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 .
Notice to Applicant
The following is a Non-Final Office action. In response to Examiner’s Final Rejection of 7/28/25, Applicant, on 10/28/25, amended claims. Claims 1-4 and 7-18 are pending in this application and have been rejected below.
Response to Amendment
Applicant’s amendments are acknowledged.
Reasons for Overcoming Prior Art
The independent claims 1 and 11 overcome the prior art as the claim has a combination of limitations in addition to claim 1 of: (viii) creating a textual-summary of strengths and weaknesses of each coach in the plurality of coaches and a textual-summary of preferences of the agent by operating a Generative Artificial Intelligence (AI) on the filtered coaching feedback data; (ix) normalizing to numerical values with Euclidean norm of the created textual-summary of strengths and weaknesses of each coach…; and (xii) calculating a correlational score for each coach in the plurality of coaches based on the respective calculated coach impact score and the respective calculated cosine similarity score, wherein the calculated correlational score of each coach indicates a level to which the calculated coach impact score and agent behavioral preferences are aligned.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-4 and 7-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. an abstract idea) without reciting significantly more.
Step One - First, pursuant to step 1 in MPEP 2106.03, the claim 1 is directed to a method which is a statutory category.
Step 2A, Prong One - MPEP 2106.04 - The claim 1 recites–
“A … method for enhancing effectiveness of a coaching session of an agent by creating the coaching session based on a calculated coach impact score of coaches, in a contact center, said computerized-method comprising:
(i) receiving coaching feedback data … from the agent after each coaching session that the agent has participated in, wherein the coaching feedback data is about the coaching session and a related coach;
(ii) receiving a request from a user, …, to create a new coaching session to the agent for a selected focus area and related behaviors;
(iii) collecting the coaching feedback data that has been received from the agent for a plurality of coaching sessions that have been conducted during a preconfigured period, wherein the collected feedback data comprising for each coaching session at least one of:
(a) set of coaching ratings; and
(b) coaching comment, and
wherein each coaching session in the plurality of coaching sessions has been conducted by a different coach;
(iv) filtering bias from the coaching feedback data by removing bias therefrom to yield filtered coaching feedback data;
(v) operating… based on the filtered coaching feedback data, to yield an effective-feedback score an associated dynamic weightage, and a coaching effectiveness score for each coach for the selected focus area and related behavior during the preconfigured period;
(vi) calculating a coach impact score for each coach in the plurality of coaches by operating a coaching impact score module on the yielded effective-feedback score, the associated dynamic weightage, and the coaching effectiveness score of the coach; and
(vii) configuring … to selectively display a subset of the plurality of coaches based on the calculated coach impact score of each coach in the plurality of coaches,
(viii) creating a textual-summary of strengths and weaknesses of each coach in the plurality of coaches and a textual-summary of preferences of the agent … on the filtered coaching feedback data;(ix) normalizing to numerical values with Euclidean norm of the created textual-summary of strengths and weaknesses of each coach in the plurality of coaches to represent coach-vector and the created textual-summary of preferences of the agent to represent agent-vector; (x) pairing the agent-vector with each coach-vector of the coach: (xi) calculating a cosine similarity score for each pair of agent- vector and coach-vector; (xii) calculating a correlational score for each coach in the plurality of coaches based on the respective calculated coach impact score and the respective calculated cosine similarity score, wherein the calculated correlational score of each coach indicates a level to which the calculated coach impact score and agent behavioral preferences are aligned (xiii) configuring the UI that is associated to the coaching application to selectively display a subset of the plurality of coaches based on the correlational score, and (xiv) creating the new coaching session for the agent with a coach having highest correlational score by operating a workflow service, (this was from Claim 5 and claim 6 - which further narrows the abstract idea by performing a number of mathematical relationships while computing scores for coaches and also narrows the teaching part of certain methods of organizing human activity identified above.),
wherein the subset of coaches includes a preconfigured number of coaches having the highest calculated coach impact score and the highest calculated correlational score, and
wherein the calculated coach impact score of each coach indicates an effectiveness-level of the coach to the new coaching session.”
