DETAILED ACTION
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 .
Claims 1-13 and 15-20 have been examined.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 July 9, 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 1-13 and 15-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (abstract idea) without significantly more. This judicial exception is not integrated into a practical application because it is recited at a high degree of generality, such that even if some embodiments of the claims might not be directed to an abstract idea, other embodiments would be. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception, as set forth in detail below.
The following 35 U.S.C. 101 analysis is performed in accordance with section 2106 of the Manual of Patent Examination Procedure (concerning Patent Subject Matter Eligibility Guidance). First, it is determined that the claims are directed to a statutory category of invention. See MPEP 2106.03 (II). Independent claim 1 recites a method, and therefore falls within the statutory category of process, as do its dependents; independent claim 8 recites a system comprising at least a memory and at least one processor coupled to the memory, and therefore falls within the statutory category of machine, as do its dependents; independent claim 15 recites a non-transitory computer-readable medium having instructions stored thereon, and therefore falls within the statutory category of article of manufacture, as do its dependents (Mayo test, Step 1). (Step 1: YES)
The claims are then analyzed to determine whether the claims are directed to a judicial exception. See MPEP 2106.04. The claims are analyzed to evaluate whether they recite a judicial exception (Step 2A, Prong One) as well as analyzed to evaluate whether the claims recite additional elements that integrate the judicial exception into a practical application of the judicial exception (Step 2A, Prong Two). See MPEP 2106.04.
Claims 1-13 and 15-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea, and specifically to commercial interactions under the field of organizing human activity without significantly more (Mayo test, Step 2A, Prong 1). The claims recite a method, system, and computer-readable medium for supplier management. See representative claim 1, as amended, set forth below with language indicating the relevance to commercial interactions bolded:
A computer-implemented method, comprising:
obtaining, by a procurement prediction engine, one or more operating parameters formed from at least one specified field of a resource-planning system, the one or more operating parameters representing structured data associated with system activity including one or more of a purchase order, a backorder, a past-due order, a return-to-vendor event, or a supplier communication;
processing, by the procurement prediction engine, a condition of a case by executing one or more parameters using one or more perception nodes comprising a neural network trained using supervised and unsupervised learning techniques to generate a model-derived value for the one or more operating parameters;
correlating, by a correlation module of the procurement prediction engine, the model-derived value of the one or more operating parameters with at least one corresponding critical parameter stored in association with the resource-planning system to generate a set of parameter associations based on aligning the model-derived value with the critical parameter according to a predefined parameter mapping stored in memory and applied by the correlation module, the critical parameter defining a threshold condition associated with operation of the resource-planning system including one or more system configuration or execution conditions relevant to supplier-management processing;
comparing, by the procurement prediction engine, the parameter associations to at least one predefined threshold associated with the critical parameter to identify a deviation comprising a discrepancy between the model-derived value of the operating parameters and an expected system performance condition defined by the critical parameter;
adapting, by the procurement prediction engine, at least one of the neural network, the perception nodes, or the correlation module to improve subsequent detection of deviations affecting system operation when the deviation exceeds an adaptation condition diagnosed during training; and
in response to identifying the deviation, automatically initiating execution of at least one predefined sequence of automated operations defined by one or more workflow rules or execution logic within the resource-planning system, without user intervention, the predefined sequence executed based on conditions associated with the deviation, including modifying at least one system configuration setting or workflow execution state to adjust the deviation, wherein the sequence of automated operations causes at least one of automated updating of system records, triggering of procurement operations, or modification of inventory or transaction data, thereby generating operations to correct the resource-planning system.
