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 .
Continued Examination Under 37 CFR 1.114
1. A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 10/22/2025 has been entered.
Claims 1 and 18 are currently amended. Claims 2-17 depend from claim 1, and claims 19-20 depend from claim 18.
Claim Rejections - 35 USC § 101
2. 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.
2.1. Claims 1--20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more, when analyzed as per MPEP 2106.
Step 1 analysis:
Claims 1-20, as recited are to a system /apparatus are statutory, (Step 1: No).
Step 2A Analysis:
Claim 1 recites:
1. (Currently amended) An on-demand delivery system to implement device-based coordination of multi-party delivery processes, comprising:
a server with a cloud services and a storage system with one or more processors and a non-transitory computer-readable storage medium to execute tasks, the server comprising:
(a) a location-based dispatch system (LBDS) to identify one or more resources of at least one order fulfillment facility, an inventory retrieval puller device, or a transportation driver device within a threshold distance of a requester device:
(b) a neural network trained by the LBDS to receive order data associated with one or more items from the requester device and
( c) to generate a resource selection schedule that automatically assigns and transmits control instructions to the identified inventory retrieval puller device or the identified transportation driver device to coordinate order retrieval and delivery without human scheduling input
(d) one or more databases to store product characteristic data of the one or more items:
( e) a fleet management system to determine vehicle-capacity based vehicle selections from fleet information, and wherein the product characteristic data is tracked by the on- demand delivery system, and a vehicle capability requirement, based on weight of the one or more items, is generated by the fleet management system for each order: and
a payment system:
(f) the requester device in electrical communication with the server to receive a payer-invite request from a user interface on a first application on a the requester device, the payer-invite request to generate an invitation to a payer to pay for a delivery order via a second application on a payer device, the delivery order to identify the one or more items to be purchased and delivered to a requester location associated with the requester device or inputted by the requester,
(g) wherein the payer is selected via a feature provided on the user interface on the first application on the requester device;
(h) the invitation to be transmitted to the payer device associated with the payer;
(i) a payment to be received by the payment system from the payer device, the payment provided in response to the invitation; and
(j) a driving instruction to be sent to a driver device or a vehicle device, the driving instruction instructing pick up of the one or more items and delivery of the one or more items to the requester location.
Step 2A Prong 1 analysis: This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim.
Claims 1-20recite abstract idea.
The highlighted limitations comprising “identify one or more resources of at least one order fulfillment facility, an inventory retrieval puller, or a transportation driver within a threshold distance of a requester: receive order data associated with one or more items from the requester, and generate a resource selection schedule and instructions to the identified inventory retrieval puller or the identified transportation driver to coordinate order retrieval and delivery; determine vehicle-capacity based vehicle selections from fleet information, and wherein the product characteristic data is tracked, and a vehicle capability requirement, based on weight of the one or more items, is generated for each order: the requester to receive a payer-invite request from a user, the payer-invite request to generate an invitation to a payer to pay for a delivery order, the delivery order to identify the one or more items to be purchased and delivered to a requester location associated with the requester, wherein the payer is selected; the invitation transmitted to the payer; a payment received from the payer, the payment provided in response to the invitation; and a driving instruction sent to a driver, the driving instruction instructing pick up of the one or more items and delivery of the one or more items to the requester location”, under their broadest reasonable interpretation, cover performance of a commercial transaction for receiving an order from a requestor, determining the resources within a predetermined proximity of the requestor and a suitable vehicle that can be used to deliver the ordered goods, providing instructions to a picker/driver for coordinating retrieval of goods and delivering them, followed by facilitating payment from a third party by sending an invitation to the payer for making payment and in response to receiving the payment providing instructions to the driver of the vehicle for delivering the ordered goods to the location of the requestor. These limitations of claim 1 and its dependent claims 2-17 fall within the group of Certain Methods of Organizing Human Activity” of abstract ideas. See MPEP 2106.04(a)(2), subsection II. Thus, claims 1-17 recite Certain Methods of Organizing Human Activity”,
The highlighted limitations comprising , “ (a) identify one or more resources of at least one order fulfillment facility, an inventory retrieval puller, or a transportation driver within a threshold distance of a requester, (c) generate a resource selection schedule and instructions to the identified inventory retrieval puller or the identified transportation driver to coordinate order retrieval and delivery, ( e) determine vehicle-capacity based vehicle selections from fleet information, and wherein the product characteristic data is tracked, and a vehicle capability requirement, based on weight of the one or more items, is generated for each order”, under their broadest reasonable interpretation, cover performance within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. For example, a human operator can determine resources/suppliers for an order received from a requestor in the nearest vicinity of the requestor, provide instructions on a paper for the picker/driver for coordinating retrieval and delivery of items. Also, based on the properties and weights of the goods ordered a human operator can select a suitable vehicle for delivering the goods. Thus, claim 1 with its dependent claims 2-17 recite “Mental Processes”.