As drafted, this is, under its broadest reasonable interpretation, within the Abstract idea grouping of “certain methods of organizing human activity” (managing relationships between people – including social activities, teaching, and following rules or instructions) and a mathematical relationships [calculating various scores, weighting, ranking]. Here, we have a series of steps for collecting feedback from people being educated how to do their job (e.g. agent employees at a call center) who are being coached (e.g. coaches/supervisors, etc) and a series of steps for how to compute scores for the coaches based on the feedback that can be “coaching ratings” or “coaching comments”, where the various scoring is considered an explicit mathematical relationship. The new limitations are from previous - Claim 5 and claim 6 - which further narrows the abstract idea by performing a number of mathematical relationships while computing scores for coaches and also narrows the teaching part of certain methods of organizing human activity identified above. Accordingly, claim 1 is directed to an abstract idea.
Step 2A, Prong Two - MPEP 2106.04 - This judicial exception is not integrated into a practical application. In particular, the claim 1 recites additional elements that are:
“A computerized-method for enhancing effectiveness of a coaching session of an agent by creating the coaching session based on a calculated coach impact score of coaches, in a contact center, said computerized-method comprising:
(i) receiving coaching feedback data via a coaching web application from the agent after each coaching session that the agent has participated in, wherein the coaching feedback data is about the coaching session and a related coach;
(ii) receiving a request from a user, via a User Interface (UI) that is associated to the coaching web application, to create a new coaching session to the agent for a selected focus area and related behaviors;
…
(v) operating a coach evaluation module based on the filtered coaching feedback data, to yield an effective-feedback score an associated dynamic weightage, and a coaching effectiveness score for each coach for the selected focus area and related behavior during the preconfigured period;
…
(vii) configuring the UI that is associated to the coaching application to selectively display a subset of the plurality of coaches based on the calculated coach impact score of each coach in the plurality of coaches...”;
(viii) creating a textual-summary of strengths and weaknesses of each coach… and a textual-summary of preferences of the agent by “operating a Generative Artificial Intelligence (AI)” on the filtered coaching feedback data; … to selectively display… coaching session with highest correlation score by operating a workflow service (viewed as just a program of the computer); (limitations above were amended from claim 5) - See updated July 2024 Subject Matter Eligibility Update, Example 48, claim 1 – series of mathematical calculations for “deep learning” in natural language processing. At step 2a, prong two and step 2B, the preamble of “computer” in combination with “operating a Generative Artificial Intelligence (AI)” is similar to updated July 2024 Subject Matter Eligibility Update, Example 48, claim 1; that is “mere instructions to implement abstract idea on a computer at MPEP 2106.05f); see also MPEP 2106.05h “field of use” for combination of computer and “train at least one machine learning model.”
(MPEP 2106.05f applies – limitations in claim involve a computer, , and is considered “apply it” [the abstract idea] on a computer; merely uses a computer as a tool to perform an abstract idea”) and having a display is “field of use” MPEP 2106.05h.
Accordingly, the additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim also fails to recite any improvements to another technology or technical field, improvements to the functioning of the computer itself, use of a particular machine, effecting a transformation or reduction of a particular article to a different state or thing, and/or an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. See 84 Fed. Reg. 55. The claim is directed to an abstract idea.
Step 2B in MPEP 2106.05 - The claim does 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 of a processor/computer, and a “user interface” to execute operations are MPEP 2106.05(f) (Mere Instructions to Apply an Exception – “Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible.” Alice Corp., 134 S. Ct. at 235) and “field of use” (MPEP 2106.05h). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
The claim fails to recite any improvements to another technology or technical field, improvements to the functioning of the computer itself, use of a particular machine, effecting a transformation or reduction of a particular article to a different state or thing, adding unconventional steps that confine the claim to a particular useful application, and/or meaningful limitations beyond generally linking the use of an abstract idea to a particular environment. See 84 Fed. Reg. 55. The claim is not patent eligible. Viewed individually or as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself.
