DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application is being examined under the pre-AIA first to invent provisions.
This Final Office Action is responsive to Applicant's amendment filed on 1 October 2025. Applicant’s amendment on 1 October 2025 amended claims 1 and 10. Currently Claims 1-8, 10, 11, 14, 15, 17, 18, 21, and 22 are pending and have been examined. Claims 9, 12, 13, 16, 19 and 20 were previously canceled. The Examiner notes that the 101 rejection has been maintained.
Examiner’s Note
The Examiner notes that the arguments regarding the prior art rejections were persuasive and the rejection on the prior have been withdrawn. It is further noted that if the remaining 101 rejection is overcome regarding the Alice rejection the claims could be in condition for allowance.
Response to Arguments
Applicant's arguments filed 1 October 2025 have been fully considered but they are not persuasive.
The Applicant argues on pages 8-9 that “the Office Action states that the claim features are directed to mental processes and that the claims do not include additional elements that amount to significantly more than the judicial exception. Applicant respectfully traverses. Under Step 2A Prong One, the claims do not recite a judicial exception of an abstract idea. On a high-level, the pending claims describe a technical approach of how a schedule is generated using a plurality of circuits each configured to do a specific set of tasks. The recited patent claim features are not mental processes because they are expressly directed to specific, concrete implementations in computer hardware and software, rather than abstract ideas that can be performed solely in the human mind. The claim requires a plurality of specialized "circuits"-including, for example, an employer surveyor circuit, embedding generator circuit, artificial intelligence circuit, schedule experimentation circuit, scheduling circuit, time sequence provisioning circuit, and schedule warden circuit-which are described as performing complex data processing, clustering, embedding generation, model training, and real- time schedule management. These operations involve the manipulation of large datasets, the generation and use of high-dimensional vector embeddings, the application of artificial intelligence models, and the execution of schedule experimentation and optimization routines that are not practically or feasibly performed mentally. Furthermore, the claim recites "configurable connector circuits" that distribute computation tasks across different computing hardware and adapt data formats for compatibility between modules, further emphasizing that the technological and structural nature of the invention are far beyond mental capabilities”.
The Examiner respectfully disagrees.
In response to the arguments the Examiner notes that the Applicant argues that the claims do not recite a judicial exception because they are "expressly directed to specific, concrete implementations in computer hardware" involving "specialized circuits" performing operations "not practically or feasibly performed mentally." This argument misapprehends the Step 2A, Prong One analysis in several fundamental respects. First, the inquiry at Step 2A, Prong One is not limited to whether claims recite mental processes that can be performed in the human mind. Rather, Step 2A, Prong One asks whether the claims recite any judicial exception, which includes three groupings of abstract ideas: (1) mathematical concepts; (2) certain methods of organizing human activity; and (3) mental processes. MPEP 2106.04(a); 2019 Revised Patent Subject Matter Eligibility Guidance). A claim that recites a combination of a mental process, mathematical concepts or methods of organizing human activity is directed to an abstract idea even if it cannot be performed mentally. Here, the recited operations generating schedules using AI models, creating embeddings, performing clustering, executing optimization routines, and managing schedules involve a mental activity that incorporates a mathematical concepts (algorithms, data analysis, optimization calculations) and methods of organizing human activity (scheduling, resource allocation, workforce management). These fall squarely within the abstract idea groupings regardless of whether they can be performed mentally. The Supreme Court has repeatedly held that mathematical algorithms and methods of organizing business operations are abstract ideas. Alice Corp. v. CLS Bank Int'l, (methods of organizing human activity); Gottschalk v. Benson, (mathematical algorithms).
Second, Applicant's argument that the operations are "not practically or feasibly performed mentally" does not remove them from the abstract idea category. The Federal Circuit addressed this precise argument in CyberSource Corp. v. Retail Decisions, Inc., 6, holding claims ineligible even though "some of the method steps at issue... may be so complex and detailed that they cannot be performed in the human mind" because the claims still embodied an abstract idea implemented on generic computers. The court explained that the relevant question is not whether the steps are too complex for mental performance, but whether they represent an abstract idea applied using conventional computer components. Similarly, in SAP America, Inc. v. InvestPic, LLC, the court held claims ineligible that used neural networks for investment analysis, noting that complexity and computer implementation do not overcome the abstract nature of the underlying concept.
Third, merely reciting implementation in "circuits" rather than using terms like "processor," "module," or "computer" does not avoid abstraction. The Supreme Court has cautioned against elevating form over substance in eligibility analysis. Alice, ("We tread carefully in construing this exclusionary principle lest it swallow all of patent law. At some level, all inventions... embody, use, reflect, rest upon, or apply laws of nature, natural phenomena, or abstract ideas."). The Federal Circuit has consistently held that claims reciting functional results to be achieved by generic computer components are abstract regardless of the terminology used to describe those components. In Intellectual Ventures I LLC v. Symantec Corp., the court analyzed claims reciting a "virus scanning processor," "filtering processor," and other specialized processors, holding them ineligible because the processors were "described only by their functions" without any "inventive concept in the non-conventional and non-generic arrangement of known, conventional pieces." The court explained that "the claimed processors... amount to nothing more than generic computer components" because they were described purely in functional terms.
Here, the recited circuits are similarly described in purely functional terms: an "employer surveyor circuit" performs surveying, an "embedding generator circuit" generates embeddings, an "artificial intelligence circuit" applies AI models, a "schedule experimentation circuit" performs experimentation, and so forth. These are functional descriptions of what tasks the circuits perform, not structural descriptions of how the circuits are configured or how they differ from conventional processors. Without specific structural limitations showing how these "circuits" are configured differently from generic processors programmed to perform these functions, the claim recitations amount to generic computer components performing abstract operations. MPEP 2106.05(f).