Since the claims 1-17, as analyzed above, recite both “Certain Methods of Organizing Human Activity” and “Mental Processes, the Supreme Court has treated such claims in the same manner as claims reciting a single judicial exception (discussing Bilski v. Kappos, 561 U.S. 593 (2010)). Here, through the limitations of claims 1-17 discussed above recite two categories of abstract ideas, they are considered together as a single abstract idea for further analysis. (Step 2A, Prong One: YES).
Since the other independent claim 18 recites similar limitations as claim 1, it and its dependent claims 19-20 are analyzed on the same basis reciting an abstract idea. Claim 18 also recites predicting operational timing of the inventory retrieval puller device, or the transportation driver device, to generate digital dispatch commands, and to update fulfillment data in response to real-time sensor feedback from those devices, which under their broadest reasonable interpretation, cover performance within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. For, example a human operator can prepare, calculate and predict a delivery schedule for collecting and delivering items based on available data on the availability of the items and the picker/driver. Merely using a computer cannot preclude these limitations being done by a human using pen and paper.
Thus, claims 1-20 recite an abstract idea (Step 2A, Prong One: YES).
Step 2A Prong 2 analysis: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d).
Claims 1-20: The judicial exception is not integrated into a practical application.
Claim 1 recites the additional elements of using generic computer components including a server computer in communication with a requestor device and payment system implementing the steps of :
(a) a location-based dispatch system (LBDS) to identify one or more resources …..;
(b) a neural network trained by the LBDS to receive order data associated with one or mor items from the requester device and
( c) to generate a resource selection schedule that automatically assigns and transmits control instructions to the identified inventory retrieval puller device or the identified transportation driver device to coordinate order retrieval and delivery without human scheduling input;
(d) one or more databases to store product characteristic data of the one or more items:
(e) a fleet management system to determine vehicle-capacity based vehicle selections from fleet information, and wherein the product characteristic data is tracked by the on- demand delivery system, and a vehicle capability requirement, based on weight of the one or more items, is generated by the fleet management system for each order;
(f) the requester device in electrical communication with the server to receive a payer-invite request from a user interface on a first application on a the requester device, the payer-invite request to generate an invitation to a payer to pay for a delivery order via a second application on a payer device, the delivery order to identify the one or more items to be purchased and delivered to a requester location associated with the requester device or inputted by the requester,
(g) wherein the payer is selected via a feature provided on the user interface on the first application on the requester device;
(h) the invitation to be transmitted to the payer device associated with the payer;
(i) a payment to be received by the payment system from the payer device, the payment provided in response to the invitation; and
(j) a driving instruction to be sent to a driver device or a vehicle device, the driving instruction instructing pick up of the one or more items and delivery of the one or more items to the requester location.
