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 .
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.
the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter.
Claims 1-20 are rejected under 35 U.S.C. 101.
As per claim 1, the claim recites a method, therefore is a process.
“ . . . detect, from a user computing device, a user associated with a claim process, the claim process involving the user providing incident information corresponding to an incident to the computing system; based on a set of response data individual to the user, generate an optimized reminder strategy to provide reminders to the user to complete the claim process . . . “ These limitations, as drafted, are processes that, under its broadest reasonable interpretation, cover performance of the limitation in the mind but for the recitation of generic computer components. Thus, the claim recites a mental process.
“transmit a set of reminders to the user computing device in accordance with the optimized reminder strategy “ amounts to data gathering which is considered to be insignificant extra solution activity (MPEP 2106.05(g); this limitation is also a mere generic transmission and presentation of collected and analyzed data which is considered to be insignificant extra solution activity (MPEP 2106.05(g).
As discussed above, “transmit a set of reminders to the user computing device in accordance with the optimized reminder strategy “ amounts to data gathering which is considered to be insignificant extra solution activity (MPEP 2106.05(g); this limitation is also a mere generic transmission and presentation of collected and analyzed data which is considered to be insignificant extra solution activity (MPEP 2106.05(g). The claim is ineligible.
As per claim 2, “executes a trained machine-learning model on the set of response data to generate the optimized reminder strategy.” is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception - see MPEP 2106.05(d) and Berkheimer Memo. See Singh. The claim is ineligible.
As per claim 3, “the trained machine-learning model generates the optimized reminder strategy to maximize (i) an individual conversion rate of the user, and (ii) individualized satisfaction of the user in completing the claim process “ is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception - see MPEP 2106.05(d) and Berkheimer Memo. See Singh. The claim is ineligible.
As per claim 4, “wherein the optimized reminder strategy comprises an optimal cadence for transmitting reminders to the user computing device” is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception - see MPEP 2106.05(d) and Berkheimer Memo. See Magaletta. The claim is ineligible.
As per claim 5, “wherein the optimized reminder strategy comprises an optimal method for transmitting reminders to the user computing device” is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception - see MPEP 2106.05(d) and Berkheimer Memo. See Magaletta. The claim is ineligible.
As per claim 6, “wherein the optimal method comprises at least one of text messaging, emailing, or phone calling the user” is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception - see MPEP 2106.05(d) and Berkheimer Memo. See Magaletta. The claim is ineligible.
As per claim 7, “wherein the optimized reminder strategy comprises optimal content for transmitting reminders to the user computing device “ is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception - see MPEP 2106.05(d) and Berkheimer Memo. See Magaletta. The claim is ineligible.
As per claim 8, “wherein the set of response data is inferred by the computing system based on the user belonging to a particular cluster” is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception - see MPEP 2106.05(d) and Berkheimer Memo. See Shah. The claim is ineligible.
As per claim 9, “the set of response data is generated by the computing system based on user-specific information of the user” is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception - see MPEP 2106.05(d) and Berkheimer Memo. See Shah. The claim is ineligible.
As per claim 10, “wherein the user-specific information comprises at least one of demographic information of the user or historical response data based on the user interacting with an application corresponding to the claim process” is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception - see MPEP 2106.05(d) and Berkheimer Memo. See Shah. The claim is ineligible.
As per claim 11-19, see rejections on claims 1-9.
As per claim 20, see rejection on claim 1.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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, 4-7, 11, 14-17, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Magaletta et al (US 12205453) (hereinafter Magaletta) in view of Lawless et al (US 2007/0168228) (hereinafter Lawless) .
As per claim 1, Magaletta teaches:
A computing system comprising:
a network communication interface;
one or more processors; and
a memory storing instructions that, when executed by the one or more processors, cause the computing system to:
detect, from a user computing device, a user associated with a process, the process involving the user providing incident information corresponding to an incident to the computing system (Magaletta, col 14, ll 13-15—under BRI, a user associated with a process can be the user creating schedule; incident information can be information regarding curfew calls) ;
based on a set of response data individual to the user (Magaletta, col 14, ll 13-15—under BRI, a set of response data can be data entered by the user from an agency ), generate an optimized reminder strategy to provide reminders to the user to complete the process (Magaletta, col 14, ll 34-35—under BRI, an optimized reminder strategy can be a strategy that includes instant, daily, or weekly schedule); and
transmit a set of reminders to the user computing device in accordance with the optimized reminder strategy (Magaletta, col 14, ll 34-35—under BRI, a set of reminders can be email alerts).
Magaletta does not expressly teach:
wherein the process is a claim process;
However, Lawless discloses:
wherein the process is a claim process (Lawless, [0084]);
Both Lawless and Magaletta pertain to the art of business process management.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to use Lawless’s method to manage a claim process because AI significantly accelerates insurance claims processing by cutting resolution times from weeks down to minutes and enabling straight-through processing.
