DETAILED ACTION
Notice of Pre-AIA or AIA Status
[1] The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Notice to Applicant
[2] This communication is in response to the amendment filed 20 January 2026. Claims 2-3, 9-10, and 16-17 have been cancelled. Claims 1, 8, and 15 have been amended. Claims 1, 4-8, 11-15, and 18-20 are pending.
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.
[3] Previous rejection(s) of claims 1, 4-8, 11-15, and 18-20 under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter, specifically an abstract idea without significantly more has/have not been overcome by the amendments to the subject claims and is/are maintained. The revised statement of rejection presented below is necessitated by amendment and addresses the present amendments to the pending claims.
The following analysis is based on the framework for determining patent subject matter eligibility under 35 U.S.C. 101 established in the decisions of the Supreme Court in Mayo Collaborative Services v. Prometheus Labs., Incorporated and Alice Corporation Pty. Ltd. v. CLS Bank International, et al. (See MPEP 2106 subsection III and 2106.03-2106.05) the 2024 Guidance Update on Patent Subject Matter Eligibility, Including Artificial Intelligence (2024 AI SME Update) published in the Federal Register, 17 July 2024 and further clarified in the Reminders on Evaluating Subject Matter Eligibility of claims under 35 U.S.C. 101 guidance memorandum published 4 August 2025. Claim(s) 1, 4-8, 11-15, and 18-20 as a whole is/are determined to be directed to an abstract idea. The rationale for this determination is explained below:
Abstract ideas are excluded from patent eligibility based on a concern that monopolization of the basic tools of scientific and technological work might serve to impede, rather than promote, innovation. Still, inventions that integrate the building blocks of human ingenuity into something more by applying the abstract idea in a meaningful way are patent eligible (See MPEP 2106.04).
Consistent with the findings of the Supreme Court in Mayo Collaborative Services v. Prometheus Labs., Incorporated and Alice Corporation Pty. Ltd. v. CLS Bank International, et al. ineligible abstract ideas are defined in groups, namely: (1) Mathematical Concepts (e.g., mathematical relationships, mathematical formulas or equations, and mathematical calculations; (2) Mental Processes (e.g., concepts performed or performable in the human mind including observations, evaluations, judgements, or opinions); and (3) Certain Methods of Organizing Human Activity. Groupings of Certain Methods of Organizing Human Activity include three sub-categories within the group, namely: (1) fundamental economic principles or practices; (2) commercial or legal interactions (e.g., agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors, and business relations); (3) managing personal behavior or relationships or interactions between people (e.g., social activities, teaching, and following rules or instructions) (See MPEP 2106.04(a).
Eligibility Step 1: Four Categories of Statutory Subject Matter (See MPEP 2106.03): Independent claims 1, 8, and 15 are directed to a method, a system, and non-transitory computer-readable storage medium, respectively, and are reasonably understood to be properly directed to one of the four recognized statutory classes of invention designated by 35 U.S.C. 101; namely, a process or method, a machine or apparatus, an article of manufacture, or a composition of matter. While the claims, generally, are directed to recognized statutory classes of invention, each of method/process, system/apparatus claims, and computer-readable media/articles of manufacture are subject to additional analysis as defined by the Courts to determine whether the particularly claimed subject matter is patent-eligible with respect to these further requirements. In the case of the instant application, each of claims 1, 8, and 15 are determined to be directed to ineligible subject matter based on the following analysis/guidance:
Eligibility Step 2A prong 1: (See MPEP 2106.04): In reference to claim 1, the claimed invention is directed to non-statutory subject matter because the claim(s) as a whole, considering all claim elements both individually and in combination, do/does not amount to significantly more than an abstract idea. The claim(s) is/are directed to the abstract idea of generating a staffing plan including predicting a future call/contact volume and scheduling staff members based on the predicted future contact volume, which is reasonably considered to be method of Organizing Human Activity. In particular, the general subject matter to which the claims are directed applies mathematical models to predict future contact volumes and aligns of schedules staff based on the predictions, which is an ineligible concept of Organizing Human Activity namely: managing personal behavior or relationships or interactions between people (e.g., aligning agent work and availability schedules with contact requests).