The specification must be examined to determine whether the recited "circuits" represent specific hardware implementations or merely software modules/processors performing programmed functions. If the specification describes these circuits as software modules, processors executing instructions, or configurable hardware performing programmed tasks (as suggested by the term "configurable connector circuits"), then the "circuit" terminology is merely claim drafting that does not change the abstract nature of the recited operations. In re TLI Commc'ns LLC Patent Litig., (holding claims ineligible where specification showed that "telephone unit" and "server" were conventional components performing conventional functions despite hardware-suggestive claim language).
Fourth, Applicant's emphasis on complexity—"manipulation of large datasets," "high-dimensional vector embeddings," "complex data processing"—does not establish patent eligibility. In Electric Power Group, LLC v. Alstom S.A., the court held claims ineligible that collected and analyzed massive amounts of power grid data, explaining that "merely selecting information, by content or source, for collection, analysis, and display does nothing significant to differentiate a process from ordinary mental processes" and that "the fundamental problem... is that the claims are directed not to a novel computer or an advanced sensor, but to information about the real world." Here, similarly, the claims are directed to schedule generation and management using data analysis—information processing operations that are abstract regardless of data volume or computational complexity.
The 2024 AI Subject Matter Eligibility Update provides directly relevant guidance. The USPTO emphasized that AI-based inventions must be evaluated using the same framework as other software inventions, and that "claims that recite AI or machine learning are not automatically patent-eligible or ineligible." 89 Fed. Reg. 58128, 58134 (July 17, 2024). The guidance explains that reciting AI operations or neural networks does not, by itself, remove claims from the abstract idea category. Rather, the analysis must focus on whether the claims improve computer technology or another technical field versus merely using computers to perform abstract operations.
Example 48, Claim 1 from the 2024 Update is instructive. That claim recited "determining embedding vectors as a function of the input signal" using a deep neural network—operations analogous to the "embedding generator circuit" and "artificial intelligence circuit" recited here. The USPTO found those claims ineligible at Step 2A because "the recited generic DNN merely adds a generic computer component to perform the method and therefore fails to provide an improvement to the technology or technical field." 89 Fed. Reg. at 58146. The instant claims appear to suffer the same deficiency: they recite AI circuits, embedding generation, and data processing without demonstrating improvements to computer technology itself.
To advance compact prosecution the Examiner notes that in order to overcome a Step 2A, Prong One finding, Applicant cannot merely argue that operations are complex or performed by "circuits." The proper analysis examines what the circuits do the functions they perform. If those functions involve mathematical operations (algorithms, data transformations, calculations) or organizing human activity (scheduling, resource allocation), they recite abstract ideas regardless of terminology or complexity.
The key question is not "Can this be performed mentally?" but rather "Do the claims recite mathematical concepts or methods of organizing human activity?" If yes, the claims recite abstract ideas, and the analysis proceeds to Step 2A, Prong Two to determine whether the abstract idea is integrated into a practical application.
To address the rejection properly, Applicant should focus on arguing (with specification support) how the claims integrate any recited abstract ideas into a practical application under Step 2A, Prong Two—for example, by demonstrating improvements to computer functionality, solutions to technical problems in computer systems, or other considerations set forth in MPEP 2106.05(a)-(c), (e)-(h). The rejection is therefore maintained.
.
The Applicant argues on pages 9-10 that “Even if the claims are misconstrued as being directed to a judicial exception, under Step 2A Prong Two, the claims do recite additional elements that integrate the alleged abstract idea into a practical application. Likewise, under Step 2B, the claims recite additional elements that amount to "significantly more" than the judicial exception. The present application is indeed a practical application as it provides an improvement in computer technology. The feature of a plurality of configurable connector circuits, as described, provides a concrete improvement in computer technology by enabling a modular, distributed, and dynamically scalable scheduling system. This architecture allows for efficient use of computing resources, seamless interoperability between diverse modules, and robust, fault-tolerant operation-capabilities that are not possible with traditional, monolithic scheduling systems… Applicant's specification states "[t]he methods and system include the use of configurable connectors that may adapt and format data outputs of different modules and/or algorithms that would normally not be compatible and/or usable between the different modules. In embodiments, various methods of biasing, data correction, and monitoring enable data compatibility and use between modules and/or algorithms that may normally not be compatible." See Specification, para. 300. "Connectors serve as the links/data tunnels that pass data between modules and/or manipulate inputs and/or outputs of modules, e.g., connectors chain modules together. In embodiments, connectors may weigh the outputs of one or more models. Connectors may be modules and may be configured with algorithms and/or circuits that learn which bias is appropriate to apply in a given situation. Connectors may also connect to other connectors." See Specification, para. 710. These steps improve the performance of the model used by the scheduling circuit to generate schedules”.
The Examiner respectfully disagrees.
In response to the arguments the Examiner notes where that Applicant argues that the claims integrate the abstract idea into a practical application under Step 2A, Prong Two, and recite significantly more under Step 2B, based on: (1) configurable connector circuits that distribute tasks across hardware and adapt data formats; and (2) experimental schedule updates that improve model performance. Applicant asserts these constitute improvements to computer technology. These arguments are not persuasive because they confuse using computers to achieve business improvements with improving how computers themselves function. The cited features describe a scheduling system that operates more effectively utilizing collecting information, analyzing information and then providing specific results, which is viewed as a business improvement achieved through conventional distributed computing and machine learning techniques not improvements to computer technology itself.
Applicant argues that "configurable connector circuits structured to propagate, bias, realign, or weight data between the scheduling circuit and at least one other circuit" and that "distribute schedule computation tasks across different computing hardware by adapting and formatting data outputs of one module... for compatibility with data inputs of another module" constitute improvements to computer technology by enabling "modular, distributed, and dynamically scalable scheduling." This argument fails because it describes using well-known distributed computing techniques to achieve better scheduling results, not improving computer functionality. The Federal Circuit has repeatedly held that distributing tasks across computing resources and formatting data for interoperability between modules are conventional data processing techniques that do not, by themselves, constitute improvements to computer technology.