Analyzing claim 1 under Step 2A, Prong Two, this judicial exception is not integrated into a practical application, partly because mere instructions to implement an abstract idea on a computer, or use a computer as a tool to perform an abstract idea, are not indicative of integration into a practical application, nor is linking the use of the judicial exception to a particular technological environment or field of use (Mayo test, Step 2A, Prong 2). Adding insignificant extra-solution activity to the judicial exception is also not indicative of integration into a practical application. Claims 1 and its dependents do not recite improvements to the functioning of a computer or to any other technology or technical field. The claims do not recite applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition. The claims do not recite applying the judicial exception with, or by the use of, a particular machine. The claims do not recite effecting a transformation or reduction of a particular article to different state or thing. The claims do not recite applying or using a judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. Claim 1 recites a computer-implemented method, but the computer is not described except as being present at a high level of abstraction, without details of structure, and an abstract idea does not become non-abstract merely because a computer is involved in applying it, as the Supreme Court ruled in Alice Corporation v. CLS Bank. The reasoning set forth here also applies to parallel system claim 8 and its dependents, and to parallel computer-readable medium claim 15 and its dependents. (Step 2A, Prong Two: NO for claims 1-20).
Next, under Step 2B of the Alice/Mayo test, the claims are analyzed to determine whether there are additional claim limitations that individually, or as an ordered combination, ensure that the claims amount to significantly more than the abstract idea. See MPEP 2106.05. This is in part a reiteration of the Step 2A, Prong Two analysis, and further involves the question of whether specific limitations are other than what is well-understood, routine, and conventional activity in the field.
There are no additional elements recited in the claims to raise them to significantly more than the judicial exception. In particular, the claims do not add a specific limitation other than what is well-understood, routine, and conventional activity in the field (Mayo test, Step 2B). The detailed method, system, and computer-readable medium recited are non-obvious over the prior art, but non-obviousness under 35 U.S.C. 103 is a different issue from eligibility under 35 U.S.C. 101. The specific steps of the claims, such as: processing the one or more operating parameters using one or more perception nodes of a neural network; correlating a correlation module of the procurement prediction engine; comparing, by the procurement prediction engine, the parameter associations to at least one predefined threshold to identify a deviation comprising a discrepancy; adapting, by the procurement prediction engine, at least one of the neural network, the perception nodes, or the correlation module to improve subsequent detection of deviations affecting system operation when the deviation exceeds an adaptation condition diagnosed during training; and modifying at least one system configuration setting or workflow execution state to adjust the deviation, etc., do not qualify, alone or in combination, to raise the claimed method and system to significantly more than an abstract idea.
Specifically with regard to independent claim 1, Flint (U.S. Patent Application Publication 2022/0277196) discloses (paragraph 29, emphasis added), “The process of training neural networks using input datasets and using trained neural networks to generate predictions is well-known in the prior art.” Further, Gervais (U.S. Patent Application Publication 2019/0353366) discloses (paragraph 78, emphasis added), “A predictive model is used by the neural network inference engine 412 for inferring output(s) based on inputs, as is well known in the art of neural networks.” Further, the courts have recognized the computer function of storing and retrieving information in memory as well-understood, routine, and conventional, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092. Hence, the recitation in claim 1 of “correlating, by a correlation module of the procurement prediction engine, model-diagnosed value of the one or more operating parameters with at least one critical parameter stored in association with the resource-planning system, the critical parameter defining a threshold condition relevant to supplier-management processing” need involve only well-understood, routine, and conventional technology, and the same applies to “executing one or more perception nodes comprising a neural network trained using supervised and unsupervised learning techniques”. The limitations of claim 1, whether considered separately or in combination, do not raise the claimed method to significantly more than an abstract idea.
Claim 2, which depends from claim 1, recites additional elements, in particular, “obtaining a first plurality of inference results generated by a first machine learning (ML) model of the procurement prediction engine and a second plurality of inference results generated by a second ML model of the procurement prediction engine”. Puri et al. (U.S. Patent Application Publication 2021/0073671) discloses (paragraph 1, emphasis added), “Recent years have seen a rapid increase in the utilization of computer-implemented learning models to perform a variety of tasks. For example, conventional systems utilize learning models to edit digital videos/digital images, generate digital predictions, and/or classify digital objects.” Hence, the recited use of machine learning models to generate inference results need involve only well-understood, routine, and conventional technology. The limitations of claim 2, whether considered separately or in combination with each other and with the limitations of claim 1, do not raise the claimed method to significantly more than an abstract idea.