As per claim 4, Magaletta/Lawless teaches:
The computing system of claim 1 (see rejection on claim 1), wherein the optimized reminder strategy comprises an optimal cadence for transmitting reminders to the user computing device (Magaletta, col 14, ll 34-35—a cadence can be an alert) .
As per claim 5, Magaletta/Lawless teaches:
The computing system of claim 1 (see rejection on claim 1), wherein the optimized reminder strategy comprises an optimal method for transmitting reminders to the user computing device (Magaletta, col 14, ll 34-35).
As per claim 6, Magaletta/Lawless teaches:
The computing system of claim 5 (see rejection on claim 5), wherein the optimal method comprises at least one of text messaging, emailing, or phone calling the user (Magaletta, col 14, ll 34-35).
As per claim 7, Magaletta/Lawless teaches:
The computing system of claim 1 (see rejection on claim 1), wherein the optimized reminder strategy comprises optimal content for transmitting reminders to the user computing device (Magaletta, col 14, ll 34-35).
As per claim 11, see rejection on claim 1.
As per claims 14-17, see rejections on claims 4-7.
As per claim 20, see rejection on claim 1.
Claims 2-3, and 12-13 are rejected under 35 U.S.C. 103 as being unpatentable over Magaletta/Lawless as applied above, and further in view of Singh et al (Pragya Singh & Vandana Singh (2024) The power of AI: enhancing customer loyalty through satisfaction and efficiency, Cogent Business & Management, 11:1, 2326107, DOI: 10.1080/23311975.2024.2326107) (hereinafter Singh).
As per claim 2, Magaletta/Lawless teaches:
The computing system of claim 1 (see rejection on claim 1), wherein the computing system executes a model on the set of response data to generate the optimized reminder strategy (Magaletta, col 14, ll 34-35).
Magaletta/Lawless does not expressly teach:
wherein the model is a trained machine-learning model
However, Singh discloses:
wherein the model is a trained machine-learning model (Singh, Introduction);
Both Singh and Magaletta/Lawless pertain to the art of business process management.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to use Singh’s method to use an AI model because using an AI model to infer a reminder schedule offers several core benefits by replacing rigid, manual time settings with context-aware, adaptive intelligence.
As per claim 3, Magaletta/Lawless/Singh teaches:
The computing system of claim 2 (see rejection on claim 2), wherein the trained machine-learning model generates the optimized reminder strategy to maximize (i) an individual conversion rate of the user, and (ii) individualized satisfaction of the user in completing the claim process (Singh, Abstract—under BRI, conversion rate can be loyalty rate).
As per claims 12-13, see rejections on claims 2-3.
Claims 8-10, and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Magaletta/Lawless as applied above, and further in view of Shah et al (US 2023/0282358 ) (hereinafter Shah).
As per claim 8, Magaletta/Lawless teaches:
The computing system of claim 1 (see rejection on claim 1).
Magaletta/Lawless does not expressly teach:
wherein the set of response data is inferred by the computing system based on the user belonging to a particular cluster.
However, Shah discloses:
wherein the set of response data is inferred by the computing system based on the user belonging to a particular cluster (Shah, [0041]).
Both Shah and Magaletta/Lawless pertain to the art of business process management.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to use Shah’s method to prefill user data because it is well-known in the art that dynamic prefill offers benefits including higher conversion rates: reducing friction and the number of required clicks.
As per claim 9, Magaletta/Lawless teaches:
The computing system of claim 1 (see rejection on claim 1).
Magaletta/Lawless does not expressly teach:
wherein the set of response data is generated by the computing system based on user-specific information of the user.
However, Shah discloses:
wherein the set of response data is inferred by the computing system based on the user belonging to a particular cluster (Shah, [0041]).
Both Shah and Magaletta/Lawless pertain to the art of business process management.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to use Shah’s method to prefill user data because it is well-known in the art that dynamic prefill offers benefits including higher conversion rates: reducing friction and the number of required clicks.
As per claim 10, Magaletta/Lawless/Shah teaches:
The computing system of claim 9 (see rejection on claim 1), wherein the user-specific information comprises at least one of demographic information of the user or historical response data based on the user interacting with an application corresponding to the claim process (Shah, [0041]—under BRI, demographic information of the user can be the user’s age, gender, date of birth, age, current health care coverage, home address, work address, occupation ).
As per claims, 18-19, see rejections on claims 8-9.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 2003/0200100 teaches a method of setting up reminders.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHARLIE SUN whose telephone number is (571)270-5100. The examiner can normally be reached 9AM-5PM.
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/CHARLIE SUN/Primary Examiner, Art Unit 2198