In Elec. Power Grp., LLC v. Alstom S.A., the court held claims ineligible that collected data from multiple sources, analyzed it, and displayed results to users, explaining: "Gathering, sending, and presenting information is not 'applying' the information; it is merely a mental or mathematical process." The court emphasized that "claims directed to the collection, manipulation, and display of data" do not improve computer functionality merely because they involve multiple computer components or data formatting. Id. Similarly, in TLI Commc'ns LLC v. AV Auto. LLC, the court found claims ineligible that transmitted and stored data across systems, holding that "the use of conventional or generic technology in a nascent but well-known environment, without more, does not provide an inventive concept."
The specification passages quoted by Applicant confirm that the connector circuits perform conventional data processing functions. Paragraph 300 states that connectors "adapt and format data outputs of different modules and/or algorithms" and enable "data compatibility and use between modules" these are standard data transformation and interface compatibility operations performed by conventional middleware, adapters, and data pipelines. Paragraph 710 states that connectors "weigh the outputs of one or more models" and "may be configured with algorithms and/or circuits that learn which bias is appropriate" these describe conventional weighted aggregation and parameter tuning techniques commonly used in machine learning systems.
Applicant's assertion that this architecture provides "parallel and distributed computation," "interoperability between heterogeneous modules and hardware," and "dynamic scaling based on real-time resource availability" describes using established distributed computing techniques, not inventing new ones. Distributed computing, load balancing, data format adaptation, and modular system architectures have been fundamental concepts in computer science for decades. The MPEP explicitly states that "mere instructions to apply an exception using a generic computer component cannot provide an inventive concept." MPEP 2106.05(f).
Critically, Applicant compares the claimed system to "traditional, monolithic scheduling systems" that suffer from "bottlenecks, poor scalability, and high resource consumption." However, this comparison reveals that the improvement is to scheduling system performance the ability to generate better schedules more efficiently not to how computers function. The computers still perform standard operations: receiving data, processing it according to programmed algorithms, formatting outputs, and distributing tasks. These are conventional computer operations; what has improved is the scheduling result (business outcome), not computer functionality (technological capability).
The distinction is critical. In Enfish, LLC v. Microsoft Corp., the court found claims eligible where they were "directed to an improvement in the functioning of a computer" itself specifically, a novel database structure that improved how computers stored and retrieved data by using self-referential tables. The improvement was to computer operations: faster queries, more flexible data organization, reduced memory usage. Here, by contrast, the claimed system uses conventional computer operations (distributed processing, data formatting, weighted aggregation) to produce better schedules. The computer operates no differently than any distributed computing system; what differs is the application domain (scheduling) and outcome (better schedules).
This distinction is reinforced by the 2024 AI Subject Matter Eligibility Update. Example 47 involved claims to network intrusion detection that were found eligible because they "improved the functioning of a computer or technical field" by providing "an improvement in the technical field of network intrusion detection". The improvement was technological enhancing computer security systems. Here, the improvement is operational producing better work schedules through distributed processing. That is an improvement to business operations achieved by using computers, not an improvement to computer technology itself.
Applicant argues that automatically updating the scheduling model by "applying different incentive structures to experimental schedules," "evaluating each experimental schedule based on performance metrics," and "automatically updating the model to favor incentive structures and schedule features that result in improved schedule performance metrics" constitutes a technical improvement. This argument fails because improving a model's predictions or outputs is not the same as improving computer functionality. The cited features describe a reinforcement learning or optimization process where the system tests different scheduling approaches, measures their effectiveness, and adjusts the model accordingly. This improves the quality of schedules generated (business outcome) by training the model more effectively, but it does not improve how the computer processes data, manages memory, executes algorithms, or performs any computational operation.
The Federal Circuit addressed this precise issue in SAP America, Inc. v. InvestPic, LLC, holding claims ineligible that used neural networks trained on historical data to generate investment predictions. The court explained that "making predictions based on collected data" using machine learning does not improve computer technology: "the claims here do not require any nonconventional computer, network, or display components, or even a 'non-conventional and non-generic arrangement of known, conventional pieces.'" The fact that the model becomes more accurate through training does not mean the computer functions differently or better.
Similarly, in Intellectual Ventures I LLC v. Capital One Bank (USA), the court held claims ineligible that customized information based on user characteristics and performance feedback, explaining that "tailoring content based on information about a user is... abstract" and that using feedback to improve results does not transform the abstract idea into patent-eligible subject matter.
Here, the experimentation and model updating process describes iterative refinement of scheduling algorithms testing variations, measuring results, and adjusting parameters to optimize outcomes. This is conceptually similar to A/B testing, hyperparameter tuning, or reinforcement learning all established techniques for improving model performance. Using "incentive structures" and "performance metrics" to guide optimization represents applying conventional optimization principles to the scheduling domain. The specification does not describe any unconventional computational technique, novel optimization algorithm, or improvement to how computers perform machine learning operations. The cited features improve what the system produces (better schedules) by using conventional machine learning training techniques (experimentation, evaluation, parameter updates). They do not improve how the computer operates. The computer performs standard ML operations: generating variations, computing metrics, updating weights. These are routine computational operations in machine learning systems.
Under MPEP 2106.05(a), to qualify as an improvement to computer functionality, the claims must show that "the claimed invention improves the functioning of a computer or improves another technology or technical field." The relevant inquiry is whether the claims improve the technology itself versus merely using technology to improve a business process. The examples provided in the MPEP of improvements to computer technology include: self-referential databases (Enfish), enhanced computer security (Example 47), improved rendering of 3D graphics, and optimized network routing algorithms that reduce latency.
The instant claims do not recite improvements of this nature. They recite using distributed computing to generate schedules, using data formatting for interoperability, and using iterative optimization to improve scheduling models. These are applications of technology to scheduling problems, not improvements to technology itself. The specification confirms this by describing the invention's advantages in terms of scheduling system capabilities: "efficient use of computing resources" for scheduling, "interoperability between diverse modules" in the scheduling system, and "improved schedule performance metrics" for generated schedules. These are scheduling system improvements achieved through conventional computing techniques.