The limitations in steps (b), (f), (h), (i) (j) are mere data gathering and transmitting recited at a high level of generality, and thus are insignificant extra-solution activity. See MPEP 2106.05(g) (“whether the limitation is significant”). In addition, all uses of the recited judicial exceptions require such data gathering and output, and, as such, these limitations do not impose any meaningful limits on the claim. These limitations amount to necessary data gathering and transmitting. See MPEP 2106.05. The limitations in step (g) is also recited at a high level of generality of selecting a payer based on a provided feature which is a generic computer function. Also, the limitations in the step (d) is also recited at a high level of generality (i.e. as a general means of storing the characteristics of the items from the receiving the order step) , and amounts to mere post solution storing, which is a form of insignificant extra‐solution activity. The computer is recited at a high level of generality. In these limitations in steps (b), (d), (g), (f), (h), (i) and (j) , the computer is used as a tool to perform the generic computer functions of receiving and transmitting data. See MPEP 2106.05(f). In limitations (a), (c), and (e) the computer is used to perform an abstract idea, as discussed above in Step 2A, Prong One, such that it amounts to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f).
Steps , “ (a, (c) , and ( e) “, as recited are performed by generic computer systems and the computer is used to perform an abstract idea, as discussed above in Step 2A, Prong One, such that it amounts to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f). The step ( c) recites using a trained neural network to generally apply the abstract idea without placing any limits on how the trained neural network functions. The recitation of “using a trained neural networks” also merely indicates a field of use or technological environment in which the judicial exception is performed. Although the additional element “using a trained neural network” limits the steps of receiving order data, generating resource selection schedule and assigns and transmits instructions to the picker or driver for coordinating and delivering ordered goods “, these types of limitations merely confine the use of the abstract idea and insignificant extra solution activity to a particular technological environment (trained neural networks) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h). Executing these steps relate to receiving and transmitting data and processing the received data to generate a resource selection schedule with instructions for the picker or driver which do not necessitate inextricable tie to computer technology because these steps can be carried out manually and is just performing the disembodied concept on a general-purpose computer.
Even when viewed individually and in combination, these additional elements in the claim 1 do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).
The other independent claim 18 recites similar limitations as claim 1, except for reciting additional elements of a loyalty and analytics systems without providing details on their functionality and as such they are considered as mere generic computer components not imposing any meaningful limits on practicing the abstract idea and do not integrate the abstract idea into a practical. Claim 18 also recites using trained models to predict operational timing of the inventory retrieval puller device, or the transportation driver device, to generate digital dispatch commands, and to update fulfillment data in response to real-time sensor feedback from those devices. As analyzed in Step 2A, Prong One, the computer is used to perform an abstract idea, as discussed above in Step 2A, Prong One, such that it amounts to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f). Accordingly, similar to the analysis for claim 1, the claim 18 when viewed in combination, the additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).
Examiner has reviewed the dependent claims 2-17and 19-20. They recite limitations directed to non-functional descriptive data, qualifying and extending the scope of limitations recited in claim 1, directed to reciting receiving, sending data non-significant extra-solution activity and falling withing mental processes using generic computer server recited at a high level of generality, which do not impose any meaningful limits on practicing the abstract idea. Therefore, dependent claims 2-17, 19-20 similar to claims 1 and 18 directed to an abstract idea.
Even when viewed in combination, the additional elements in claims 1-20 do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES). Step 2A=Yes. Claims 1-20 are directed to abstract ideas.
Step 2B analysis: This part of the eligibility analysis evaluates whether the claim as a whole amounts to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
The claims 1-20 do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Since claims are as per Step 2A are directed to an abstract idea, they have to be analyzed per Step 2B, if they recite an inventive step, i.e., the claims recite additional elements or a combination of elements that amount to “Significantly More” than the judicial exception in the claim. As discussed above with respect to Step 2A Prong Two, the additional elements in the claims 1-20 amount to no more than mere instructions to apply the exception using a generic computer components, and generally linking the judicial exception to a particular technological environment or field of use. The same analysis applies here in 2B, i.e., mere instructions to apply the exception using a generic computer components, and generally linking the judicial exception to a particular technological environment or field of use using a generic computer components cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
As per MPEP 2106 , a conclusion that an additional element or elements is/are extra-solution activity, or are well-understood, conventional and routine activity in step 2A should be re-evaluated in step 2B. Here the receiving, acquiring, gathering, transmitting, providing data/information and storing steps were considered extra-solution activity, or are well-understood, conventional and routine activities in step 2A and thus they are re-evaluated in step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field.
