DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Application
This communication is a Final Office Action in response to communications received April 30, 2026. Claims 1, 3-5, 8, 10-12, 15, and 17-19 were amended. Claims 1-20 are currently pending.
Response to Arguments
Applicant’s arguments with regards to the 101 rejections have been fully considered, but they are not persuasive.
Applicant argues that the pending claims are not directed to an abstract idea because they integrate the exception into a practical application by improving technology and the functioning of a computer - specifically through better matching of support requests with support agents based on varying the selection of corresponding models relative to surpluses in agent queues and/or requestor queues.
Examiner respectfully disagrees. The claim recites limitations that reasonably fall within the abstract idea grouping of certain method of organizing human activity, including the feature argued by applicant above. The recited limitations of the independent claims, as outlined below, involve intaking customer requests, comparing the available support agents for the request, and assigning or selecting agents to handle the calls. This is business or commercial interactions, as well as managing personal behavior and following rules or instructions.
With regard to step 2A prong 2 and the claim integrating the recited abstract idea into a practical application, it is noted the additional elements in the independent claims are one or more processors, a non-transitory computer-readable medium, receiving match requests, and establishing a communication session. These additional elements, when considering the claim as a whole and these additional elements, alone and in combination, amount to generic computer-components recited at a high level of generality and amount to nothing more than instructions to apply and implement the abstract idea.
The arguments reference certain court decisions, however in these decisions the specifications explained improvements to technology or computers, and these improvements were reflected in the claim language. Here, the maintaining of the requestor and support agent models, monitoring of queues, receiving requests to pair agents and requestors, considering and identifying queues with surplus all fall within the recited abstract idea. Thus, the instant claims differ from these court decisions.
Applicant’s arguments with respect to the 35 U.S.C. 102 rejection of claims 1-20 have been considered but are moot because the new ground of rejections set forth below, necessitated by amendment. The current rejection does not rely on any reference applied in the prior rejection.
Claim Objections
Claims 5, 12, and 19 are objected to because of the following informalities: These claims recite a “set of requestor models includes request model that has been generated.” It appears a word is missing and the limitation should read set of requestor models includes a request model that has been generated. Appropriate correction is requested.
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 1-20 are rejected under 35 U.S.C. 101 because the claims are directed to a judicial exception, in this case the exception is an abstract idea (see MPEP 2016.03), without significantly more.
Independent Claims 1, 8 and 15
Step 2A – Prong One:
The limitations of these claims recite the following:
maintain a set of requestor models
maintain a set of support agent models
monitor a state of a first queue that includes a plurality of support requests, wherein monitoring the state of the first queue includes determining a first quantity of support requests in the first queue;
monitor a state of a second queue that indicates a plurality of available support agents, wherein monitoring the state of the second queue includes determining a second quantity of available support agents in the second queue;
receive a request to pair a particular support request, of the plurality of support requests, with a support agent, wherein the particular support request is received from a particular requestor;
compare the first quantity of support requests, in the first queue, to the second quantity of available support agents in the second queue;
identify, based on the comparing, whether the first queue is associated with a surplus with respect to the second queue or whether the second queue is associated with a surplus with respect to the first queue;
when identifying a surplus for the first queue with respect to the second queue:
select, from the set of support agent models, a first support agent model for one or more support agents of the plurality of support agents; and
select, from the set of requestor models, a particular first requestor model for the particular support request;
when identifying a surplus for the second queue with respect to the first queue:
select, from the set of support agent models, a second support agent model for one or more support agents of the plurality of support agents; and
select, from the set of requestor models, a second requestor model for the particular support request;
select, based on the selected first or second requestor model and the selected first or second support agent model, a particular support agent of the plurality of support agents.
These limitations recite an abstract idea, specifically a certain method of organizing human activity such as business or commercial interactions, managing personal behavior and following rules or instructions, because the recited claim limitations are responsibilities and functions that are normally executed by a call center manager to improve the handling of customer requests. Call centers or any customer service intakes customer request, compares the available support agents for the request, and assigns or selects an agent to handle the call, and the steps of the claims involve organizing human activity, the claim recites an abstract idea consistent with the “certain methods of organizing human activity” grouping set forth in the see MPEP 2106.04(a)(2)(II).