Applicant's comparison to "traditional, monolithic scheduling systems" further confirms that the claimed advance is in scheduling methodology, not computer technology. A monolithic scheduling system and a distributed scheduling system both use computers conventionally; they differ in system architecture for the scheduling application, not in computer functionality. This is analogous to the distinction in Alice Corp. v. CLS Bank Int'l, where the Court held that implementing an abstract idea on a "generic computer" does not transform it into patent-eligible subject matter, even if the computer implementation is more efficient than prior manual methods.
The claims do not integrate the abstract idea into a practical application under Step 2A, Prong Two, and do not recite significantly more than the abstract idea under Step 2B. The claims remain subject to rejection under 35 U.S.C. 101. The rejection is therefore maintained.
The Applicant argues on pages 10-11 that “the apparatus described in claim 1 is built on an agglomerate network architecture, which enables modular, distributed, and potentially parallel computation. The Specification states: "In one aspect, the methods and systems described herein provide for parallelization and/or distribution of computing tasks. The systems and methods enable schedule computation with a plurality of interconnected modules that may be distributed over different computing hardware. In one aspect, the computations of each module may be less complex and require fewer computation resources than a traditional monolithic implementation..." See Specification, para. 299. This modular approach allows for more efficient use of computational resources, as different parts of the scheduling process can be handled by specialized modules, potentially in parallel, reducing overall computation time and memory usage”.
The Examiner respectfully disagrees.
In response to the arguments the Examiner notes where the Applicant argues that the claimed "agglomerate network architecture" constitutes an improvement to computer technology because it "enables modular, distributed, and potentially parallel computation," citing specification par. 299, which states the system provides for "parallelization and/or distribution of computing tasks" where "computations of each module may be less complex and require fewer computation resources than a traditional monolithic implementation." Applicant asserts this "allows for more efficient use of computational resources... potentially in parallel, reducing overall computation time and memory usage." This argument is unpersuasive because it describes using conventional distributed computing techniques to improve scheduling application performance, not improving computer technology itself. Parallel and distributed computing architectures have been fundamental techniques in computer science for decades. Simply implementing a scheduling application using these well-known architectural patterns does not constitute an improvement to computer functionality.
The specification passage cited by Applicant confirms the conventional nature of the claimed approach. Paragraph 299 describes "parallelization and/or distribution of computing tasks" and states that "schedule computation is performed with a plurality of interconnected modules that may be distributed over different computing hardware" with "computations of each module [being] less complex." This describes a standard distributed systems architecture: decomposing a complex problem into smaller subproblems, distributing them across multiple processing units, and potentially executing them in parallel. These are textbook distributed computing principles that have been widely practiced since at least the 1980s-1990s with the advent of networked computing systems and formalized through numerous architectural patterns (e.g., microservices, service-oriented architectures, distributed processing frameworks).
The Federal Circuit has consistently held that using conventional distributed computing techniques does not provide an inventive concept. In Content Extraction & Transmission LLC v. Wells Fargo Bank, the court held claims ineligible that involved collecting data from various sources and transmitting it across networks, explaining that these claims "do not go beyond requiring the collection, display, and manipulation of data using generic computer components and conventional data-processing techniques." The court emphasized that "[n]early every computer system includes the essential elements" of receiving, processing, and transmitting data across networks. Id.
Similarly, in Intellectual Ventures I LLC v. Erie Indem. Co., the court found claims ineligible that involved storing and processing data across multiple computer systems, holding that "the claims' invocation of computers and networks that are not even arguably inventive" cannot confer eligibility. The court explained that distributing processing across multiple systems using conventional networking represents routine use of computers, not an improvement to computer technology. Here, the claimed architecture distributes scheduling computations across "interconnected modules" that may run on "different computing hardware" precisely the type of conventional distributed processing the Federal Circuit has found insufficient. The specification's acknowledgment that modules may operate "potentially in parallel" further confirms conventionality, as parallel processing has been a standard technique for improving application throughput since the earliest days of multi-processor systems.
Applicant's assertion that the architecture provides "more efficient use of computational resources," "reducing overall computation time and memory usage" requires careful analysis. Claims to improved efficiency can constitute improvements to computer technology when they represent novel technical solutions to computational problems, but not when they result from conventional application of known techniques. The specification indicates the claimed efficiency gains result from decomposing scheduling tasks into smaller modules a conventional software engineering practice. Paragraph 299 states that "computations of each module may be less complex and require fewer computation resources than a traditional monolithic implementation." This describes the well-known principle that dividing a problem into smaller subproblems can make each subproblem individually simpler. However, this is a consequence of problem decomposition generally, not a novel computer technology improvement.
The MPEP explains that to qualify as an improvement to computer technology under MPEP 2106.05(a), the claims must reflect "a specific improvement over prior systems, resulting in an improved computer capability." The guidance emphasizes that the improvement must be to "the functioning of a computer" or to "another technology or technical field," citing Enfish as an example where claims to a self-referential database structure "improved the way a computer stores and retrieves data in memory." MPEP 2106.05(a).
In Enfish, the claimed self-referential table structure provided concrete, measurable improvements: faster search times, increased flexibility in data modeling, and more efficient memory usage because of the novel data structure itself. The court found these constituted improvements to computer functionality because they changed how the computer performed fundamental operations (data storage and retrieval). Critically, the specification in Enfish described why and how the self-referential structure achieved these improvements through technical mechanisms inherent to the novel structure. Here, by contrast, the specification does not describe any novel computational technique, algorithm, or architecture that improves how computers process information. It describes distributing scheduling tasks across modules—an application architecture decision. The cited efficiency gains (potentially reduced computation time, potentially lower memory usage) are described as flowing from using a distributed rather than monolithic application architecture, not from any innovation in computer processing, memory management, or computational algorithms. The word "potentially" in Applicant's argument is also telling. The claim recites that modules "may be distributed over different computing hardware" (specification par. 299), suggesting this is an optional characteristic, not a required structural feature. Similarly, Applicant states the architecture "potentially" enables parallel computation and uses phrases like "may be less complex" and "can be handled by specialized modules." These conditional and permissive descriptions indicate that the claimed system uses conventional distributed computing capabilities available in standard computing systems, rather than requiring novel computer functionality.