Claim 3, which depends from claim 2, recites generating inference results which are used to determine system operations, including at least one of workflow execution, scheduling adjustments, or resource allocation within the resource planning system; the operations of claim 3 only peripherally involve technology. Claim 4, which depends from claim 3, recites nothing specifically technological. The limitations of claims 3 and 4, whether considered separately or in combination with each other and with the limitations of claims 1 and 2, do not raise the claimed method to significantly more than an abstract idea.
Claim 3, which depends from claim 2, recites generating inference results which are used to determine system operations, including at least one of workflow execution, scheduling adjustments, or resource allocation within the resource planning system; the operations of claim 3 only peripherally involve technology. Claim 5, which depends from claim 3, recites generating or configuring a call to action condition, which is not specifically technological. Claim 7, which depends from claim 5, recites that the procurement inference engine is trained to generate system condition determinations based on historical operational data, which is not specifically technological. The procurement inference engine requires only well-understood, routine, and conventional, as set forth above with respect to claim 1, based on Gervais and Flint. The limitations of claims 3, 5, and 7, whether considered separately or in combination with each other and with the limitations of claims 1 and 2, do not raise the claimed method to significantly more than an abstract idea.
Claim 3, which depends from claim 2, recites generating inference results which are used to determine system operations, including at least one of workflow execution, scheduling adjustments, or resource allocation within the resource planning system; the operations of claim 3 only peripherally involve technology. Claim 6, which depends from claim 3, recites that the system condition is used to initiate execution of at least one intercompany system operation, external system operation, response management processing, or resolution execution; this limitation is not in itself technological. The limitations of claims 3 and 6, whether considered separately or in combination with each other and with the limitations of claims 1 and 2, do not raise the claimed method to significantly more than an abstract idea.
Independent claim 8 recites “A system, comprising: a memory; and at least one processor coupled to the memory and configured to: [perform operations corresponding to the steps of method claim 1].” Avidan et al. (U.S. Patent Application Publication 2017/0193592) discloses (paragraph 25, emphasis added), “Although not illustrated, it should be appreciated that the ecommerce server 110, the merchant computer 120, and the customer computer 130 each include conventional components, such as a processor and a memory medium storing computer-readable instructions that are executable by the processor to perform various operations including those described herein.” Hence, the memory and coupled at least one processor are well-understood, routine, and conventional technology. Otherwise, the operations of claim 8 require only well-understood, routine, and conventional technology on the same grounds as the method steps of claim 1, and based on Flint and Gervais, as cited above with respect to claim 1. The limitations of claim 8, whether considered separately or in combination, do not raise the claimed system to significantly more than an abstract idea.
Claim 9, which depends from claim 8, is parallel to claim 2, and thus requires only the use of well-understood, routine, and conventional technology, as set forth above with regard to claim 2, and based on Puri. The limitations of claim 9, whether considered separately or in combination with each other and with the limitations of claim 8, do not raise the claimed system to significantly more than an abstract idea.
Claim 10, which depends from claim 9, is parallel to claim 3, and thus only peripherally involves technology, which need be only well-understood, routine, and conventional technology, as set forth above with regard to claim 3. Claim 11, which depends from claim 10, is parallel to claim 4, and thus requires only the use of well-understood, routine, and conventional technology, as set forth above with regard to claim 4. The limitations of claims 10 and 11, whether considered separately or in combination with each other and with the limitations of claims 8 and 9, do not raise the claimed system to significantly more than an abstract idea.
Claim 10, which depends from claim 9, is parallel to claim 3, and thus only peripherally involves technology, which need be only well-understood, routine, and conventional technology, as set forth above with regard to claim 3. Claim 12, which depends from claim 10, is parallel to claim 5, and thus requires only the use of well-understood, routine, and conventional technology, as set forth above with regard to claim 5. Therefore, the limitations of claims 10 and 12, whether considered separately or in combination with each other and with the limitations of claims 8 and 9, do not raise the claimed system to significantly more than an abstract idea.