Therefore, claims 1, 8 and 15 recite an abstract idea.
Step 2A – Prong Two:
The scope of the independent claim limitations incorporates the following additional elements:
one or more processors
a non-transitory computer-readable medium
receive a request to match a support request with a support agent
establish a communication session between a support agent and a requestor.
These additional elements listed above, or combination of these elements, amount to nothing more than simply reciting the abstract idea to improve the handling of customer requests while adding the words ‘apply it’, MPEP 2106.05(f). The system elements, including one or more processors and a non-transitory computer-readable medium, to implement the abstract idea amount to components of a general-purpose computer. Further, additional elements that recite generic computer-implemented steps such as receiving a support request or establishing a communication session, are recited at a high level of generality amount to nothing more than instructions to apply the abstract idea without any improvement to technology, technical field, or to the functioning of the computer itself.
Therefore, the additional elements, whether evaluated individually or in combination, fail to integrate the recited abstract idea into a practical application.
The claimed invention is directed to an abstract idea.
Step 2B
Under Step 2B of the patent eligibility analysis, the combination of additional elements is evaluated to determine whether they amount to something “significantly more” than the recited abstract idea to improve the handling of customer requests. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply the exception using a general-purpose computer and/or its components. Mere instructions to apply an exception using a general-purpose computer and/or its components cannot provide an inventive concept.
Claims 1, 8 and 15 are not patent eligible.
Dependent Claims –
Claims 2, 9 and 16 further recite the central theme of the abstract idea to generate or refine models, which is a certain method of organizing human activity, specifically following rules to manage business interactions between the customer and the service agent. Additionally, the claim limitations recite the additional element of using artificial intelligence/machine learning techniques. This additional element recites only the idea of a solution and fails to recite details of how a solution to a problem is accomplished. Therefore, the claim limitations do not integrate the judicial exception into a practical application because this type of recitation is the equivalent to the words “apply it”.
Claims 3, 10 and 17 further recite the central theme of the abstract idea to maintain affinity between models, which is a certain method of organizing human activity, specifically following rules to manage business interactions between the customer and the service agent. The claim limitation is further directed to the abstract idea, a mental process, without significantly more.
Claims 4, 11 and 18 recite data elements, specifically the intended result that the communication session includes a voice call. The recitation of maintaining the state of data in an online form without restriction on how the state is maintained and with no description of the mechanism for maintaining the state describes "the effect or result dissociated from any method by which maintaining the state is accomplished" and does not provide a meaningful limitation because it merely states that the abstract idea should be applied to achieve a desired result.
Claims 5, 12 and 19 further recite the central theme of the abstract idea to generate or refine models based on the interaction between requestors and support agents, which is a certain method of organizing human activity, specifically following rules to manage business interactions between the customer and the service agent. The claim limitation is further directed to the abstract idea, a mental process, without significantly more.
Claims 6, 13 and 20 recite data elements, specifically the intended result that the data fields including the priority of support requests in the queue of requestors. The recitation of maintaining the state of data in an online form without restriction on how the state is maintained and with no description of the mechanism for maintaining the state describes "the effect or result dissociated from any method by which maintaining the state is accomplished" and does not provide a meaningful limitation because it merely states that the abstract idea should be applied to achieve a desired result.
Claims 7 and 14 recite the intended result that the requestor models and the agent models are generated or refined based on simulated interactions between requestors and support agents. The recitation of maintaining the state of data in an online form without restriction on how the state is maintained and with no description of the mechanism for maintaining the state describes "the effect or result dissociated from any method by which maintaining the state is accomplished" and does not provide a meaningful limitation because it merely states that the abstract idea should be applied to achieve a desired result.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-2, 4-6, 8-9, 11-13, 15-16, 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Flockhart (US 8,234,141) in view of Konig et al. (US 2017/0316438).
