DETAILED ACTION
This Non-Final Office Action is in response to the arguments amendments, and Request for Continued Examination filed August 31, 2026.
Claims 1, 8, 15, 21, and 28 have been amended.
Claim 29 is newly added.
Claims 1, 4-5, 8-12, 15-19, 21, 23, and 25-29 are currently pending and have been considered below.
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
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 August 31, 2026 has been entered.
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, 4-5, 8-12, 15-19, 21, 23, and 25-29 are rejected under 35 U.S.C. 101 because the claimed invention is directed towards non-eligible subject matter.
In terms of Step 1, claims 1, 4-5, 8-12, 15-19, 21, 23, and 25-29 are directed towards one of four categories of statutory subject matter.
In terms of Step 2(a)(1), independent claims 1, 8, and 15 are directed towards (as represented by claim 1), “a method for providing intelligent supply chain optimization, comprising: receiving a transaction agreement request from a user, wherein the transaction agreement request includes a plurality of order details; generating a revised transaction agreement request based on one or more user profiles, a multi-party entity feedback loop, one or more constraints relating to the transaction agreement request, and transaction agreement fulfillment requirements of the entity; providing, a multi-party interactive environment, wherein the chatbot enables real time communication between the user and one or more providers and displays offers and counteroffers to the user; negotiating, in the interactive user interface, the revised transaction agreement between the user and the one or more providers of the multi-party entity feedback loop during one or more current negotiations; searching a plurality of existing shipment plans and the one or more current negotiations based on the plurality of order details; identifying, from the plurality of existing shipment plans and the one or more current negotiations, an existing shipment plan specifying an agreed delivery time slot associated with a provider located in a geographic area associated with the user; determining a candidate delivery time slot for delivery of a physical product associated with the transaction agreement request, wherein the candidate delivery time slot is temporally proximate to the agreed delivery time slot; assessing, based on a current logistics state, a marginal cost of fulfilling delivery of the physical product during the candidate delivery time slot; generating a time-sensitive counteroffer comprising the candidate delivery time slot and a shipment cost based on the marginal cost; receiving, through the chatbot, an acceptance of the candidate delivery time slot and the shipment cost; and in response to receiving the acceptance, selecting the candidate delivery time slot for delivery of the physical product to the user, and delivering, by the provider, the physical product to the user during the candidate delivery time slot agreed upon by the provider and the user”. The claims are describing the creation of a transaction agreement based on negotiating partner feedback, fulfillment requirements, and restrictions. This consideration further includes the aspect of the chatbot as the chatbot is further interacting with and facilitating the contract negotiation providing offers and counteroffers. As such, the claims are describing a commercial interaction and business relation, as well as an interaction between people. This commercial interaction further includes the transactional aspects of the shipment and delivery slots, counteroffers with respect to the delivery, basing the shipping/delivery on marginal cost, and providing the product based on the agreed upon slot. Providing the negotiation through the chatbot (which is further identified as an additional element) is merely providing the negotiation and transactional interaction Therefore, the claims are directed towards an abstract idea under the certain method of organizing human activity grouping.
Step 2(a)(II) considers the additional elements in terms of being transformative into a practical application. The additional elements of the independent claims are, “by a processor {claim 1}, A system for providing intelligent supply chain optimization, comprising: one or more computers with executable instructions that when executed cause the system to {claim 8}, and A computer program product for providing intelligent supply chain optimization in a computing environment, the computer program product comprising: one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instruction comprising: program instructions to {claim 15}; training a machine learning component to learn and collect feedback data relating to a supply chain state, one or more acceptance or rejections of historical transaction agreements and revised transaction agreement requests, behaviors of users, and one or more policies based on a value function; providing, by the machine learning component, a multi-party interactive environment through a chatbot within an interactive user interface, during one or more current negotiations using a machine learning operation of the machine learning component, wherein the machine learning component is retrained using reinforcement learning; receiving, through the chatbot, an acceptance”. The additional elements are described in the originally filed specification figure 1 and paragraphs [46-55]. The additional elements are merely described as generic technology to implement the abstract idea. The computer elements are not describing a technical improvement. In terms of the machine learning, the originally filed specification describes the ML and training steps in paragraphs [19-25]. The specification merely describes techniques and high-level ML elements to implement the abstract idea. The training steps are describing the input elements that are used to train and the ML is a generic model to provide the analysis to the identified abstract idea. As such, the training and ML are generic technology to implement the abstract idea. In terms of the chatbot, the element is described in the originally filed specification [77 and 84]. The chatbot is not described in terms of being a technical improvement, but rather a tool to implement the abstract idea (a tool to interface the negotiation and business relation, as well as the interaction between people). The chatbot and interactive interface are not directed towards a technical improvement, but rather generic technology to implement the abstract idea. Therefore, the additional elements are not transformative into a practical application. Refer to MPEP 2106.05(f).