In support of Examiner’s conclusion, Examiner respectfully directs Applicant’s attention to the claim limitations of representative claim 1. In particular, claim 1 as presented by amendment includes:
“…providing input data…wherein the input data includes the predicted contact volume of the call type for the future time period, the predicted contact duration of the call type for the future time period, a number of available staff members and a number of available contact time units of each of the number of available staff members, wherein the input data further includes staff skills and queue assignment capabilities of the available staff members; and computing…hour-by-hour queue-level staffing plan, wherein the hour-by-hour queue-level staffing plan minimizes a difference between a total number of predicted customer contact time units and a total number of staff member contact time units for the future time period…”
Considered as an ordered combination, the steps/functions of claim 1 are reasonably considered to be representative of the inventive concept and are further reasonably understood to be series of actions or activities directed to a general process of generating a staffing plan including predicting a future call/contact volume and scheduling staff members based on the predicted future contact volume, which is an ineligible concept of Organizing Human Activity namely: managing personal behavior or relationships or interactions between people (e.g., aligning agent work and availability schedules with contact requests) (See MPEP 2106.04(a)(2)).
Further limitations are directed to ineligible Mathematical Concepts (e.g., mathematical relationships, mathematical formulas or equations, and mathematical calculations) and processes/functions which are performable by Human Mental Processing and/or or by a human using pen and paper (See CyberSource Corp v. Retail Decisions, Inc., 654 F.3d 1366, 1373 (Fed. Cir. 2011).
The courts have previously identified subject matter limited to the implementation of Mathematical Concepts as ineligible abstract ideas (See at least Gottschalk v. Benson, 409 U.S. 63, 65, 175 USPQ2d 673, 674 (1972); and Parker v. Flook, 437 U.S. 584, 588-89, 198 USPQ2d 193, 195 (1978)). Further, the courts consider steps/processes performable by Human Mental Processing and/or by a human using pen and paper to be ineligible abstract ideas (See CyberSource Corp v. Retail Decisions, Inc., 654 F.3d 1366, 1373 (Fed. Cir. 2011). Lastly, if a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for a recitation of generic computer components, then the claim is still to be grouped as a mental process unless the limitation cannot practically be performed in the human mind (See MPEP 2106.04(a)(2)).
With respect to functions/steps limited to Mathematical Concepts, representative claim 1, as presented by amendment, recites:
“…by finding argminp,m ∑vd-pm, wherein the variable v is the predicted contact volume of the call type for the future time for an hour of the future time period, wherein the variable d is the predicted contact duration of the call type for the future time period for the hour, wherein the variable p is a binary valued vector indicating if a staff member of the number of available staff members is available at the hour, wherein the value m is the number of available contact time units the staff member is available for in the future time period as expected contact time minutes at the hour, wherein the total number of predicted customer contact time units and the total number of staff member contact time units are measured in minutes, wherein the computing of the hour-by-hour queue-level staffing plan is performed, for each contact queue and for each hour, by executing a mixed integer linear programming solver subject to constraints on a limit of scheduled staff and a sum of expected minutes, including ∑p≤P and ∑m≤S, and further constrained such that staff are assigned only to contact queues recorded as having required skills and training…”
With respect to functions/steps performable by human mental processing and/or by a human using pen and paper, representative claim 1 as presented by amendment recites:
“…predicting…a predicted contact volume and a predicted contact duration of customer contacts with a contact center for a future time period for each hour of the future time period…”, “…automatically detecting anomalous patterns in the predicted contact volume and predicted contact duration…and adjusting the predictions based on detected anomalies…computing…a hour-by-hour queue-level staffing plan, wherein the hour-by-hour queue-level staffing plan minimizes a difference between a total number of predicted customer contact time units and a total number of staff member contact time units for the future time period…”
Respectfully, absent further clarification of the processing steps executed by the recited machine learning model and/or applications and processors, one of ordinary skill in the art would readily understand that predicting a future business metrics, such as customer or call volume, by observing patterns in contact volume and using provided mathematical models and determining staff allocations to meet the predicted volume are practicable/performable by a human using pen and paper and employing by the human mental processing (See CyberSource Corp v. Retail Decisions, Inc., 654 F.3d 1366, 1373 (Fed. Cir. 2011) (“a method that can be performed by human thought alone is merely an abstract idea and is not patent eligible under 35 U.S.C 101).
