1/29/2026 that their claims are similar to the PTAB case dated 9/26/25 Ex parte Desjardins and Applicant asserts this case “creates a two part test for reciting an improvement to a technical field”. Examiner notes that the Memorandum from Charles Kim, Deputy Commissioner for Patents dated 12/5/2025 specifically states in paragraph 2 “These updates are not intended to announce any new USPTO practice or procedure and are meant to be consistent with existing USPTO guidance”.
Regarding Test 1:
Applicant asserts on page 13 that the first test is “does the disclosure "provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement"”? Applicant asserts on page 14, top, “Regarding the first step of this test, the specification explains that "[b]y evaluating each candidate order batch on a per-picker basis, the online concierge system simplifies the problem of determining which candidate order batch to offer to each picker" and that this "reduc[es] the computational load from traditional methods. Specification [0004]”.
MPEP 2106.05(a) establishes the requirements for “Improvements to the functioning of a computer or to any other technology or technical field” and states: “If it is asserted that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes, a technical explanation as to how to implement the invention should be present in the specification. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement… 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… the claim must be evaluated to ensure the claim itself reflects the disclosed improvement in technology… the claim must include the components or steps of the invention that provide the improvement described in the specification… An important consideration in determining whether a claim improves technology is the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome”.
MPEP 2106.05(a) also states that the following are *not* sufficient to show an improvement in computer functionality: “Accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer” (citing FairWarning) and “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” (citing BSG Tech).
Examiner holds that [0004] is conclusory and Applicant does not provide sufficient technical details such that one of ordinary skill in the art would recognize the claimed invention as providing a technical improvement relating to how “the problem of determining which candidate order batch to offer to each picker” is simplified or how “the computation load” is reduced. Paragraph [0004] recites “By evaluating each candidate order batch on a per-picker basis, the online concierge system simplifies the problem of determining which candidate order batch to offer to each picker. Additionally, since the online concierge system can rescind offered order batches if another picker accepts an order batch with overlapping orders, the online concierge system can easily adjust which order batch to offer to which picker based on whether the pickers accept their offered order batches, rather than having to spend computational resources determining beforehand which pickers are most likely to accept which offered order batches. Thus, the solution provided herein for offering order batches to pickers allows an online concierge system to have an effective assignment of orders to pickers while reducing the computational load from traditional methods”. Applicant does not provide technical detail of how to evaluate each candidate order batch on a per-picker basis. Applicant recites some factors in [0061] of an “order batch score” such as “likelihood that the candidate picker will accept and service the order batch, a predicted amount of time that the candidate picker will take to complete the order batch, an amount of consideration to be paid to the candidate picker, or a distance that the candidate picker would need to travel to service the order batch” and states “the online concierge system generates 340 a set of order batch scores for each candidate picker” but does not teach nor imply only performing this calculation for a subset of orders or pickers. Applicant does not provide technical detail of “the problem of determining which candidate order batch to offer to each picker” or disclose any specific way to “simplify” this calculation. Applicant recites in [0057] “In some embodiments, the online concierge system generates a candidate order batch for every possible subset of the received orders. Alternatively, to reduce the computational load on the online concierge system, the online concierge system may apply heuristic rules that limit which candidate order batches the online concierge system generates. Heuristic rules are constraints on which orders can be included in a candidate order batch together. These heuristic rules may reduce the space of route permutations the online concierge system considers to those that are most likely to be effective. For example, permutation rules may specify a minimum or maximum number of orders in each candidate order batch, a minimum or maximum total number of items across the orders in a candidate order batch, a minimum or maximum number of types of items across the orders in a candidate order batch, or a maximum distance that a picker would be required to travel to service the order batch”. Applicant does not disclose any technical detail of the “heuristic rules” or why a particular candidate order batch is “most likely to be effective” nor define what “effective” means in context. Applicant does not disclose how particular subsets are not selected. Applicant does not disclose how order batches are grouped nor how particular candidate order batches are selected to offer to each picker and how some candidate order batches are not offered. Applicant does not disclose any technical detail with respect to how a specific piece of hardware or specific software construct determines that an order has been duplicatively placed on the available-order list of two pickers. Applicant recites in [0064] that a (human) picker receives a list of candidate batches on their “picker device”, which is defined in [0017] to include a cell phone, and then accepts a particular batch to pick. Applicant does not disclose any technical detail about how the system detects that overlapping candidate batches have been given to other pickers and how to rescind an order from another picker or pickers that has been accepted by a particular picker. Applicant does not disclose with any technical detail how a specific piece of hardware or specific software construct generates an “update” to the display of the second picker that has the effect of removing the duplicate order. Applicant does not disclose computational processing and storage requirements or how much capacity of each is required for the various calculations. Applicant does not teach any tools to measure a total number of calculations or a “reduction” in computational processing and storage or even disclose any metrics of a “reduction”. Applicant does not disclose extra processing and storage capacity required to constantly offer and withdraw candidate batches versus just assigning them based on the “most likely to be effective” criteria.