Claim 10, which depends from claim 9, is parallel to claim 3, and thus requires only the use of well-understood, routine, and conventional technology, as set forth above with regard to claim 3. Claim 13, which depends from claim 10, is parallel to claim 6, and thus requires only the use of well-understood, routine, and conventional technology, as set forth above with regard to claim 6. The limitations of claims 10 and 13, whether considered separately or in combination with each other and with the limitations of claims 8 and 9, do not raise the claimed system to significantly more than an abstract idea.
Independent claim 15 recites, “A non-transitory computer-readable medium having instructions stored thereon that, when executed by at least one computing device, cause the at least one computing device to:[perform operations corresponding to the steps of method claim 1].” Avidan et al. (U.S. Patent Application Publication 2017/0193592) discloses (paragraph 25, emphasis added), “Although not illustrated, it should be appreciated that the ecommerce server 110, the merchant computer 120, and the customer computer 130 each include conventional components, such as a processor and a memory medium storing computer-readable instructions that are executable by the processor to perform various operations including those described herein. The computer-readable instructions can be stored on non-transitory computer-readable storage media of a conventional type, whether devices and/or materials.” Hence, the non-transitory computer-readable medium having instructions stored thereon is well-understood, routine, and conventional technology. Otherwise, the operations of claim 15 require only well-understood, routine, and conventional technology on the same grounds as the method steps of claim 1, and based on Flint and Gervais, as cited above with respect to claim 1. The limitations of claim 15, whether considered separately or in combination, do not raise the claimed computer-readable medium to significantly more than an abstract idea.
Claim 16, which depends from claim 15, is parallel to claim 2, and thus requires only the use of well-understood, routine, and conventional technology, as set forth above with regard to claim 2, and based on Puri. The limitations of claim 16, whether considered separately or in combination with each other and with the limitations of claim 15, do not raise the claimed computer-readable medium to significantly more than an abstract idea.
Claim 17, which depends from claim 16, is parallel to claim 3, and thus only peripherally involves technology, which need be only well-understood, routine, and conventional technology, as set forth above with regard to claim 3. Claim 18, which depends from claim 17, is parallel to claim 4, is parallel to claim 4, and thus requires only the use of well-understood, routine, and conventional technology, as set forth above with regard to claim 4. The limitations of claims 17 and 18, whether considered separately or in combination with each other and with the limitations of claims 15 and 16, do not raise the claimed computer-readable medium to significantly more than an abstract idea.
Claim 17, which depends from claim 16, is parallel to claim 3, and thus only peripherally involves technology, which need be only well-understood, routine, and conventional technology, as set forth above with regard to claim 3. Claim 19, which depends from claim 17, is parallel to claim 5, and thus requires only the use of well-understood, routine, and conventional technology, as set forth above with regard to claim 5. The limitations of claims 17 and 19, whether considered separately or in combination with each other and with the limitations of claims 15 and 16, do not raise the claimed computer-readable medium to significantly more than an abstract idea.
Claim 17, which depends from claim 16, is parallel to claim 3, and thus only peripherally involves technology, which need be only well-understood, routine, and conventional technology, as set forth above with regard to claim 3. Claim 20, which depends from claim 17, is parallel to claim 6, and thus requires only the use of well-understood, routine, and conventional technology, as set forth above with regard to claim 6. The limitations of claims 17 and 20, whether considered separately or in combination with each other and with the limitations of claims 15 and 16, do not raise the claimed computer-readable medium to significantly more than an abstract idea. (Step 2B: NO for claim 1-13 and 15-20)
Non-Obvious Subject Matter
Claims 1-7 are rejected under 35 U.S.C. 101, claims 3-7 are rejected under 35 U.S.C. 112; additionally, claims 1-7 and especially 3-7 are objected to for informalities. However, claims 1-7 recite non-obvious subject matter.
Claims 8-13 are rejected under 35 U.S.C. 101, claims 10-14 are rejected under 35 U.S.C. 112; additionally, claims 10-14 are objected to for informalities. However, claims 8-14 recite non-obvious subject matter.
Claims 15-20 are rejected under 35 U.S.C. 101, claims 17-20 are rejected under 35 U.S.C. 112; additionally, claims 15-20 are objected to for informalities. However, claims 15-20 recite non-obvious subject matter.