The background of the example does not provide any indication that the computer components are anything other than a generic, off the shelf computer component and the Symantec, TLI, OIP Techs, Versata court decisions cited in MPEP 2106.05(d) (ii) indicate that mere receiving, acquiring, transmitting, providing data and storing data steps using a generic computer are well-understood, routine, conventional functions when they are claimed in a merely generic manner (as it is here).
Accordingly, a conclusion that the receiving, receiving, acquiring, transmitting, providing data and storing data steps are well-understood, routine conventional activities are supported under Berkheimer Option 2. See MPEP 2106.05 (f) 2: Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. 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 or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit).
Even when considered individually and in combination, the additional elements in claims 1-20 represent mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept. (Step 2B: NO).
Thus, pending claims 1-20 are patent ineligible.
3. Prior art discussion:
Reference the currently amended claims 1 and 18 , the prior art of record, alone or combined, Borders et al.[US Patent 7,177,825 cited in the IDS filed 02/23/2023 and cited in the Non-Final Rejection mailed 02/14/2024], hereinafter Borders teaches a method for device-based coordination of multi-party delivery processes for a delivery order identifying one or more items to be purchased and delivered to a requester location associated with the requester device or inputted by the requester [See col.27, lines 56-67] and the funds capturing component allows the user to select one of the payment features from a credit card or debit card option [See col.33, lines 4-8], and on receiving shipment status information the delivery data is downloaded on a mobile field office which manages the delivery courier to be dispatched to deliver the ordered goods at the requestor’s location See [Col.23, line 56-.col.24, line 1]. However, Borders neither teaches nor renders obvious at least the limitations, as a whole comprising, “a neural network trained by the LBDS to receive order data associated with one or more items from the requester device and generate a resource selection schedule and instructions to the identified inventory retrieval puller or the identified transportation driver to coordinate order retrieval and delivery, a fleet management system to determine vehicle-capacity based vehicle selections from fleet information, and wherein the product characteristic data is tracked by the on- demand delivery system, and a vehicle capability requirement, based on weight of the one or more items, is generated by the fleet management system for each order: and the requester device in electrical communication with the server to receive a payer-invite request from a user interface on a first application on a the requester device, the payer-invite request to generate an invitation to a payer to pay for a delivery order via a second application on a payer device, the delivery order to identify the one or more items to be purchased and delivered to a requester location associated with the requester device or inputted by the requester, wherein the payer is selected via a feature provided on the user interface on the first application on the requester device”. Claims 2-17 depend from claim 1, and claims 10-20 depend from claim 18.
(ii) Kim et al. [US 20150317622 A1 cited in the Non-Final Rejection mailed 02/14/2024], hereinafter Kim teaches . Kim, in the same field of endeavor of electronic commerce including online purchases requiring payments provided by a third- party , teaches [See Kim claims 1 and 4] “associating a first mobile phone number of a purchaser with a second, different mobile phone number of a payer; receiving a payment request at the computing device directly via a network from the purchaser”, but does not teach all the limitations, as a whole, discussed above for claims 1 and 18.
Foreign reference:
(iii) JP 2004315116A cited in the Final Rejection mailed 07/22/2025 [See para 0018 and Fig.1] describes a delivery system receiving an order for an article from a requestor with the delivery information and a delivery system delivers the ordered goods at the requestor’s location.
NPL reference:
(iv) Article, “U.S. Patent and Trademark Office Releases Bank of America's Patent Application for Anonymous Electronic Payment System”, Publication info: Global IP News. Banking Patent News [New Delhi] 10 Sep 2015; retrieved from Dialog on 05/30/2022 [cited in the IDS filed 02/23/2023 and in the parent Application17094881] states that the patent Application No. 14/716458 filed with USPTO discloses systems and methods for autonomous payments to an individual, comprising a user interface associated with an individual generating a payment request for a transaction to an account associated with an entity. In response to the request generating an Internet accessible address to the electronic payment user interface and an authorization input from the payer to make an electronic payment of monetary funds from an account of the payer to the account of the individual is received.