Applicant merely conclusively states that there is an undefined order assignment process and asserts that there is a efficiency improvement with no technical detail of this. It appears that Applicant’s ”technical improvement” is merely the intuition that if a computer processes less data it will use fewer computational resources. Further, Examiner notes that Applicant’s “problem” only exists because Applicant created it by duplicatively offering the same order to two pickers which is not a problem rooted in technology.
Examiner holds that Applicant does not provide sufficient technical details such that one of ordinary skill in the art would recognize the claimed invention as providing a technical improvement relating to how “the problem of determining which candidate order batch to offer to each picker” is simplified or how “the computation load” is reduced.
Regarding Test 2:
Applicant asserts on page 13 that the second test is “Second, does the claim itself "reflect[] the disclosed improvement in technology"?”. Applicant asserts on page 15 that the “Declaration of Reza Faturechi under 37 USC 1.132” “confirms that these steps are ones that allow the online system to "substantially reduce the computational resources required to provide functionality relating to the assignment problem." Declaration at 11. Therefore, the claims "reflect the disclosed improvement in technology"”.
Applicant asserts on page 14 of their Remarks dated 1/29/26 that that the following claim language “improves the functionality of computing systems”:
a. "offering, by the online system, a candidate order batch of the set of candidate order batches to each picker of the set of candidate pickers";
b. "receiving, by the online system, an acceptance from a first picker device associated with a first picker of the set of candidate pickers, wherein the acceptance is received through a picker user interface on the first picker device displaying the candidate order batch offered to the first picker and indicates that the first picker will service the candidate order batch offered to the first picker";
c. "identifying, by the online system, an order batch offered to a second picker of the set of candidate pickers, wherein the identified order batch comprises an order that is in the subset of orders corresponding to the order batch offered to the first picker;" and
d. "transmitting, by the online system, instructions to a second picker device associated with the second picker to rescind the identified order batch by updating the user interface of the second picker device to no longer display the identified order batch to the second picker”.
As discussed in the 35 USC 101 rejection, infra, Applicant’s Claims are directed to the abstract idea in the category of Certain Methods of Organizing Human Activity in the subcategory of Commercial or Legal interactions because they recite the common commercial practice of optimizing the picking of incoming orders and selecting which human pickers pick a particular incoming order or group of orders. Applicant does not recite any additional elements other than general purpose computers or cell phones, broadly-claimed software constructs/functionality, and, in dependent Claims 4 and 14, general purpose machine learning functionality, with no detailed technical disclosure of any special features or benefits relating to Applicant’s inventive concept. Applicant does not claim any additional elements that are sufficient to amount to significantly more than the judicial exception.
Applicant does not claim a reduction of computational load or complexity or claim picking efficiencies. Applicant’s claims recited above recite letting two pickers select from a subset of picklists then withdrawing a picklist that was offered to one picker if another picker selects it. It is assumed but not claimed that only one picker can pick a particular picklist at a time. Applicant does not claim a baseline of a picking efficiency or computational complexity or computational load nor claim a specific improvement to picking efficiency, computational complexity or computational load. Additionally, Applicant does not claim any metrics to measure an improvement to picking efficiency or computational complexity or computational load, nor teach hardware or software capable of measuring any of this data. Applicant’s claimed elements may or may not have the incidental effect of reducing complexity of an optimization problem simply because they remove data but this merely *improves the data* and does not improve the processing of the data or improve computer technology or any other technology. Applicant thus does not claim a technical improvement under MPEP 2106.05(a). Applicant appears to be claiming a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art” under MPEP 2106.05(a) and this does not provide an improvement to technology.
Applicant’s arguments have been carefully considered but are not persuasive, the rejection 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.
Examiner is using the “step” annotation from the flowchart of MPEP 2106 (III), and MPEP 2106.04 and MPEP 2106.05 for clarity.