Distinguishing Application Architecture from Computer Technology
The fundamental error in Applicant's argument is conflating application-level architectural decisions with improvements to computer technology. Every software system makes architectural choices: monolithic versus distributed, synchronous versus asynchronous, centralized versus decentralized, and so forth. These choices affect application performance, scalability, and maintainability—but they do not constitute improvements to computer technology unless they involve novel computational techniques or solve technical problems in how computers operate.
The Supreme Court addressed this distinction in Alice Corp. v. CLS Bank Int'l, holding that implementing an abstract idea using "generic computer components" does not transform it into patent-eligible subject matter, even if the computer implementation is more efficient than prior manual or monolithic implementations. The Court emphasized that "nearly any" abstract idea can be implemented more efficiently using computers, but this does not make the computer implementation patent-eligible.
Here, comparing the claimed distributed scheduling system to "traditional monolithic implementation" (par. 299) reveals that the advance is in scheduling system architecture—how the scheduling application is structured—not in computer technology. A monolithic scheduling application and a distributed scheduling application both use computers in conventional ways; they differ in how the scheduling problem is decomposed and allocated across computational resources, not in how those resources perform computations.
This is directly analogous to cases where courts have found claims ineligible despite efficiency improvements. In OIP Techs., Inc. v. Amazon.com, Inc., the court held claims ineligible to an improved price optimization system that processed offers more efficiently, explaining that "the claims are directed not to an improvement in computers as tools, but to certain arrangements of elements in price optimization." Similarly, in Bancorp Servs., L.L.C. v. Sun Life Assurance Co. of Can. (U.S.), the court found claims ineligible to a computerized system that managed insurance more efficiently than manual systems, holding that efficiency gains from computerization alone do not confer eligibility.
The 2024 AI Subject Matter Eligibility Update reinforces this principle. The USPTO explained that claims improving "the functioning of a computer or another technology or technical field" are eligible, but claims that merely use computers to improve business operations are not. Example 48, Claim 1 involved using neural networks for speech processing and was found ineligible because the claimed DNN "merely adds a generic computer component to perform the method and therefore fails to provide an improvement to the technology or technical field". The instant claims similarly use generic distributed computing components (modules, interconnections, parallel processing) to perform scheduling—this adds generic computer
To establish that architectural features constitute improvements to computer technology rather than mere application design choices, Applicant should demonstrate: Novel computational technique: Does the architecture employ a previously unknown method of processing, storing, or transmitting data that improves computer operations? Here, parallelization and distribution are well-known techniques. Technical solution to technical problem: Does the architecture solve a problem inherent in computer systems (e.g., cache coherency, network latency, memory fragmentation)? Here, the specification describes solving scheduling complexity an application-domain problem, not a computer systems problem. Measurable technological improvement: Does the specification provide concrete evidence of improved computer performance metrics (algorithmic complexity reduction, bandwidth efficiency, processing throughput) resulting from novel technical features? Here, the specification describes "potentially" reduced resources from problem decomposition a general principle, not a specific technological innovation. Structural requirements: Do the claims require specific structural configurations that differ from conventional architectures? Here, the claims recite functional descriptions of circuits performing scheduling tasks with "configurable connectors" generic components performing conventional data routing and transformation.
The specification's description of "parallelization and/or distribution" as features the system "provides for" (par. 299) indicates these are capabilities being used, not innovations being contributed. This is equivalent to stating that an application "provides for" data storage or network communication—these describe using existing computer capabilities, not improving them.
The claimed agglomerate network architecture represents a distributed application design that uses conventional parallel and distributed computing techniques to improve scheduling system performance. This constitutes using computer technology to improve a business process (scheduling in the form of a mental process), not improving computer technology itself. The claims do not integrate the abstract idea into a practical application under Step 2A, Prong Two, and do not recite significantly more than the abstract idea under Step 2B. The rejection is therefore maintained.
The Applicant argues on page 11 that “In yet another improvement in computer technology, claim 1 includes a schedule warden circuit that automatically detects and corrects schedule norm violations. Claim 1 recites: "detect whether a property of the time sequence data violates a schedule norm; and in response to determining that the property violates the schedule norm, execute a corrective action on the scheduling circuit in real-time..." Automating the detection and correction of schedule violations reduces the need for manual review and intervention, streamlining the scheduling process and further reducing computational and human resource requirements. Accordingly, the claims do include additional elements that integrate the judicial exception into a practical application. For at least these reasons, Applicant respectfully requests withdrawal of this rejection”.
The Examiner respectfully disagrees.
In response to the arguments the Examiner notes that the Applicant argues that claim 1 recites an improvement to computer technology through a "schedule warden circuit" that "automatically detects and corrects schedule norm violations" by detecting "whether a property of the time sequence data violates a schedule norm" and executing "a corrective action on the scheduling circuit in real-time." Applicant asserts this "reduces the need for manual review and intervention" and "reduces computational and human resource requirements," thereby integrating the abstract idea into a practical application. This argument is not persuasive because automating a process using generic computer components does not constitute an improvement to computer technology, even if the automation reduces manual labor or improves business efficiency. The Supreme Court and Federal Circuit have consistently held that merely implementing abstract ideas on computers to automate tasks that could otherwise be performed manually does not transform those ideas into patent-eligible subject matter.
The Supreme Court addressed this precise issue in Alice Corp. v. CLS Bank Int'l, holding claims ineligible that automated financial transactions using generic computer components. The Court explained that the claims "amounted to 'nothing significantly more' than an instruction to apply the abstract idea... using some unspecified, generic computer". The Court emphasized that "nearly any computer will be able to" perform such automated tasks, and that implementing abstract ideas on "a general-purpose computer" does not provide an inventive concept. The fact that automation might be more efficient than manual processes was irrelevant to the eligibility analysis.
