DETAILED ACTION
Status
This communication is in response to Applicant’s “AMENDMENT” filed on April 27, 2026 (hereinafter “Amendment”). In the Amendment, Applicant amended Claims 1 and 19-20; cancelled Claim 8; and added no claim(s). Therefore, Claims 1-7 and 9-20 are pending and presented for examination.
Original Claims 1-20 were originally presented by Applicant and, therefore, have been constructively elected by original presentation for prosecution on the merits per MPEP § 819 and MPEP § 821.03.
The present application, filed after March 16, 2013, is being examined under the first inventor to file (FITF) provisions of the America Invents Act (AIA ).
Examiner notes that this application has published on May 28, 2026, as U.S. Patent Application Publication No. 2026/0148622 of Dakka et al. (hereinafter “Dakka”).
Priority/Benefit Claim
No claim(s) for benefit or priority exists in this application and, therefore, the effective filing date of this application is its filing date of November 22, 2024.
Information Disclosure Statement(s)
Applicant is notified of 37 C.F.R. 1.56, which states that each inventor named in the application has a duty to disclose information material to patentability.
CPC Classification Notes
Examiner notes the following Cooperative Patent Classification (CPC) classifications as being related to this case:
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G06F ELECTRIC DIGITAL DATA PROCESSING
G06F 16/24522 ••••• {Translation of natural language queries to structured queries}
G06F 40/00 Handling natural language data
G06F 40/20 • Natural language analysis (semantic analysis of natural language G06F 40/30)
G06F 40/30 • Semantic analysis
G06F 40/40 • Processing or translation of natural language (natural language analysis G06F 40/20; semantic analysis G06F 40/30)
G06F 40/58 •• Use of machine translation, e.g. … for server-side translation for client devices or for real-time translation
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G07F 19/00 Complete banking systems; Coded card-freed arrangements adapted for dispensing or receiving monies or the like and posting such transactions to existing accounts, e.g. automatic teller machines data processing equipment for bank accounting G06Q 40/02
G07F 19/20 • Automatic teller machines [ATMs]
G07F 19/206 •• Software aspects at ATMs
G07F 19/209 •• {Monitoring, auditing or diagnose of functioning of ATMs}
G07F 19/211 •• {Software architecture … in relation to the ATM network}
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Response to Amendments
A Summary of the Response to Applicant’s Amendment:
Applicant’s Amendment introduces an objection(s) to Claim 19; therefore, the Examiner asserts the objection(s) to independent Claim 19, as provided below.
Applicant’s Amendment overcomes the rejection to Claim 8 under 35 U.S.C. § 101; therefore, Examiner withdraws the § 101 rejection to Claim 8. However, Applicant’s Amendment does not overcome rejections to Claims 1-7 and 9-20 under 35 U.S.C. § 101; therefore, Examiner asserts/maintains § 101 rejections to Claims 1-7 and 9-20, as provided below.
Applicant’s Amendment overcomes the rejection to Claim 8 under 35 U.S.C. § 103; therefore, the Examiner withdraws the § 103 rejection to Claim 8. However, Applicant’s Amendment does not overcome § 103 rejections to Claims 1-7 and 9-20; therefore, the Examiner maintains/asserts § 103 rejections to Claims 1-7 and 9-20, as provided below.
Applicant’s Amendment introduces new rejections to Claims 1-7 and 9-20 under § 112(b); therefore, the Examiner asserts § 112(b) rejections to Claims 1-7 and 9-20, as provided below.
Applicant’s arguments are found to be not persuasive; please see Examiner’s “Response to Arguments” provided below.
Claim Objections
Independent Claim 19 is objected to because of the following informalities: grammatical error(s). Claim 19 recites a set of operational elements (i.e., receive…; generate…; append…; transmit…; receive… transmit….); however, Claim 19 lacks a conjunction (e.g., “and”) between the 5th and 6th major operations recited in Claim 19. More specifically, Claim 19 lacks a conjunction (e.g., “and”) as well as a semicolon (i.e., “;”) between claim elements “receive…from the pre-trained LLM” and “transmit the SQL database query statement…” — similar to how Claim 1 recites the word “and” between operations “transmitting the at least one SQL database query statement…;” and “querying” in Claim 1. Appropriate correction(s) is required to independent Claim 19.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b) of the America Invents Act (AIA ):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 1-7 and 9-20 are rejected under 35 U.S.C. 112(b) of the AIA as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention. “A claim is indefinite when it contains words or phrases whose meaning is unclear” (MPEP § 2173.05(e)).