The following is a statement of reasons for the indication of allowable subject matter: Devarakonda et al. (U.S. Patent Application Publication 2020/0210922) is the closest prior art of record as general background for the claimed invention, being directed to resource planning in the context of a supply chain involving suppliers. Devarakonda discloses, for example, neural networks (paragraph 68), and discloses (paragraph 98, emphasis added), “The action sequence, whether executed in the manual mode, the semi-autonomous mode, or the fully-autonomous mode, may include the machine-learning (ML) application 218 communicating, over a network, an electronic message to a planning system (enterprise resource planning system 204).” Devarakonda does not disclose the specific operations of the claimed method, system, and non-transitory computer-readable medium. Demeilliez et al. (U.S. Patent Application Publication 2021/0026755) discloses comparison with a predetermined threshold value (paragraphs 25-30, e.g., paragraph 25, emphasis added) “it further comprises a step of identifying a resource with an anomaly risk, said identification step comprising comparing a value of future consumption of a resource to be predicted to a predetermined monitoring threshold value, the resource to be predicted having to a resource with an anomaly risk when a predetermined monitoring threshold value is exceeded.”
Merg et al. (U.S. Patent Application Publication 2018/0357614) discloses determining a deviation (e.g., Abstract, emphasis added), “determining a comparison element based on a quantity of VROs in the second set including the common VSP; determining a deviation between the baseline and the comparison element; determining the deviation exceeds a threshold and responsively determining one or more common factors associated with at least a subset of the second set”. Merg further discloses (paragraph 114, emphasis added), “Accordingly, the processor 204, when comparing the deviation to the threshold, can determine that the deviation of 230% exceeds the threshold of 30%. Similarly, in the second embodiment, the threshold can be 25%. The processor 204 can compare the deviation of 50% to the threshold of 25% and can determine that the deviation exceeds the threshold.”
DeBo et al. (U.S. Patent 9,465,778) discloses the execution of predefined operations in response to a deviation (column 6, lines 47-50, emphasis added), “The action module 120, when executed by the processors 114, may automatically determine and complete appropriate actions (e.g., selected from a set of pre-defined actions) in response to a detection of a deviation from guidelines, standards, and practices.”
However, Devarakonda, Demeilliez, Merg, DeBo, and the other prior art references of record do not, alone or in combination, disclose, teach, or reasonably suggest the specific method of claim 1, or the parallel system of claim 8 or non-transitory computer-readable medium of claim 15.
The above statement is applicable to each of the independent claims.
Response to Arguments
Applicant's arguments filed July 20, 2026 have been fully considered, but they are not persuasive. The only remaining issue is that the claims are rejected under 35 U.S.C. 101. Applicant argues (pages 16-18 of the Amendment and Remarks of July 9, 2026) that the claims do not recite an abstract idea. Examiner replies that the claims are directed to an abstract idea, and that it is not dispositive that they do not solely recite the abstract idea without any specific actions or technology, an issue which will be addressed below. Applicant argues (page 17 of the Amendment and Remarks) that the claimed automated operations produce concrete changes within the computing system itself, including updating system records, triggering procurement operations, and modifying inventory or transaction data. Examiner replies, first, that procurement operations are commercial interactions, and therefore an abstract idea. Secondly, the courts have recognized storing and retrieving information in memory as well-understood, routine, and conventional functions, in Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d at 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1363, 115 USPQ2d at 1092-93 (Fed. Cir. 2015). Therefore, updating system records and modifying inventory or transaction data, which presumably involve storing changed information in memory, require only the use of well-understood, routine, and conventional functions and technology. Some of the claims in the four Shepherd patents at issue in Alice Corporation v. CLS Bank International recited the use of technology, but the Supreme Court nonetheless ruled that the claims were not patent-eligible.
Applicant then argues, “The Examiner asserts that the claimed operations could be performed by a human manager facilitating commercial operation. Applicant respectfully disagrees.” Examiner does not find quite this assertion in the Final Rejection of February 27, 2026.