In Ultramercial, Inc. v. Hulu, LLC, the Federal Circuit applied this principle to hold claims ineligible that automated content distribution, explaining that "the claims simply instruct the practitioner to employ conventional Internet and advertising functions to solve a business problem" and that "all of the claimed steps can be, and regularly are, performed by the human mind or using pen and paper." The court rejected arguments that automation provided practical benefits, holding that efficiency improvements from computerization do not confer eligibility.
Here, the claimed "schedule warden circuit" performs monitoring and corrective action functions: it detects whether schedule properties violate norms and executes corrective actions. These are abstract concepts evaluating data against rules and taking corrective steps implemented using generic computer components. The claim does not recite any specific technological innovation in how violation detection is performed, what computational technique enables real-time monitoring, or how corrective actions are executed in a manner that improves computer operations. The circuit is described purely functionally: it performs the task of detecting violations and correcting them, without structural limitations showing how it differs from conventional rule-checking and automated response systems.
Applicant's argument that the system "reduces the need for manual review and intervention" and "streamlines the scheduling process" describes a business efficiency improvement reducing human labor is not a technological improvement. The Federal Circuit has consistently distinguished between these two types of improvements, holding that only the latter satisfies 101.
In Credit Acceptance Corp. v. Westlake Servs., the court held claims ineligible that automated credit evaluation processes, explaining that "using a computer to accelerate the process and to determine which offer to send does not add an inventive concept." The court emphasized that "the claims here do not improve the computer or its components, but rather recite only standard operations to allow computers to function as tools in the performance of otherwise well-understood operations." The fact that automation reduced manual work was not relevant to eligibility.
Similarly, in Smart Sys. Innovations, LLC v. Chi. Transit Auth., the court found claims ineligible to automated fare collection systems that reduced manual ticket processing, holding that using computers "to perform conventional business processes" does not constitute patent-eligible subject matter even when "the conventional business processes are performed more efficiently."
Here, Applicant explicitly frames the improvement in terms of reducing "manual review and intervention" and reducing "human resource requirements" these are business efficiency gains from automation, not improvements to computer technology. The computer performs conventional monitoring operations (checking data against rules) and conventional control operations (executing corrective actions) standard computer functions that have been performed since early rule-based systems and automated control systems. The improvement is that humans no longer need to perform these tasks manually, but this describes using computers as labor-saving tools, not improving how computers function.
The claimed operations—detecting violations of norms and executing corrective actions represent fundamental computer operations that have been performed conventionally for decades. Rule-based monitoring (IF condition violated THEN take action) is basic computational logic present in virtually all control systems, monitoring systems, and automated management systems.
The Federal Circuit has held that such monitoring and response operations are abstract and do not constitute improvements to computer technology. In Elec. Power Grp., LLC v. Alstom S.A., the court held claims ineligible that monitored power grid data, detected anomalous conditions, and displayed alerts, explaining that "selecting information, by content or source, for collection, analysis, and display does nothing significant to differentiate a process from ordinary mental processes" and that the claims were "directed not to a novel computer or an advanced sensor, but to information about the real world." The court emphasized that monitoring data and taking actions based on detected conditions are abstract concepts, not technological improvements.
Similarly, in Intellectual Ventures I LLC v. Symantec Corp., the court found claims ineligible that monitored email for spam indicators and filtered messages, holding that these claims did not "improve the functioning of the computer itself" but rather performed "filtering based on content" using generic computer components. The court explained that detecting undesirable characteristics and taking corrective action (filtering) represents an abstract idea implemented on conventional computers. Here, the schedule warden circuit detects whether schedule properties violate norms a monitoring operation analogous to detecting spam, detecting anomalies, or detecting rule violations in any domain. It then executes corrective action an automated response analogous to filtering messages, triggering alerts, or adjusting parameters. The claim does not recite how the detection is performed (what algorithm, what data structures, what computational technique) or how the corrective action improves computer operations. Without such specificity, the claim covers any implementation of norm-checking and automated correction using generic computer components.
The claim recites that corrective action is executed "in real-time," which Applicant may view as providing specificity. However, the Federal Circuit has held that adding temporal requirements such as "real-time" or "immediate" does not transform abstract ideas into patent-eligible subject matter absent a specific technological innovation enabling such operation. In Bancorp Servs., L.L.C. v. Sun Life Assurance Co. of Can. (U.S.), the court held that requiring operations to be performed "in real-time" did not provide an inventive concept where the claims did not explain how real-time operation was achieved through novel technical means. Similarly, in buySAFE, Inc. v. Google, Inc., the court found that requiring a computer system to operate in a particular temporal manner does not confer eligibility when the underlying operations remain abstract. Here, the claim requires executing corrective action "in real-time" but does not recite any specific technological implementation enabling real-time operation. Modern computer systems routinely perform monitoring and automated responses in real-time using conventional event-driven architectures, interrupt handling, and process scheduling. Without claim limitations specifying a novel technical approach to achieving real-time correction such as a specific scheduling algorithm, priority scheme, or system architecture the "real-time" limitation merely describes a functional requirement, not a technological innovation.
Applicant's assertion that the system "reduces computational... resource requirements" requires careful scrutiny. Reductions in computational resources can constitute improvements to computer technology when they result from novel technical approaches such as improved algorithms with lower computational complexity, optimized data structures, or efficient system architectures. However, when reduced computational usage results merely from eliminating certain operations (e.g., eliminating manual review processes), this represents a business efficiency, not a technological improvement. Here, Applicant states that automating detection and correction "reduces the need for manual review," which in turn reduces "computational... requirements." This suggests the computational savings result from eliminating manual review processes that would otherwise require computer support (user interfaces for reviewers, data presentation, manual correction entry, etc.). Reducing computational requirements by eliminating certain operations is not the same as improving how the computer performs operations that remain. The former is a business process change (deciding not to do certain tasks), while the latter is a technological improvement (doing tasks more efficiently).