Step 2(b) considers the additional elements in terms of being significantly more than the identified abstract idea. The additional elements of the independent claims are, “by a processor {claim 1}, A system for providing intelligent supply chain optimization, comprising: one or more computers with executable instructions that when executed cause the system to {claim 8}, and A computer program product for providing intelligent supply chain optimization in a computing environment, the computer program product comprising: one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instruction comprising: program instructions to {claim 15}; training a machine learning component to learn and collect feedback data relating to a supply chain state, one or more acceptance or rejections of historical transaction agreements and revised transaction agreement requests, behaviors of users, and one or more policies based on a value function; providing, by the machine learning component, a multi-party interactive environment through a chatbot within an interactive user interface, during one or more current negotiations using a machine learning operation of the machine learning component, wherein the machine learning component is retrained using reinforcement learning; receiving, through the chatbot, an acceptance”. The additional elements are described in the originally filed specification figure 1 and paragraphs [46-55]. The additional elements are merely described as generic technology to implement the abstract idea. The computer elements are not describing a technical improvement. In terms of the machine learning, the originally filed specification describes the ML and training steps in paragraphs [19-25]. The specification merely describes techniques and high level ML elements to implement the abstract idea. The training steps are describing the input elements that are used to train and the ML is a generic model to provide the analysis to the identified abstract idea. As such, the training and ML are generic technology to implement the abstract idea. In terms of the chatbot, the element is described in the originally filed specification [77 and 84]. The chatbot is not described in terms of being a technical improvement, but rather a tool to implement the abstract idea (a tool to interface the negotiation and business relation, as well as the interaction between people). The chatbot and interactive interface are not directed towards a technical improvement, but rather generic technology to implement the abstract idea. Therefore, the additional elements are not significantly more than the identified abstract idea. Refer to MPEP 2106.05(f).
Dependent claims 4, 11, and 18 are further describing the identified abstract ideas. The claims are directed towards (as represented by claim 4), “further including identifying the one or more marginal transaction agreement fulfillment requirements for performing the transaction agreement request”. The claims are further describing the commercial activity in terms of identifying transactional requirements. The claims also fall into the mental process as a person with pen and paper can provide and revise a contract based on marginal transaction requirements presented in the negotiation. As such, the claims are further describing the identified abstract ideas and are not directed towards additional elements that are significantly more or transformative into a practical application.
Dependent claim 5, 12, and 19 are further describing the abstract idea and not directed towards additional elements beyond those identified above. The claims are directed towards, “further including: identifying one or more transaction agreement fulfillment options for performing the transaction agreement request from the user; and the entity; and selecting a transaction agreement fulfillment option for performing the transaction agreement request from the user by the entity having a least amount of constraints and transaction agreement fulfillment requirements for fulfilling the transaction agreement request”. The claims are further describing the contract negotiation based on transaction requests and fulfillment based on having the least amount of constraints. The claims are not directed towards additional elements that are transformative into a practical application or significantly more than the identified abstract idea.
Dependent claims 9 and 16 are further describing the abstract idea. The claims are directed towards, “wherein the executable instructions when executed cause the system to query a supply chain state to identify a cost for servicing the transaction agreement request”. The claims are further describing the commercial aspect in terms of providing a query to identify cost for servicing the agreement request (i.e. contract). The claims are also describing the mental process as a person with pen and paper can mentally opine and consider the cost to a contract. As such, the claims are further describing the identified abstract ideas and are not directed towards additional elements that are significantly more or transformative into a practical application.
Dependent claims 10 and 17 are further describing the identified abstract ideas. The claims are directed towards, “wherein the executable instructions when executed cause the system to generate and monitor the one or more user profiles”. The claims are further describing providing user profiles that are generated and monitored. The claims are further describing a collection of information through the mental process consideration and providing elements of the contract under the commercial activity consideration. The claims, as considered with respect to the independent claims, are providing elements of the contract negotiation that falls within the identified abstract ideas. As such, the claims are further describing the identified abstract ideas and are not directed towards additional elements that are significantly more or transformative into a practical application.