Claims 1, 8, and 15 include technical elements and recited functions that constitute technical features which have been considered at each step of Examiner’s analysis but are determined to constitute generic computing structures executing generic computing functions previously identified by the courts, as further analyzed under Step 2A prong 2 and Step 2B below.
Eligibility Step 2A prong 2: (See MPEP 2106.04(d)): Under step 2A prong two, Examiners are to consider additional elements recited in the claim beyond the judicial exception and evaluate whether those additional elements integrate the exception into a practical application. Further, to be considered a recitation of an element which integrates the judicial exception into a practical application, the additional elements must apply, rely on, or use the judicial exception in a manner that imposes meaningful limits on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception.
As presented by amendment, the claims retain the technical elements including “a machine learning model”, “a planning application”, “computing system”, and “queue management software” (claims 1, 8, and 15) and “a computer including a processor” and “computer-executable instructions” (claims 8 and 15). Claims 1, 8, and 15 further include “…training a regression machine learning model with observed historical contact data comprising data name, a call type, a description, and moving average data…”. Claims 1, 8, and 15 further include a “statistical anomaly detection module” and a “distributed computing environment”. With respect to these potential additional elements and as presented by amendment:
(1) The “computer”, “processor”, “planning application”, and “instructions” are identified as engaged in an unspecified, general manner in the performance of each of the recited steps/functions.
(2) As presented by amendment, the “computing system” is identified as “receiving…observed historical contact data from a plurality of disparate data sources, the observed historical contact data comprising a data name, a call type, a description, and moving average data, wherein the observed historical contact data is pre-processed to normalize time intervals and remove outliers” and “the computing system provides, as output, the hour-by-hour queue-level staffing plan for the contact center's contact queues that is not generated manually or with conventional rule-based systems, and provides the computed hour-by-hour, queue-level staffing plan to contact queue management software in a contact management center for scheduling....”
(3) The “statistical anomaly detection module” is identified as being used to “automatically detecting anomalous patterns in the predicted contact volume and predicted contact duration”
(4) The “distributed computing environment” is identified as being the computing environment on which the planning application executes.
(5) The “machine learning model” is identified as being trained with observed historical contact data comprising data name, a call type, a description, and moving average data.
With respect to the above noted functions attributable to the identified additional elements, MPEP 2106.05 stipulates that: Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea – see MPEP 2106.05(f); and/or Generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h) serve as indications that the use of the technology recited does not indicate integration into a practical application of the judicial exception.
The amendments to specify “…the computing system provides, as output, the hour-by-hour queue-level staffing plan for the contact center's contact queues that is not generated manually or with conventional rule-based systems, and provides the computed hour-by-hour, queue-level staffing plan to contact queue management software in a contact management center for scheduling....”, provide further clarity with respect to the granularity of the staffing plan to specify hourly planning at the queue level. However, the recitations do not alter or otherwise modify the primary directive of the claimed inventio, which is to generating a staffing plan including predicting a future call/contact volume and scheduling staff members based on the predicted future contact volume. The claimed queue management software, absent further clarification is reasonably understood to constitute a generic computing element which serves to add an additional generic computing function of storing the computed staffing plan in a queue format.
With respect the recitation of the “statistical anomaly detection module” and a “distributed computing environment”, while these recitations identify additional technical elements that are engaged in the performance of the recited steps/analysis at a high level of generality, and further identify a generically recited distributed environment on which the application executes, the limitations fail to provide no further clarification with respect to the functions performed by the “statistical anomaly detection module” and a “distributed computing environment”. The identified functions performed by the recited “statistical anomaly detection module” and a “distributed computing environment” are limited to: (1) receiving and sending data via a computer network (e.g., input data); (2) storing and retrieving information and data from a generic computer memory (e.g., model, data, and queue structured staffing plan); and (3) performing repetitive calculations and/or mental observations using the obtaining information/data (e.g., detecting anomalous patterns).