Claims 1-8 and 11-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
Independent Claim 1 and dependent Claims 2-8 recite a method (process). Independent Claim 11 and dependent claims 12-19 recite a medium (manufacture). Independent Claim 20 recites a system (machine). Thereby Claims 1-8 and 11-20 fall into one of the four statutory categories of invention.
Step 2A, prong 1:
Applicant recites the following elements in Claim 1 (and similarly Claims 11 and 20):
A method comprising, at a computer system comprising a processor and a computer-readable medium, causing the processor to perform the steps: receiving by an online system, a set of orders from a plurality of client devices associated with a plurality of users of an online system, each order of the set of orders comprising a set of items to be collected from a retailer of a plurality of retailers, wherein each retailer in the plurality of retailers is associated with a plurality of retailer locations; generating by the online system, a set of candidate order batches based on the set of orders and the retailer locations associated with the plurality of retailers, wherein each candidate order batch comprises a different subset of the set of orders and comprises a first order to be serviced at a first retailer location of a first retailer and a second order to be serviced at a second retailer location of a second retailer; selecting by the online system, a set of candidate pickers to service the set of orders; offering by the online system, a candidate order batch of the set of candidate order batches to each picker of the set of candidate pickers, wherein offering a candidate order batch to a candidate picker comprises: generating by the online system, a set of order batch scores for the candidate picker, wherein the set of order batch scores comprises an order batch score for each candidate order batch in the set of candidate order batches, and wherein an order batch score for a candidate order batch is generated based on order data for the orders in the candidate order batch and picker data associated with the candidate picker; selecting by the online system, a candidate order batch from the set of candidate order batches based on the set of order batch scores; and transmitting by the online system, the selected candidate order batch to a picker device associated with the candidate picker to be displayed to the candidate picker through a picker user interface; receiving by the online system, an acceptance from a first picker device associated with a first picker of the set of candidate pickers, wherein the acceptance is received through a picker user interface on the first picker device displaying the candidate order batch offered to the first picker and indicates that the first picker will service the candidate order batch offered to the first picker; identifying by the online system, an order batch offered to a second picker of the set of candidate pickers, wherein the identified order batch comprises an order that is in the subset of orders corresponding to the order batch offered to the first picker; and transmitting by the online system, instructions to a second picker device associated with the second picker to rescind the identified order batch by updating the user interface of the second picker device to no longer display the identified order batch to the second picker.
Examiner has bolded the elements that are part of the abstract idea.
These elements recite optimizing the picking of incoming orders and selecting which human pickers pick a particular incoming order or group of orders. These elements represent an abstract idea in the category of Certain Methods of Organizing Human Activity in the subcategory of Commercial or Legal interactions because it is a common commercial practice to optimizing the picking of incoming orders and selecting which human pickers pick a particular incoming order or group of orders. Claim 1 (and similarly Claims 11 and 20) thus recites an abstract idea. Dependent Claims 2-8 and 12-19 contain the same abstract idea by virtue of their dependency on Claim 1 or Claim 11, respectively. Accordingly Claims 1-8 and 11-20 recite an abstract idea.
Step 2A, prong 2:
In addition to the abstract idea discussed above, Claim 1 (and similarly Claims 11 and 20) also recites the following additional elements:
computer system comprising a processor – Applicant describes this in [0069] as a general purpose computing system and does not provide any detailed technical disclosure of any special features or technologies.
online system – Applicant describes an “online concierge system” in [0028] as comprising the software constructs “data collection module 200, a content presentation module 210, an order management module 220, a machine learning training module 230, and a data store 240”. Applicant does not claim the modules and only broadly describes these software modules in their spec by name and their presumed functionality and does not provide any technical detail of their function, nor how they work nor their input or output data nor provide their source code thus an online system is a general purpose software construct.
medium - Applicant describes this in [0069] with no detailed technical disclosure of any special features or benefits relating to Applicant’s inventive concept.
picker device – Applicant describes this in [0017] as a general-purpose cell phone or other general-purpose personal computer.
Additionally Claims 4 and 14 also recite a machine learning model. Applicant describes this in [0048] as one of a wide range of possible technologies with no detailed technical disclosure of any special features or benefits relating to Applicant’s inventive concept.
MPEP 2106.05(f)(2) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application”. As discussed, the additional elements computer system/processor, online system, medium, picker device and machine learning model are broadly claimed and used in their ordinary capacity with no detailed technical disclosure of any special features or technologies and, thus, they do not integrate the abstract idea into a practical application.