As per claims 1, 8 and 15, Flockhart teaches a device comprising:
one or more processors (See figure 1, column 12, lines 5-11, also disclosing a computer readable medium. See also figure 1) configured to:
maintain a set of requestor representative data sets (See column 6, lines 5-10, column 8, lines 10-32, column 11, lines 20-40, wherein qualifiers and profile items are stored and maintained for contacts/customer requesting support);
maintain a set of support agent representative data sets (See column 3, lines 50-57, column 6, lines 10-20, column 8, lines 10-32, wherein representative attributes associated with agent(s) is/are stored and updated);
monitor a state of a first queue that includes a plurality of support requests, wherein monitoring the state of the first queue includes determining a first quantity of support requests in the first queue (See figure 2, column 5, line 55-colun 6, line 4, with customer incoming contacts represented in a work item queue);
monitor a state of a second queue that indicates a plurality of available support agents, wherein monitoring the state of the second queue includes determining a second quantity of available support agents in the second queue (See figure 2, column 5, line 55-colun 6, line 4, with agents represented in a queue based on their skill and availability);
receive a request to pair a particular support request, of the plurality of support requests, with a support agent, wherein the particular support request is received from a particular requestor (See column 9, line 53-column 10, line 3 and lines 6-7, where a contact/ work item arrives at the head of the queue and needs to be paired with a support agent. See also figure 4);
compare the first quantity of support requests, in the first queue, to the second quantity of available support agents in the second queue (See figure 2, column 6, lines 5-20, column 7, lines 50-60, where work items are assigned to different work item queues, and from these queues the work items are assigned to agents in agent queues. Goals, volumes and surpluses are considered when looking at the queues);
identify, based on the comparing, whether the first queue is associated with a surplus with respect to the second queue or whether the second queue is associated with a surplus with respect to the first queue (See column 7, lines 50-60, column 8, lines 62-67, column 9, lines 22-27, and column 10, line 60-column 11, line 2, where volumes, surpluses and shortages are considered);
when identifying a surplus for the first queue with respect to the second queue (Paragraphs 13 and 24 of instant specification, fewer agents are available than are needed to handle all support requests in one or more queues):
select, from the set of support agent data sets, a first support agent data set for one or more support agents of the plurality of support agents and select, from the set of requestor data sets, a particular first requestor data set associated with for the particular support request (See column 9, lines 22-27, column 10, line 60-column 11, line 2, when there is a high volume of work the system selects an agent that is faster compared to their peers – as opposed to one that is the most effective. See column 8, lines 62-66, where the selection is dynamic based on the changing conditions at the contact center );
when identifying a surplus for the second queue with respect to the first queue (Paragraphs 13 and 24 of instant specification, more agents are available than are needed to handle all support requests in one or more queues):
select, from the set of support agent data sets, a second support agent data set for one or more support agents of the plurality of support agents; and select, from the set of requestor data sets, a second requestor data set for the particular support request (See column 9, lines 22-27, column 10, line 60-column 11, line 2, where when there is a surplus of available agents, the agent skill having the highest metric for efficiency is selected. See column 8, lines 62-66, where the selection is dynamic based on the changing conditions at the contact center);
select, based on the selected first or second requestor data and the selected first or second support agent data, a particular support agent of the plurality of support agents (See figure 4, column 9, lines 53-67, column 10, lines 24-26 and line 60-column 11, line 6, wherein a work item and an agent are selected to be paired); and
establish a communication session between the selected particular support agent and the particular requestor (See figure 4, column 7, lines 26-31, column 11, lines 5-6, where communication sessions are established).
While Flockhart discloses data sets representative of requestors and support agents that are used to pair agents and requestors, Flockhart does not explicitly disclose that these representative data sets are models.
In a call center environment, Konig et al. discloses maintaining a set of requestor models (See at least 0056, 0059, 0061-62, 0074, 0081-3, 0100) and maintaining a set of support agent models (See at least 0056, 0061-62, 0068, 0081-3, 0100), selecting a requestor model or a support agent model from a set of requestor models or a set of agent models (See at least 0059, 0063, 0088, which discuss individual models for customers and agents), and selecting an agent using these models (See at least paragraphs 0063, 0112, and 0120, where an agent to best handle the issue is identified).