The specification would need to describe how the schedule warden circuit employs a novel computational technique that reduces resource consumption compared to prior automated monitoring systems for example, through an efficient algorithm, optimized data structure, or innovative architecture. Without such description, the claimed reduction in "computational requirements" appears to result from automation of manual processes, not from technological innovation in how the computer operates.
The claim recites that the warden circuit "detects" violations and "executes" corrective actions without specifying any technological innovation in detection methods, correction mechanisms, or system architecture. This is a functional description of monitoring and control operations that computers perform routinely. The improvement described reducing manual review is a labor-saving benefit of automation, not an improvement to computer functionality. Every automated system reduces manual labor by definition; this does not make every automated system patent-eligible.
The schedule warden circuit represents using generic computer components to automate schedule monitoring and correction applying abstract ideas (rule-checking and corrective action) using conventional computing. This does not integrate the abstract idea into a practical application under Step 2A, Prong Two, and does not provide significantly more than the abstract idea under Step 2B. For the foregoing reasons, the claims remain subject to rejection under 35 U.S.C. 101 and the rejection is therefore maintained.
Claim Rejections - 35 USC 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-8, 10, 11, 14, 15, 17, 18, 21, and 22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter because the claim(s) 1-8, 10, 11, 14, 15, 17, 18, 21, and 22 as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea. The claim(s) 1-8, 10, 11, 14, 15, 17, 18, 21, and 22 is/are directed to the abstract idea of timekeeping and scheduling using user data and generated models. The claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more than the judicial exception itself. Claim(s) (1-8, 10, 11, 14, 15, 17, 18, 21, and 22) is/are directed to an abstract idea without significantly more.
Step 1
Regarding Step 1 of the Subject Matter Eligibility Test for Products and Processes (from the January 2019 101 Examination Guidelines), claim(s) (1-8, and 21) is/are directed to an apparatus, and claim(s) (10, 11, 14, 15, 17, 18, and 22) and therefore the claims recite a series of steps and, therefore the claims are viewed as falling in statutory categories.
Step 2A Prong 1
The claimed invention is directed to an abstract idea without significantly more. The claim(s) 1-8, 10, 11, 14, 15, 17, 18, 21, and 22 recite(s) a mental process that is utilized to organize human activities. Specifically, the independent claims 1, and 10 recites a mental process that provides the organizing of human activity: as drafted, the claim recites the limitation of scheduling and time sequencing of schedules which is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting a circuit nothing in the claim precludes the determining step from practically being performed in the human mind. For example, but for a circuit language, the claim encompasses the user manually performing timekeeping and scheduling based on collected information. The mere nominal recitation of a generic circuit does not take the claim limitation out of the mental processes and/or organize human activity grouping. This limitation is a mental process and/or organizing human activity. While the Guidance provides that claims do not recite a mental process and/or organizing human activity when they contain limitations that can practically be performed in the human mind, for instance when the human mind is not equipped to perform the claim limitations (GPS position calculation, network monitoring, data encryption for communication, rendering images. However with regard to the instant application the Examiner has reviewed the disclosure and determined that the underlying claimed invention is described as a concept that is performed in the human mind and/or with the aid of a pen and paper, and thus it is viewed that the applicant is merely claiming that concept performed 1) on a generic computer, 2) in a computer environment or 3) is merely using a computer as a tool to perform the concept, and therefore is considered to recite a mental process and/or organizing human activity.
Note to the Applicant per the 2019 October Guidance: The 2019 PEG sets forth a test that distills the relevant case law to aid in examination, and does not attempt to articulate each and every decision. As further explained in the 2019 PEG, the Office has shifted its approach from the case-comparison approach in determining whether a claim recites an abstract idea and instead uses enumerated groupings of abstract ideas. The enumerated groupings are firmly rooted in Supreme Court precedent as well as Federal Circuit decisions interpreting that precedent. By grouping the abstract ideas, the 2019 PEG shifts examiners’ focus from relying on individual cases to generally applying the wide body of case law spanning all technologies and claim types. In sum, the 2019 PEG synthesizes the holdings of various court decisions to facilitate examination.
Step 2A Prong 2
Specifically the determined judicial exception is not integrated into a practical application because the generically recited computer elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer and additionally that the scheduling and time sequence provisioning steps required to use the correlation do not add a meaningful limitation to the method as they are insignificant extra-solution activity (including post solution activity).
The claim recites the additional element(s): that a processor is used to perform both the determining and generating steps. The processor in both steps is recited at a high level of generality, i.e., as a generic processor performing a generic computer function of processing data (timekeeping and scheduling). This generic processor limitation is no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to the abstract idea.
The claim recites the additional element(s): interpret data, scheduling and time sequence provisioning performs the determining user embedding, and generate a model step. The interpreting and scheduling steps are recited at a high level of generality (i.e., as a general means of interpreting, scheduling, and time sequence provisioning for use in the determining and generating steps), and amounts to mere data analysis, which is a form of insignificant extra-solution activity. The circuit that performs the determining and generating steps are also recited at a high level of generality, and merely automates the determining and generating step. Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer component (the circuit).
The Examiner has further determined that the claims as a whole does not integrate a judicial exception into a practical application in order to provide an improvement in the functioning of a computer or an improvement to other technology or technical field. It has been determined that based on the disclosure does not provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. It has not been provided clearly in the disclosure that the alleged improvement would be apparent to one of ordinary skill in the art, but is instead in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art, and therefore does not improve the technology. Second, in the instance, which in this case it is not clear that the specification sets forth an improvement in technology, the claim must not reflect the disclosed improvement (the claims must include components or steps of the invention that provide the improvement described in the specification).
Note to the Applicant from the October 2019 Guidance: Generally, examiners are not expected to make a qualitative judgment on the merits of the asserted improvement. If the examiner concludes the disclosed invention does not improve technology, the burden shifts to applicant to provide persuasive arguments supported by any necessary evidence to demonstrate that one of ordinary skill in the art would understand that the disclosed invention improves technology. Any such evidence submitted under 37 C.F.R. 1.132 must establish what the specification would convey to one of ordinary skill in the art and cannot be used to supplement the specification. For example, in response to a rejection under 35 U.S.C. 101, an applicant could submit a declaration under 1.132 providing testimony on how one of ordinary skill in the art would interpret the disclosed invention as improving technology and the underlying factual basis for that conclusion.