The claims as a whole do not integrate the abstract idea into a practical application because they do not impose any meaningful limitations on practicing the abstract idea. Claims 1-8 and 11-20 are therefore directed to an abstract idea.
Step 2B: As discussed above, Applicant claims the abstract idea of selecting human pickers, grouping incoming orders and optimizing picking orders. As discussed above, Applicant also recites the additional elements of: computer system/processor, online system, medium, picker device and machine learning model. As discussed above with respect to Step 2A, the claimed computer system/processor, online system, medium, picker device and machine learning model are hardware or software constructs recited at a high level of generality and amount to no more than instructions to apply the exception using general purpose computer systems. MPEP 2106.05(f) states that merely adding a general purpose computer or computer components to an abstract idea does not amount to significantly more, thus computer system/processor, online system, medium, picker device and machine learning model are not significantly more. The additional elements alone or in combination do not improve the functioning of a computer or any other technology or technological field. The additional elements alone or in combination do not apply the judicial exception to a particular (non-general purpose) machine. The additional elements alone or in combination do not effect a transformation or reduction of a particular article to a different state or thing. Applicant does not claim or teach in their specification any special purpose hardware or improvements thereof. Therefore, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Dependent Claims 2 and 12 further limit the selection of orders and contain the same abstract idea by virtue of their dependency on Claims 1 or 11, respectively.
Dependent Claims 3-5 and 13-15 further limit the selection of picker/order combination and contain the same abstract idea by virtue of their dependency on Claims 1 or 11, respectively.
Dependent Claims 6 and 16 further limit the selection of picker and contain the same abstract idea by virtue of their dependency on Claims 1 or 11, respectively.
Dependent Claims 7 and 17 further limit the offer/receipt of the order to the first picker and contain the same abstract idea by virtue of their dependency on Claims 1 or 11, respectively.
Dependent Claim 19 further limits the display of the order and contain the same abstract idea by virtue of their dependency on Claims 1 or 11, respectively.
Claims 1-8 and 11-20 are not patent eligible.
Prior Art
After a diligent search Examiner is not able to find prior art that teaches all of the elements of Applicant’s claims or be combined without improper hindsight reasoning. The closest prior art is:
U.S. Patent Publication 2016/0364688 (Vakneen) teaches a package delivery system that sends notice to a user dashboard of a potential package delivery to a subset of all drivers that includes just the drivers that are nearby the pickup point and capable of performing the delivery, wherein a driver in the subset accepts or declines the delivery jobs and the first driver to accept the job gets the job and the remaining drivers see in their user dashboard that they are unable to accept the job (see at least [0014]). Further, drivers are on the list have characteristics that allow them to be “favorite” drivers and the system shows the delivery jobs to the “favorite” drivers first before other drivers in the subset of other nearby drivers (see at least [0006]).
U.S. Patent Publication 2020/0410864 (Ripert) (belonging to Applicant but published 12/31/2020 so prior art) teaches an online concierge system that allocates orders among agents based on location of the agent in real time and “locks” a certain order to a first agent when the first agent arrives at the store and re-allocates the remaining orders among the remaining agents. (see at least [0006]). Further the system removes the delivery orders that were locked to the first agent from the plurality of (available) delivery orders that the remaining agents can see (see at least [0007]. This reference also teaches grouping or batching orders in at least [0043] but does this to optimize driving not picking. This reference teaches optimizing pickups at a plurality of pickup locations (see at least [0009] and [0028]).
U.S. Patent Publication 2022/0092521 (Hunter) teaches a delivery management system that calculates a driver score (see at least [0140], [0277] and [0300]), an order score (see at least [0126]) and use rules and/or machine learning to optimize the best combination (see at least [0140]).
U.S. Patent Publication 2021/0269244 (Ahmann) teaches batch picking and teaches that the same item can be stored in different aisles. Examiner holds that different aisles that store the same items are functionally similar to different stores of the same retailer because both increase picking flexibility and optimize overall picking in the same way.
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 KIMBERLY S BURSUM whose telephone number is (571)272-8213. The examiner can normally be reached M-F 9:30 AM - 6:30 PM.
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/KIMBERLY S. BURSUM/Examiner, Art Unit 3627
/FLORIAN M ZEENDER/Supervisory Patent Examiner, Art Unit 3627