With respect to the identification of the “machine learning model”, Examiner notes the 2024 Guidance Update on Patent Subject Matter Eligibility, Including Artificial Intelligence (2024 AI SME Update) published in the Federal Register on 17 July 2024. In particular, Examiner respectfully directs Applicant’s attention to Example 47, claim 2. Specifically, the instant recitations of “using a machine learning model” and “training the machine learning model” are analogous to the training of an artificial neural network based on input data and receiving continuous training data of Examiner 47. Reasonably, the training data and feedback data are limited to mere data gathering and generating an output at a high level of generality and, by extension, are reasonably understood to constitute insignificant extra solution activity (See MPEP 2106.05(g)). The recited training process is limited to a recitation of the inputs and outputs to be applied to an undefined training process absent any technical specificity regarding actual training. Accordingly, the recited machine-learning processes and associated training are reasonably understood to constitute generic, commercially available machine learning models as the claims fail to specify any technical steps in obtaining the results other than to state that the model is trained and utilized to receive inputs and generate outputs.
Each of the above noted limitations states a result (e.g., input is provided, contact volume is predicted, a staffing plan is determined etc.) as associated with a respective “computer” or “planning application”. Beyond the general indication that the recited application and model are engaging in the process in an unspecified manner, the limitations provide no further clarification with respect to the functions performed by the “processor/executable instructions” and “planning application” in producing the claimed result. A recitation of “by a processor” or “by an application”, absent clarification of particular processing steps executed by the underlying technology. The identified functions performed by the recited technology are limited to: (1) receiving and sending data via a computer network (e.g., input data); (2) storing and retrieving information and data from a generic computer memory (e.g., model, data, and queue structured staffing plan); and (3) performing repetitive calculations and/or mental observations using the obtaining information/data (e.g., detecting anomalous patterns) (See MPEP 2106.05(f)).
Accordingly, claim 1 is reasonably understood to be conducting standard, and formally manually performed process of generating a staffing plan including predicting a future call/contact volume and scheduling staff members based on the predicted future contact volume using the generic devices as tools to perform the abstract idea. The identified functions of the recited additional elements reasonably constitute a general linking of the abstract idea to a generic technological environment. The claimed generating a staffing plan including predicting a future call/contact volume and scheduling staff members based on the predicted future contact volume benefits from the inherent efficiencies gained by data transmission, data storage, and information display capacities of generic computing devices, but fails to present an additional element(s) which practical integrates the judicial exception into a practical application of the judicial exception.
Eligibility Step 2B: (See MPEP 2106.05): Analysis under step 2B is further subject to the Revised Examination Procedure responsive to the Subject Matter Eligibility Decision in Berkheimer v. HP, Inc. issued by the United States Patent and Trademark Office (19 April 2018). Examiner respectfully submits that the recited uses of the underlying computer technology constitute well-known, routine, and conventional uses of generic computers operating in a network environment. In support of Examiner’s conclusion that the recited functions/role of the computer as presented in the present form of the claims constitutes known and conventional uses of generic computing technology, Examiner provides the following:
In reference to the Specification as originally filed, Examiner notes paragraphs [0056]-[0070]. In the noted disclosure, the Specification provides listings of generic computing systems, e.g., a general computing platform including exemplary servers, network configurations and various processor configuration which are identified as capable and interchangeable for performing the disclosed processes. The disclosure does not identify any particular modifications to the underlying hardware elements required to perform the inventive methods and functions. Accordingly, it is reasonably understood that this disclosure indicates that the hardware elements and network configurations suitable for performing the inventive methods are limited to commercially available systems at the time of the invention. Absent further clarification, it is reasonably understood that any modifications/improvements to the underlying technology attributable to the inventive method/system are limited to improvements realized by the disclosed computer-executable routines and the associated processes performed.