Both Flockhart and Konig et al. are focused on connecting contacts and agents in call center environments. Flockhart specifically discloses generators that maintain and update data representing requestors (contacts) and agents, which are used to select and connect agents with contacts. Konig et al. specifically aggregates this data into agent and customer models that are used to make predictions about the customer and agent. It would have been obvious before the effective filing date of the invention to include the customer and agent models Konig et al. in the updating of data representations of the requestor and agent of Flockhart in order to better tailor interactions and allocate resources based on the predictions, thereby improving overall performance, including improving the customer experience. See Konig et al., paragraph 0056, and Flockhart, column 8, lines 10-35.
Regarding Claims 2, 9 and 16, Flockhart teaches a profile generator and maintaining and updating data representing requestors and agents (See at least column 8, lines 10-35). Flockhart does not specifically disclose generating or refining the set of requestor models and the set of support agent models using artificial intelligence/machine learning ("AI/ML") techniques.
Konig et al. teaches generating or refining the set of requestor models and the set of support agent models using artificial intelligence/machine learning ("AI/ML") techniques (See at least paragraphs 0011, 0058, 0067, 076, 0082, 0087, wherein using the customer (requestor) models and the agent models involves machine learning and training or predicting a feature of the model).
Both Flockhart and Konig et al. are focused on connecting contacts and agents in call center environments. Flockhart specifically discloses generators that maintain and update data representing requestors (contacts) and agents, which are used to select and connect agents with contacts. Konig et al. specifically aggregates this data into agent and customer models that are used to make predictions about the customer and agent. It would have been obvious before the effective filing date of the invention to include the machine learning on customer and agent models Konig et al. in the updating of data representations of the requestor and agent of Flockhart in order to better tailor interactions and allocate resources based on the predictions, thereby improving overall performance, including improving the customer experience. See Konig et al., paragraph 0056, and Flockhart, column 8, lines 10-35.
Regarding Claims 4, 11 and 18, Flockhart et al. teaches wherein the communication session between the selected particular support agent and the particular requestor includes a voice call (See column 3, lines 34-37).
Regarding Claims 5, 12 and 19, Flockhart teaches wherein the set of requestor data includes a requestor data that has been generated or refined based on interactions between a plurality of requestors and one or more support agents of the plurality of support agents (See column 7, lines 30-33, column 8, lines 10-35, column 11, lines 19-40, where data is stored and updated including previous history with the enterprise).
While Flockhart discloses data sets representative of requestors and support agents that are used to pair agents and requestors, Flockhart does not explicitly disclose that these representative data sets are models.
In a call center environment, Konig et al. discloses requestor models and support agent models (See at least 0056, 0059, 0061-62, 0068, 0074, 0081-3, 0100) and where the requestor model is generated or refined based on interactions between a plurality of requestor and one or mor support agents (See at least paragraphs 0056, 0068, 0081).
Both Flockhart and Konig et al. are focused on connecting contacts and agents in call center environments. Flockhart specifically discloses generators that maintain and update data representing requestors (contacts) and agents, which are used to select and connect agents with contacts. Konig et al. specifically aggregates this data into agent and customer models that are used to make predictions about the customer and agent, and continuously updates this data after interaction. It would have been obvious before the effective filing date of the invention to include the customer and agent models Konig et al. in the updating of data representations of the requestor and agent of Flockhart, and continuously updating these models, in order to better tailor interactions and allocate resources based on the predictions, thereby improving overall performance, including improving the customer experience. See Konig et al., paragraphs 0056 and 0081, and Flockhart, column 8, lines 10-35.
Regarding Claims 6, 13 and 20, Flockhart teaches wherein the particular support request is a first support request, wherein the queue includes a particular sequence of requests, wherein the first support request is later in the particular sequence than a second support request, wherein the communication session is established between the selected particular support agent and the particular requestor prior to a selection procedure to select a support agent for the second support request (See column 5, line 55-column 6, line 6, and column 11, line 10-45, where queues are sequences of work and where different qualifiers can pull work from the queue, such as being a ‘gold customer’ or in a multi-skilled agent scenario. See also column 10, lines 53-63).
Claims 3, 10 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Flockhart (US 8,234,141) in view of Konig et al. (US 2017/0316438) and in further view of Chishti (US 2010/0111285).
Regarding claims 3, 10 and 17, Flockhart discloses the one or more processors are further configured to maintain measures of satisfaction between respective requestor and support agent data sets, wherein selecting the particular support agent is further based on a particular measure of satisfaction (See column 7, line 59-colun 8, line 5 and lines 33-55).