Response to Arguments
4. Applicant's arguments filed 10/22/2025, see pages 10-16 with respect to rejection of claims 1-20 under 35 USC 101 “that the claims are directed to an abstract idea without significantly more, when analyzed as per MPEP 2106”, have been fully considered but they are not persuasive for following reasons:
The subject eligibility matter of claims is analyzed and evaluated per MPEP 2106 comprising steps : Step 1, Step 2a, Prong one, Step 2a, Prong Two, and Step 2B.
Step 2A, Prong One:
Examiner disagrees with the Applicant’s agreements on page 14, “ the amended claims do not recite a judicial exception or a fundamental method of organizing human activity. The claimed steps do not involve interpersonal or economic relationships but rather technical processes for automatically managing networked devices and digital resources. The LBDS executes trained neural models to predict operational metrics such as load, unload, and pulling times; to schedule optimal driver arrival and departure; …….. These are computer executed, data driven functions, not abstract mental processes or business rules. The operations materially improve system performance and reduce latency in order fulfillment. As held in McRO v. Bandai Namco Games America, 837 F.3d 1299 (Fed. Cir. 2016), automation of processes that previously required human judgment constitutes a technological improvement rather than an abstract idea.”, because Step 2A, Prong One analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim. The independent claims 1 and 18, recite limitations, “identify one or more resources of at least one order fulfillment facility, ….: receive order data associated with one or more items from the requester, and generate a resource selection schedule …..; determine vehicle-capacity based vehicle selections from fleet information….. the requester to receive a payer-invite request from a user, the payer-invite request to generate an invitation to a payer to pay for a delivery order, …. the invitation transmitted to the payer; a payment received from the payer, the payment provided in response to the invitation; and a driving instruction sent to a driver, the driving instruction instructing pick up of the one or more items and delivery of the one or more items to the requester location”, cover performance of a commercial action related to receiving an order from a requestor, determining the resources within a predetermined proximity of the requestor and a suitable vehicle that can be used to deliver the ordered goods, providing instructions to a picker/driver for coordinating retrieval of goods and delivering them, followed by facilitating payment from a third party by sending an invitation to the payer for making payment and in response to receiving the payment providing instructions to the driver of the vehicle for delivering the ordered goods to the location of the requestor. These limitations of claim 1 fall within the group of Certain Methods of Organizing Human Activity” of abstract ideas. See MPEP 2106.04(a)(2), subsection II.
The limitations comprising , “ (a) identify one or more resources of at least one order fulfillment facility, an inventory retrieval puller, or a transportation driver within a threshold distance of a requester, (c) generate a resource selection schedule and instructions to the identified inventory retrieval puller or the identified transportation driver to coordinate order retrieval and delivery, ( e) determine vehicle-capacity based vehicle selections from fleet information, and wherein the product characteristic data is tracked, and a vehicle capability requirement, based on weight of the one or more items, is generated for each order” and “predicting operational timing of the inventory retrieval puller device, or the transportation driver device, to generate digital dispatch commands, and to update fulfillment data in response to real-time sensor feedback from those devices” in claim 18, under their broadest reasonable interpretation, cover performance within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. For example, a human operator can determine resources/suppliers for an order received from a requestor in the nearest vicinity of the requestor, predict/prepare and provide instructions on a paper for the picker/driver for coordinating retrieval and delivery of items. Also, based on the properties and weights of the goods ordered a human operator can select a suitable vehicle for delivering the goods. Thus, claim 1 with its dependent claims 2-17 recite “Mental Processes”.
In view of the foregoing, claims 1 and 18 with their dependent claims 2-17, and 19-20 respectively do recite “Certain Methods of Organizing Human Activity”, and “Mental Processes” groupings of abstract ideas.
Step 2A, Prong Two analysis:
Examiner disagrees with the Applicant’s agreements on pages 14-15.