Independent claim 11 is directed to a system at step 1, which is a statutory category. Claim 11 recites similar limitations as claim 1 and is rejected for the same reasons at step 2a, prong one, 2a, prong 2, and step 2b. In addition, it recites “one or more processors”, which at step 2a, prong 2 and step 2B also is considered “MPEP 2106.05f” apply it [abstract idea] on a computer. The claim is not patent eligible.
Claims 2 and 12 narrow the abstract idea having a user acknowledge by a person. Claims 3 and 13 narrow the abstract idea by naming different biases that will be removed.
Claims 4 and 14 narrow the abstract idea by ranking or showing coach with highest impact (i.e. most to improve upon).
Claims 7 and 15 narrow the abstract idea by having further mathematical relationships to help prioritize learning/teaching for people.
Claims 8-10, 16-18 narrow the abstract idea by having further mathematical relationships to help prioritize learning/teaching for people. The recitations of “database” and “data store” and computer components here are considered part of “apply it [abstract idea] on a computer” MPEP 2106.05(f) and “field of use” (MPEP 2106.05h).
Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
For more information on 101 rejections, see MPEP 2106.
Response to Arguments
Applicant's arguments filed 10/28/2025 have been fully considered but they are not persuasive.
Applicant argues that the claims do not recite “mathematical relationships”, nor do they recite “any method of organizing human activity”, not do they recite a mental process. Remarks, page 12. In response, Examiner respectfully disagrees. As stated in the 101 rejection, the claim is directed to “certain methods of organizing human activity” (managing relationships between people – including social activities, teaching, and following rules or instructions) and a mathematical relationships [calculating various scores, weighting, ranking]. The claim is a series of steps for a person coaching another person, such as an employee or call agent. A number of mathematical relationships are also in the claims – e.g. (v) effective-feedback score an associated dynamic weightage, and a coaching effectiveness score for each coach; (vi) calculating a coach impact score… (ix) normalizing to numerical values with Euclidean norm of the created textual-summary of strengths and weaknesses of each coach… (xi) calculating a cosine similar score… (xii) calculating a correlational score for each coach. The arguments are not persuasive, and do not address the specific rejection. “Mental process” was not asserted.
Applicant then argues there is a practical application as there is “selectively display a subset of the plurality of coaches based on the correlational score and creating the new coaching session for the agent with a coach having highest correlational score by operating the workflow service.” Remarks, page 12. In response, Examiner respectfully disagrees. As stated in the claim 1 rejection, the “display”, selectively display, and computer are part of the “apply it [abstract idea] on a computer” (MPEP 2106.05f) and “field of use” (MPEP 2106.05h). The specification supports the view that “by generative artificial intelligence” is just “apply it by a computer.” See Applicant’s [0204-0206] as published- According to some embodiments of the present disclosure, the filtered coaching comments, and ratings, i.e., filtered coaching feedback data may be provided to Generative AI with LLM to determine strengths and weaknesses of a coach. The Generative AI may create a textual summary of strengths and weaknesses of the coach based on the following prompt-text.” The specification also supports that the “selectively display” is just displaying results from the abstract idea of coaching and scoring of people. See e.g. [0127] as published and FIG. 10 – “A UI that is associated to the coaching application, such as coaching web application 110b, may be configured to selectively display a subset of the plurality of coaches based on the correlational score.” See MPEP 2106.05(a)(II) Examples that the courts have indicated may not be sufficient to show an improvement to technology include: iii. Gathering and analyzing information using conventional techniques and displaying the result, TLI Communications, 823 F.3d at 612-13. In contrast, an eligible example is in MPEP 2106.04(a)(1) “vi. a method of rearranging icons on a graphical user interface (GUI) comprising the steps of: receiving a user selection to organize each icon based on the amount of use of each icon, determining the amount of use of each icon by using a processor to track the amount of memory allocated to the application associated with the icon over a period of time, and automatically moving the most used icons to a position in the GUI closest to the start icon of the computer system based on the determined amount of use.” The “operating a workflow service” is viewed as part of just operating the computer to perform the abstract idea and is still rejected under the “apply it [abstract idea] on a computer” (MPEP 2106.05f) and “field of use” (MPEP 2106.05h).
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.
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/IVAN R GOLDBERG/Primary Examiner, Art Unit 3619