While Flockhart discloses data sets representative of requestors and support agents that are used to pair agents and requestors, Flockhart does not explicitly disclose that these representative data sets are models.
In a call center environment, Konig et al. discloses requestor models and support agent models (See at least 0056, 0059, 0061-62, 0068, 0074, 0081-3, 0100).
Both Flockhart and Konig et al. are focused on connecting contacts and agents in call center environments. Flockhart specifically discloses data representing requestors (contacts) and agents, which are used to select and connect agents with contacts. Konig et al. specifically aggregates this data into agent and customer models that are used to make predictions about the customer and agent. It would have been obvious before the effective filing date of the invention to include the customer and agent models Konig et al. in the updating of data representations of Flockhart in order to better tailor interactions and allocate resources based on the predictions, thereby improving overall performance, including improving the customer experience. See Konig et al., paragraph 0056, and Flockhart, column 8, lines 10-35.
Further, while Flockhart and Konig et al. discuss customer satisfaction data (Flockhart, column 3, lines 50-57, column 8, lines 1-3 and 33-45; Konig, paragraphs 0061, 0074, 0085, 0112), they do not expressly disclose affinity. Chishti discloses affinity data matching and maintaining measures of affinity between respective requestor models and support agent models, wherein selecting the particular support agent is further based on a particular measure of affinity between the first or second support agent model and the first or second requestor model (See at least paragraphs 30, 36, 43, 64-8 where caller and agent affinity data is collected and stored as representative characteristics that are used when later matching callers and requestors).
All of Flockhart, Konig et al., and Chishti disclose call center routing systems that utilize models and representative data about callers and agents to best pair callers and agents. It would have been obvious before the effective date of the invention to include the affinity data of Chishti in the information and models used to represent agents and callers in Flockhart and Konig et al. in order to optimize business goals through the outcomes of calls, including revenue and increasing customer satisfaction. See Chishti, at least paragraph 30, and Flockhart, column 4, lines 5-12.
Claims 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Flockhart (US 8,234,141) in view of Konig et al. (US 2017/0316438) and in further view of Khatri et al. (US 2025/0365367).
Regarding Claims 7 and 14, Flockhart does not disclose the requestor models and agent models are generated or refined based on simulated interaction between requestors and support agents.
In a call center environment, Konig et al. discloses requestor models and support agent models (See at least 0056, 0059, 0061-62, 0068, 0074, 0081-3, 0100) and where the requestor model is generated or refined based on interactions between a plurality of requestor and one or mor support agents (See at least paragraphs 0056, 0068, 0081). However, Koenig et al. does not specifically disclose simulated interactions between requestors and support agents.
Khatri et al. teaches simulated interactions between requestors and support agents (See at least paragraphs 0005, 0057, 0065, 0082, 0092, which disclose simulated contact-agent pairings to improve overall performance of the call center).
All of Flockhart, Konig et al., and Khatri disclose call center routing systems that utilize models and representative data about callers and agents to best pair callers and agents. It would have been obvious before the effective filing date of the invention to include the simulation of Khatri et al. in the information and models used to represent agents and callers in Flockhart and Konig et al. when matching contacts and agents in order to maximize contact center performance by amplifying the data considered when creating contact-agent pairings. See Khatri et al., paragraphs 0002, 0006, 0008.
Conclusion
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.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
McConnell (US 12,445,559) discloses maintaining data representing agents and monitoring multiple queues to determine if there are shortages or surpluses.
O’Brien et al (US 10,757,262) discusses queues in call centers, agent surpluses and assigning tasks to agents while considering their status
Li et al. (US 12,073,340) teaches Queue Level Metric Forecasting, and routing customers to agents based on this information.
Ross et al. (U.S. 11,831,794) discloses routing leads / customers to agents and advisors in a call center environment using models and modeling data.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BETH V BOSWELL whose telephone number is (571)272-6737. The examiner can normally be reached M-F 8AM - 4:30PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tariq Hafiz can be reached at (571) 272-5350. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BETH V BOSWELL/Supervisory Patent Examiner, Art Unit 3625
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