Applicant’s arguments , “ The Claims Integrate Any Alleged Abstract Idea into a Practical Application. Even if the claims were viewed as reciting a judicial exception, the amended features integrate that concept into a practical application that improves computer functionality and logistics system performance. The amended claims integrate predictive load and unload analysis, pulling time estimation, and blockchain based transaction verification within a coordinated dispatch framework that enhances scheduling accuracy and system reliability. The learning system dynamically trains on real world data, including item, location, fulfillment center, and personnel information, to continuously improve delivery time estimation and coordination between puller and driver devices. This feedback-based prediction model enhances the technical performance of the LBDS by reducing idle time, improving synchronization, and increasing throughput efficiency. The cryptographically linked blocks form the backbone of the LBDS data validation system, ensuring immutability, order sequencing, and auditability across devices; functions central to system reliability rather than extra solution activity. The multi device authorization and communication process includes distinct applications on separate devices that exchange verified transaction data via the distributed LBDS. This structured, cryptographically authenticated communication process represents a concrete technical network improvement, not a generic data transmission.”, “, relate to commercial activity of fulfilling orders and improving the fulfilment of orders does not amount to a technical improvement.
Step 2A, Prong Two eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d). The claim 1 recites additional limitations a computer processor executing the steps (a), (b), (c), (d), ( e), (f), (g), ( h), ( i), and ( j). The limitations in steps (b), (f), (h), (i) (j) are mere data gathering and transmitting recited at a high level of generality, and thus are insignificant extra-solution activity. See MPEP 2106.05(g) (“whether the limitation is significant”). In addition, all uses of the recited judicial exceptions require such data gathering and output, and, as such, these limitations do not impose any meaningful limits on the claim. These limitations amount to necessary data gathering and transmitting. See MPEP 2106.05. The limitations in step (g) is also recited at a high level of generality of selecting a payer based on a provided feature which is a generic computer function. Also, the limitations in the step (d) is also recited at a high level of generality (i.e. as a general means of storing the characteristics of the items from the receiving the order step) , and amounts to mere post solution storing, which is a form of insignificant extra‐solution activity. The computer is recited at a high level of generality. In these limitations in steps (b), (d), (g), (f), (h), (i) and (j) , the computer is used as a tool to perform the generic computer functions of receiving and transmitting data. See MPEP 2106.05(f). In limitations (a), (c), and (e) the computer is used to perform an abstract idea, as discussed above in Step 2A, Prong One, such that it amounts to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f).
Steps , “ (a, (c) , and ( e) “, as recited are performed by generic computer systems and the computer is used to perform an abstract idea, as discussed above in Step 2A, Prong One, such that it amounts to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f). The step ( c) recites using a trained neural network to generally apply the abstract idea without placing any limits on how the trained neural network functions. The recitation of “using a trained neural networks” also merely indicates a field of use or technological environment in which the judicial exception is performed. Although the additional element “using a trained neural network” limits the steps of receiving order data, generating resource selection schedule and assigns and transmits instructions to the picker or driver for coordinating and delivering ordered goods “, these types of limitations merely confine the use of the abstract idea and insignificant extra solution activity to a particular technological environment (trained neural networks) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h). Executing these steps relate to receiving and transmitting data and processing the received data to generate a resource selection schedule with instructions for the picker or driver which do not necessitate inextricable tie to computer technology because these steps can be carried out manually and is just performing the disembodied concept on a general-purpose computer. Even when viewed individually and in combination, these additional elements in the claim 1 do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).
The other independent claim 18 recites similar limitations as claim 1, except for reciting additional elements of a loyalty and analytics systems without providing details about their functions and therefore they are considered as mere generic computer components and do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claim 18 also recites using trained models to predict operational timing of the inventory retrieval puller device, or the transportation driver device, to generate digital dispatch commands, and to update fulfillment data in response to real-time sensor feedback from those devices. As analyzed in Step 2A, Prong One,
the computer is used to perform an abstract idea, as discussed above in Step 2A, Prong One, such that it amounts to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f). Accordingly, similar to the analysis for claim 1, the claim 18 when viewed in combination, the additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., blockchain based transaction verification within a coordinated dispatch framework that enhances scheduling accuracy and system reliability. The learning system dynamically trains on real world data, including item, location, fulfillment center, and personnel information, to continuously improve delivery time estimation and coordination between puller and driver devices. The cryptographically linked blocks form the backbone of the LBDS data validation system, ensuring immutability, order sequencing, and auditability across devices; functions central to system reliability rather than extra solution activity.) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
In view of the foregoing, the applicant’s arguments, directed to independent claims 1 and 18, that the claims integrate the abstract idea into a practical application are not found persuasive. Even when viewed individually and in combination, these additional elements in the claims 1 and 18 do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).