While the above noted disclosure serves to provide sufficient explanation of technical elements required to perform the inventive method using available computing technology, the disclosure does not appear to identify any particular modifications or inventive configurations of the underlying hardware elements required to perform the inventive methods and functions. Accordingly, it is reasonably understood that the disclosure indicates that the hardware elements and network configurations suitable for performing the inventive methods are limited to commercially available systems at the time of the invention. Further, absent further clarification, it is reasonably understood that any modifications/improvements to the underlying technology attributable to the inventive method/system are limited to improvements realized by the disclosed computer-executable routines and the associated processes performed.
As presented by amendment, the claims retain the technical elements including “a machine learning model”, “a planning application”, “computing system”, and “queue management software” (claims 1, 8, and 15) and “a computer including a processor” and “computer-executable instructions” (claims 8 and 15). Claims 1, 8, and 15 further include “…training a regression machine learning model with observed historical contact data comprising data name, a call type, a description, and moving average data…”. Claims 1, 8, and 15 further include a “statistical anomaly detection module” and a “distributed computing environment”. With respect to these potential additional elements and as presented by amendment:
(1) The “computer”, “processor”, “planning application”, and “instructions” are identified as engaged in an unspecified, general manner in the performance of each of the recited steps/functions.
(2) As presented by amendment, the “computing system” is identified as “receiving…observed historical contact data from a plurality of disparate data sources, the observed historical contact data comprising a data name, a call type, a description, and moving average data, wherein the observed historical contact data is pre-processed to normalize time intervals and remove outliers” and “the computing system provides, as output, the hour-by-hour queue-level staffing plan for the contact center's contact queues that is not generated manually or with conventional rule-based systems, and provides the computed hour-by-hour, queue-level staffing plan to contact queue management software in a contact management center for scheduling....”
(3) The “statistical anomaly detection module” is identified as being used to “automatically detecting anomalous patterns in the predicted contact volume and predicted contact duration”
(4) The “distributed computing environment” is identified as being the computing environment on which the planning application executes.
(5) The “machine learning model” is identified as being trained with observed historical contact data comprising data name, a call type, a description, and moving average data.
While Examiner acknowledges that the noted limitations are computer-implemented, Examiner respectfully submits that, in aggregate (e.g., “as a whole”) they do not amount to significantly more than the abstract idea/ineligible subject matter to which the claimed invention is primarily directed.
While utilizing a computer, the claimed invention is not rooted in computer technology nor does it improve the performance of the underlying computer technology. The computer-implemented features of the claimed invention noted above are reasonably limited to: (1) receiving and sending data via a computer network (e.g., input data); (2) storing and retrieving information and data from a generic computer memory (e.g., model, data, and queue structured staffing plan); and (3) performing repetitive calculations and/or mental observations using the obtaining information/data (e.g., detecting anomalous patterns). The above listed computer-implemented functions are distinguished from the generic data storage, retrieval, transmission, and data manipulation/processing capacities of the generic systems identified in the Specification solely by the recited identification of particular data elements that are of utility to a user performing the specific method of generating a staffing plan including predicting a future call/contact volume and scheduling staff members based on the predicted future contact volume. In summary, the computer of the instant invention is facilitating non-technical aims, i.e., generating a staffing plan, because it has been programmed to store, retrieve, and transmit specific data elements and/or instructions that is/are of utility to the user. The non-technical functions of generating a staffing plan including predicting a future call/contact volume and scheduling staff members based on the predicted future contact volume benefit from the use of computer technology, but fail to improve the underlying technology.
In support, the courts have previously found that utilization of a computer to receive or transmit data and communications over a network and/or employing generic computer memory and processor capacities store and retrieve information from a computer memory are insufficient computer-implemented functions to establish that an otherwise unpatentable judicial exception (e.g. abstract idea) is patent eligible. With respect to the determinations of the Courts regarding using a computer for sending and receiving data or information over a computer network and storing and retrieving information from computer memory, see at least: receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362; sending messages over a network OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); receiving and sending information over a network buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); storing and retrieving information in memory, 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 1092-93 and see performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199; and Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) with respect to the performance of repetitive calculations does not impose meaningful limits on the scope of the claims.