Dependent claims 21, 23, and 25 are further describing the abstract idea and are not directed towards additional elements beyond those identified above. The claims are directed towards, “wherein the processor is internal to an intelligent supply chain enhancing service, the intelligent supply chain enhancing service comprising an interactive supply chain component, a transaction agreement generator component, a monitoring component, the machine learning component, and a feedback component, wherein the intelligent supply chain enhancing service suggests offers and counteroffers to the user which are accepted or rejected by the user in the interactive user interface”, “further comprising: offering, in the interactive user interface, one or more time slots to the user associated with the one or more providers, wherein each of the one or more time slots includes an estimated cost of shipment determined by the machine learning component”, and “further comprising: querying, by an interactive orchestrator component, a generation component based on the plurality of order details received in the transaction agreement request from the user; assessing, by a logistics component, a current logistics state based on the plurality of order details received and the one or more user profiles of the multi-party entity feedback loop; and providing, in the interactive user interface, one or more updated counteroffers to the user based on the assessment of the current logistics state”. The claims are further describing the commercial activity in terms of the negotiation and offer/counteroffer for the order details. As such, the claims are further describing the abstract idea identified above. The claims are further directed towards additional elements considered above. The claims are not directed towards additional elements that are significantly more or transformative into a practical application.
Claims 26-28 are directed towards additional elements beyond those identified above. The claims are directed towards, “wherein the machine learning component is retrained using the reinforcement learning based on at least observations, rewards, and actions between the user and the one or more providers”, “wherein the observations include a set of orders and associated parameters from the one or more providers, the actions include offer decisions by the user within the interactive user interface, and the rewards include revenue and cost outcomes associated with the actions of the user”, and “wherein the machine learning component learns for the retraining based on at least learning a supply chain state, one or more acceptance or rejections of historical transaction agreements and revised transaction agreement requests, actions of the user within the interactive user interface, and one or more policies based on a value function, wherein the value functions is a prediction of a future total reward”. The additional elements are with respect to the machine learning elements for training and retraining. The originally filed specification describes the ML and training steps in paragraphs [19-25]. The specification merely describes techniques and high level ML elements to implement the abstract idea. The training and retraining in the claims are describing observations and outcomes, as well as historical agreements and other transaction policy elements. The training is merely generic technology to implement the abstract idea. The training is not describing an improvement to training machine learning models but rather utilizing generic training techniques to implement the ML modeling to implement the abstract idea. The additional elements are not directed towards a technical improvement and thus are not significantly more or transformative into a practical application. Refer to MPEP 2106.05(f).
Claim 29 is further describing the abstract idea and not directed towards additional elements beyond those identified above. The claim is directed towards, “wherein generating the time-sensitive counteroffer comprises generating a plurality of alternative price-slot pairs including the candidate delivery time slot and the shipment cost, and wherein receiving the acceptance comprises receiving a selection of the candidate delivery time slot and the shipment cost before expiration of a time limit for accepting the time-sensitive counteroffer”. The claim is further describing the commercial interaction and negotiation in terms of delivery time slots and time-sensitive counteroffers. The claim is not directed towards additional elements that are transformative into a practical application or significantly more than the identified abstract idea. Refer to MPEP 2106.05(f).
The claims are describing an abstract idea without additional elements that are significantly more or transformative into a practical application. Therefore, claims 1, 4-5, 8-12, 15-19, 21, 23, and 25-29 are rejected under 35 USC 101 for being directed towards non-eligible subject matter.
Response to Arguments
In response to the arguments filed August 31, 2026 on pages 13-23 regarding the 35 USC 101 rejection, specifically that the claimed invention is directed towards eligible subject matter.
Examiner respectfully disagrees.
The arguments allege that the amended claim limitations are not directed towards a transaction agreement, however, further clarifies that the amendments are directed towards shipment plans and current negotiations which is within the consideration of commercial interaction. Providing a negotiation based on delivery and other cost factors is within the commercial interaction for the identified abstract idea. The claim is considered as a whole with respect to the amended claim limitations and the searching, assessing, and selecting/delivering are within the commercial interaction for the negotiation and delivery of the product.
In terms of the additional element considerations, the computer and chatbot elements are considered generic technology to implement the abstract idea. The arguments allege that the processor and chatbot are provided in terms of an ordered combination that provides additional elements that are beyond generic technology. The computer and chatbot elements are not described in terms of technical improvements, but rather generic technology to implement the identified abstract idea. As such, the claims are not directed towards additional elements that are transformative into a practical application. The arguments further allege that the additional elements under Step 2b are technical improvements with respect to DDR and Diamond v Diehr. The processor and chatbot based on the considered specification paragraphs are merely generic technology. The chatbot and processor are not describing a specific technical improvement. As such, the claims are not directed towards additional elements that are significantly more than the identified abstract idea. As such, claims 1, 8, and 15 are maintaining the 35 USC 101 rejection, as considered above in light of the amended claim limitations.
Lacking any further arguments, claims 1, 4-5, 8-12, 15-19, 21, 23, and 25-29 are maintaining the 35 USC 101 rejection, as considered above in light of the amended and newly added claim limitations.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Thakkar et al [20220067746] (customer support post-purchase including delivery of product);
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/ANDREW CHASE LAKHANI/Primary Examiner, Art Unit 3629
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