For further clarification the Examiner points out that the claim(s) 1-20 recite(s) interpreting user data, determine user embedding, generate a model, generate time sequence, and transmitting the time sequence which are viewed as an abstract idea in the form of a mental process and/or organizing human activity. This judicial exception is not integrated into a practical application because the use of a computer for interpret, determine, generate, and transmit which is the abstract idea steps of valuing an idea (scheduling and time sequencing of schedules) in the manner of “apply it”.
Thus, the claims recite an abstract idea directed to a mental process and/or organizing human activity (i.e., to scheduling and time sequencing of schedules). Using a computer to interpreting, determine, generate, and transmit the data resulting from this kind of mental process and/or organizing human activity merely implements the abstract idea in the manner of “apply it” and does not provide 'something more' to make the claimed invention patent eligible. The claimed limitations of a computing device are not constraining the abstract idea to a particular technological environment and do not provide significantly more.
The scheduling and time sequencing of schedules would clearly be to a mental activity that a company would go through in order to decide how to perform timekeeping and scheduling. The specification makes it clear that the claimed invention is directed to the mental activity data gathering and data analysis to determine how to manage timekeeping tasks and scheduling:
The dependent claims recite elements that narrow the metes and bounds of the abstract idea but do not provide ‘something more’.
The dependent claims do not remedy these deficiencies.
Claims 17 recite limitations which further limit the claimed analysis of data.
Claims 3, 6, 7, and 18 recites limitations directed to claim language viewed insignificantly extra solution activity.
Using a computer to perform the data processing as claimed is merely implementing the abstract idea in the manner of “apply it” and does not provide significantly more. Additionally with respect to the Berkheimer the Examiner points out that the steps of the claim are viewed to be to nothing more than spell out what it means to apply it on a computer and cannot confer patent-eligibility as there are no additional limitations beyond applying an abstract idea, restricted to a computer. As the claims are merely implementing the abstract idea in the manner of “Apply It” the need for a Berkheimer analysis does not apply and is not required. With respect to the currently filed claims the implementing steps can be found in Kolodner which discloses how the claims alone and in combination are viewed to be well understood, routine and conventional based on point 3 of the Berkheimer memo and subsequent evidence, complying with and providing evidence.
Claims 2, 4, 5, 8, 11, 14, and 15 recites limitations directed to claim language viewed non-functional data labels.
Thus, the problem the claimed invention is directed to answering the question based on gathered and analyzed information about the timekeeping and scheduling. This is not a technical or technological problem but is rather in the realm of scheduling and therefore an abstract idea.
Step 2B
The claim(s) 1-8, 10-11, 14-15, 17-18, and 21-22 does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed with respect to Step 2A Prong Two, the additional element in the claim amounts to no more than mere instructions to apply the exception using a generic computer component.
The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. This is the case because in order for the claims to be viewed as significantly more the claims must incorporate the integral use of a machine to achieve performance of a method, in contrast to where the machine is merely an object on which the method operates, which does not provide significantly more in order for a machine to add significantly more, it must play a significant part in permitting the claimed method to be performed, rather than function solely as an obvious mechanism for permitting a solution to be achieved more quickly. Whether its involvement is extra-solution activity or a field-of-use, i.e., the extent to which (or how) the machine or apparatus imposes meaningful limits on the claim. Use of a machine that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not provide significantly more. Additionally, another consideration when determining whether a claim recites significantly more is whether the claim effects a transformation or reduction of a particular article to a different state or thing. "[T]ransformation and reduction of an article ‘to a different state or thing’ is the clue to patentability of a process claim that does not include particular machines. All together the above analysis shows there is not improvement in computer functionality, or improvement to any other technology or technical field. The claim is ineligible.
With respect to the Berkheimer as noted above the same analysis applies to the 2B where the claims are viewed as applying it and as such no further analysis is required. However, with respect to the claims that are viewed as extra solution or post solution activity the Examiner notes that the claims are viewed as well-understood, routine, and conventional. A citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s). An appropriate publication could include a book, manual, review article, or other source that describes the state of the art and discusses what is well-known and in common use in the relevant industry.
The dependent claims recite elements that narrow the metes and bounds of the abstract idea but do not provide ‘something more’. Specifically, the dependent claims do not remedy these deficiencies of the independent claims.
With respect to the legal concept of prima facie case being a procedural tool of patent examination, which allocates the burdens going forward between the examiner and the applicant. MPEP 2106.07 discusses the requirements of a prima facie case of ineligibility. In particular, the initial burden was on the Examiner and believed to be properly provided as to explain why the claim(s) are ineligible for patenting because of the above provided rejection which clearly and specifically points out in accordance with properly providing the requirement satisfying the initial burden of proof based on the October 2019 Guidance and the burden now shifts to the applicant.
Therefore, based on the above analysis as conducted based on the January 2019 Guidance from the United States Patent and Trademark Office the claims are viewed as a court recognized abstract idea, are viewed as a judicial exception, does not integrate the claims into a practical application, and does not provide an inventive concept, therefore the claims are ineligible.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Greenawalt (U.S. Patent Publication 2019/0114574 A1) discloses a machine learning model trained on employee workflow and scheduling data to recognize patterns associated with employee risk factors.
Westland et al. (U.S. Patent 10,572,844 B1) discloses determining employee shift schedules.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to STEPHEN S SWARTZ whose telephone number is (571)270-7789. The examiner can normally be reached Mon-Fri 9:00 - 6:00.
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, Beth Boswell can be reached at 571 272-6737. 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.
/S.S.S/Examiner, Art Unit 3625
/BETH V BOSWELL/Supervisory Patent Examiner, Art Unit 3625