Step 2B:
Examiner disagrees with the Applicant’s agreements on pages 14-15, “ Under Step 2B, the amended claims recite significantly more than any alleged abstract concept. The combination of the neural network-based learning system, blockchain enabled data verification, and multi device communication structure represents a non-conventional technological integration that provides measurable improvements in computer operation and logistics management. The neural network continuously learns from ground truth operational data to predict timing metrics and optimize scheduling, thereby automating and improving processes that previously required human oversight. The LBDS ensures data immutability, security, and sequencing through cryptographically linked blocks that provide verified audit trails. These features collectively enhance the accuracy, transparency, and trustworthiness of the logistics dispatch process. “ as already discussed above for Step 2A, Prong Two are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Step 2B eligibility analysis evaluates whether the claim as a whole amounts to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05. As discussed above with respect to Step 2A Prong Two, the additional elements in the claims 1-20 amount to no more than mere instructions to apply the exception using a generic computer components, and generally linking the judicial exception to a particular technological environment or field of use. The same analysis applies here in 2B, i.e., mere instructions to apply the exception using a generic computer components, and generally linking the judicial exception to a particular technological environment or field of use using a generic computer components cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. Further, the background of the example does not provide any indication that the computer components are anything other than a generic, off the shelf computer component and the Symantec, TLI, OIP Techs, Versata court decisions cited in MPEP 2106.05(d) (ii) indicate that mere receiving, acquiring, transmitting, providing data and storing data steps using a generic computer are well-understood, routine, conventional functions when they are claimed in a merely generic manner (as it is here). Accordingly, a conclusion that the receiving, receiving, acquiring, transmitting, providing data and storing data steps are well-understood, routine conventional activities are supported under Berkheimer Option 2. See MPEP 2106.05 (f) 2:
Examiner respectfully disagrees with the applicant’s statement “ As in Enfish v. Microsoft, 822 F.3d 1327 (Fed. Cir. 2016), and BASCOM Global Internet Services v. AT&T Mobility, 827 F.3d 1341 (Fed. Cir. 2016), the claimed system provides a specific improvement in computer functionality and network coordination rather than applying a generic computer to an abstract process.””, because this is a conclusive statement without providing any parallels or comparison of the claims of the instant application with the claims of Enfish or Bascom.
In Enfish the claims were not directed to an abstract idea as they were directed to configuring a computer for creating a new database table resulting in improvements to computer operations which is an improvement on the existing database technology including a single table opposed to a standard model where each entry is in a separate table, including faster search times and smaller memory requirements. In the instant Application the claims are not directed to any improvement in computer operations but instead directed to an abstract idea of providing business solutions for order fulfillment with the additional elements amounting to no more than mere instructions to apply the exception using a generic computer components, and generally linking the judicial exception to a particular technological environment or field of use. So Enfish has no applicability.
In Bascom, although the claims were directed to the abstract idea of filtering content, an inventive concept can be found in a non-conventional and non-generic arrangement of known, conventional pieces. In Bascom the court held that claims contained ‘significantly more” than an abstract idea of ‘filtering content because they recited a separate point of novelty that is : installation of filtering tool at a specific location on Internet of the content, remote from end users, with customizable filtering features specific to each end user. Bascom does not apply in this case. In contrast the claims in the instant application do not provide an unconventional functionality but are directed to an abstract idea of providing business solutions for order fulfillment with the additional elements amounting to no more than mere instructions to apply the exception using a generic computer components, and generally linking the judicial exception to a particular technological environment or field of use. So Bascom has no applicability.
In view of the foregoing, the rejection of independent claims 1 and 18 under 35 USC 101 is sustainable and maintained.
Conclusion
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/YOGESH C GARG/Primary Examiner, Art Unit 3688