Independent claims 8 and 15, directed to an apparatus/system and computer-executable instructions stored on computer-readable media for performing the method steps are rejected for substantially the same reasons, in that the generically recited computer components in the apparatus/system and computer readable media claims add nothing of substance to the underlying abstract idea.
Dependent claims 4-7, 11-14, and 18-20, when analyzed as a whole are held to be ineligible subject matter and are rejected under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claimed invention is not directed to an abstract idea.
In accordance with all relevant considerations and aligned with previous findings of the courts, the technical elements imparted on the method that would potentially provide a basis for meeting a “significantly more” threshold for establishing patent eligibility for an otherwise abstract concept by the use of computer technology fail to amount to significantly more than the abstract idea itself. For further guidance and authority, see Alice Corporation Pty. Ltd. v. CLS Bank International, et al. 573 U.S.____ (2014)) (See MPEP 2106).
Subject Matter Overcoming Art of Record
[4] Claims 1, 4-8, 11-15, and 18-20 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action.
The most closely applicable prior art of record is referred to in the Office Action mailed 19 December 2024 as D’Attilio et al. (United States Patent Application Publication No. 2022/0027837). D’Attilio provides system and method which utilizes AI modelling to facilitate agent scheduling. The system and method include using time series data to train model to provide staffing requirements based on a predicted call/contact volume
While D’Attilio is similar to the instant application in many respects, there are clear patentable distinctions. While D’Attilio predicts call volume and correlates the call volume to a staffing requirement for future time periods, the predictions of staff requirements do not include a predictions of call volumes and particular a forecasted call duration for a specified, or subgroup of call types as required by each of claims 1, 8, and 15.
Response to Remarks/Amendment
[5] Applicant's remarks filed 20 January 2026 have been fully considered and are addressed as follows:
[i] Applicant’s remarks in response to previous rejection(s) of claim(s) 1, 4-8, 11-15, and 18-20 under 35 U.S.C. 101 as being directed to non-statutory subject matter as set forth in the previous Office Action mailed 22 October 2026 are reasonably considered to have been fully addressed in the context of the revised rejection of the claims presented above responsive to the amendments to the subject claims and in consideration of the framework for determining patent subject matter eligibility under 35 U.S.C. 101 established in the decisions of the Supreme Court in Mayo Collaborative Services v. Prometheus Labs., Incorporated and Alice Corporation Pty. Ltd. v. CLS Bank International, et al. (See MPEP 2106 subsection III and 2106.03-2106.05) and the 2024 Guidance Update on Patent Subject Matter Eligibility, Including Artificial Intelligence (2024 AI SME Update), published in the Federal Register, 17 July 2024. Additionally, Applicant substantially rehashes arguments previously presented in the prior response. These arguments are addressed in accordance with Examiner’s response in the prior Office Action(s) mailed 22 October 2026 and 2 July 2025, incorporated in their entirety in response.
Conclusion
[6] The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Cited PATENT Literature:
Li et al., Accurate Individual Queue Level Metric Forecasting For Virtual Contact Center Queues With Insufficient Data, Using Models Trained At Higher Granularity Level, United States Patent No. 12,073,340, column(s) 2-3 : Relevant Teachings: Li discloses a system/method that provides for the generation of contact volume forecasts. The system/method employ AI/ML models to provide forecasts for different time horizons in a queue form.
Stepanov et al., METHOD, APPARATUS, AND COMPUTER-READABLE MEDIUM FOR MANAGING CONCURRENT COMMUNICATIONS IN A NETWORKED CALL CENTER, United States Patent Application Publication No. 2021/0266405, paragraphs [0103]-[0104]: Relevant Teachings: Stepanov discloses a system/method that includes steps/functions including forecasting call volumes and derivative projected queue positions.
Kosiba et al., System And Method For Generating Forecasts And Analysis Of Contact Center Behavior For Planning Purposes, United States Patent Application Publication No. 2002/0184069, paragraphs [0054]-[0055]: Relevant Teachings: Kosiba discloses a system/method that includes steps/functions of forecasting call center call volumes and provides scheduling on an hourly level.
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.
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/ROBERT D RINES/Primary Examiner, Art Unit 3625
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