Applicant then argues, “The Examiner asserts that the claims are directed to ‘commercial interactions’ based on the recited context of purchase orders, backorders, and supplier activity. However, this characterization improperly focuses on the source of the data rather than the claimed operations performed on that data. A distinction that is legally significant under § 101.” Examiner replies that the claims are written at a high level of generality. For example, “initiating execution of at least one predefined sequence of automated operations defined by one or more workflow rules or execution logic within the resource-planning system, without user intervention, the predefined sequence executed based on conditions associated with the deviation, including modifying at least one system configuration setting or workflow execution state to adjust the deviation, wherein the sequence of automated operations causes at least one of automated updating of system records, triggering of procurement operations, or modification of inventory or transaction data, thereby generating operations to correct the resource-planning system” means that an automated system takes some kind of action in response to identifying a deviation, and somehow correct the resource-planning system, but it is not clear what, specifically, is done.
Applicant proceeds to argue (pages 18 and 19 of the Amendment and Remarks) from the distinction over the cited references. Examiner agrees that the claims are not obvious over the prior art of record, but replies that non-obviousness under 35 U.S.C. 103 is a different issue from patent-eligibility under 35 U.S.C. 101. Claims can be ineligible under 35 U.S.C. 101 despite being non-obvious, or obvious over the prior art despite being patent-eligible under 35 U.S.C. 101 (as might be the case for a mechanical device).
Applicant argues (pages 19 and 20 of the Amendment and Remarks) that the claims are integrated into a practical application (Step 2A, Prong Two of the Alice/Mayo test). Examiner reiterates what was set forth in the previous Final Rejection, that being of some practical use of some kind does not necessarily make a claimed invention patent-eligible, and in particular reiterates that the present claims are analogous to the representative claim in the Ultramercial, Inc. v. Hulu, LLC decision, in which a method claim included, inter alia, “a third step of providing the media product for sale at an Internet website”, and therefore could not be carried out without the use of computer and telecommunication technology. The Court of Appeal for the Federal Circuit found the claims patent-ineligible, and wrote, “The claims’ invocation of the Internet also adds no inventive concept. As we have held, the use of the Internet is not sufficient to save otherwise abstract claims from ineligibility under § 101.” Examiner maintains that the use of a neural network is also not sufficient to save otherwise abstract claims from ineligibility under § 101.
Further, Examiner is unpersuaded by Applicant’s that claimed features “apply any alleged abstract idea in a manner that improves the functioning of the resource-planning system by enabling automated detection and correction of system-level deviations.” The resource-planning system is not improved in a technological sense, but merely applied vaguely and generally defined operations to correct the resource-planning system somehow in response to identifying a vague and general deviation of some kind.
Applicant argues (pages 20 and 21 of the Amendment and Remarks) that the claims recite significantly more under Step 2B. Examiner has set forth above why the claims, as most recently amended, do not recite significantly more than an abstract idea. Applicant naturally sees the matter differently, and argues that what is claimed is “a specific, non-conventional architecture in which machine learning is integrated with system control to enable automated, real-time modification of system operation.” Examiner maintains that the technology used is merely well-understood, routine, and conventional, an expression which applies both to use of a neural network as such and to “modification of system operation”, specially when the nature of the modification is unclear, and merely recited at a high level of generality, which as has been set forth above, describes the current claims.
Therefore, Examiner believes that it is proper, and in accordance with the statute, with judicial precedent, and with Patent Office guidance to maintain the 35 U.S.C. 101 rejections of the claims as currently amended.
Conclusion
The following are
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. DeBo et al. (U.S. Patent 9,465,778) disclose automated governance of data applications.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NICHOLAS D ROSEN, whose telephone number is (571)272-6762. The examiner can normally be reached 9:00 AM-5:30 PM, M-F. Non-official/draft communications may be faxed to the examiner at 571-273-6762, or emailed to Nicholas.Rosen@uspto.gov (in the body of an email, please, not as an attachment).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Marissa Thein, can be reached at 571-272-6764. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/NICHOLAS D ROSEN/ Primary Examiner, Art Unit 3689 August 21, 2026
Prosecution Insights