Each of independent Claims 1 and 19 twice introduces the phrase “message data” and, therefore, it is unclear as to what the phrase “the message data” makes antecedent reference to in each of the independent claims. Consequently, Claims 1, 19 and 20 are rejected under AIA 35 U.S.C. 112(b) as being indefinite. In other words, there is insufficient antecedent basis for the phrase “the message data” recited in independent Claims 1 and 19. For example, it is unclear as to whether the phrase “the message data”, which is recited in each of Claims 1 and 19 (e.g., in the phrase “…appending…to the message data to generate the query data;”):
references first-recited “(i) message data representing the user-specific query” recited in each of independent Claims 1 and 19 (bolding emphasis added by Examiner);
references second-introduced “(ii) pre-defined system message data representing a pre-defined system message” (bolding emphasis added), which is recited in each of Claims 1 and 19; or
references some combination thereof (i.e., some combination of the 1st and 2nd introductions of “message data” recited in each of Claims 1 and 19) such as, for example, refers to all of “(i) message data” and all of (ii) pre-defined system message data, or refers to some of “(i) message data” and some of “(ii) pre-defined system message data”.
Therefore, Claims 1, 19 and 20 are rejected under AIA 35 U.S.C. 112(b) as being indefinite. For purposes of this Office action, “the message data”, as recited in Claims 1 and 19, is understood to be any message data introduced in independent Claims 1 and 19. Appropriate corrections are required.
In addition, each of independent Claims 1 and 19 twice introduces the phrase “a user-specific query” and then subsequently introduces recitations of “the user-specific query”; therefore, it is unclear as to what later-recited phrases of “the user-specific query” refers to in each claim — there is insufficient antecedent basis for the phrase “the user-specific query” recited in each of independent Claims 1 and 19. Thus, Claims 1 and 19 are rejected under 35 U.S.C. 112(b) of the AIA as being indefinite. For example, it is unclear as to whether the phrase “the user-specific query” references the first-recited “a user-specific query” in the preamble phrase “a computer-implemented method for automatically generating, responsive to a user-specific query”, the secondly introduced “a user-specific query” in the phrase “(ATMs), a user-specific query requesting information”, or both recitations to “a user-specific query” introduced in each independent Claims 1 and 19. As currently presented, recitations of “the user-specific query” are each amenable to multiple plausible constructions and, therefore, a person having ordinary skill in the art would be unable to determine what the Applicant does and does not regard as the invention. Hence, Claims 1, 19 and 20 are rejected under AIA 35 U.S.C. 112(b) as being indefinite. For purposes of this Office action, “the user-specific query”, as recited in independent Claims 1 and 19, is understood to be any user-specific query introduced in Claims 1 and 19. Appropriate corrections are required.
Regarding Claim 14, since it is unclear as to what the phrase “the computing device” makes antecedent reference to in Claim 14, Claim 14 is rejected under AIA 35 U.S.C. 112(b) as being indefinite. There is insufficient antecedent basis for the phrase “the computing device” recited in Claim 14. For example, it is unclear as to whether the phrase “the computing device” recited in Claim 14 (bolding emphasis added):
references the phrase “a computing device” recited in Claim 1 (bolding emphasis added) upon which Claim 14 depends via intervening Claims 11-13;
references second-introduced “a computing device” recited in Claim 13 (bolding emphasis added); or
references both computing devices introduced in Claims 1 and 13.
Therefore, Claim 14 is rejected under AIA 35 U.S.C. 112(b) as being indefinite. For purposes of this Office action, “the computing device”, as recited in Claim 14, is understood to be any computing device introduced in Claims 1 or 13. Appropriate correction(s) is required.
Regarding Claim 18, since it is unclear as to what the phrase “the computing device” makes antecedent reference to in Claim 18, Claim 18 is rejected under AIA 35 U.S.C. 112(b) as being indefinite. There is insufficient antecedent basis for the phrase “the computing device” recited in Claim 18. For example, it is unclear as to whether the phrase “the computing device” recited in Claim 18 (bolding emphasis added):
references the phrase “a computing device” recited in Claim 1
(bolding emphasis added) upon which Claim 18 directly depends;
references second-introduced “a computing device” recited in Claim 18 (bolding emphasis added); or
references both computing devices introduced in Claims 1 and 18.
Therefore, Claim 18 is rejected under AIA 35 U.S.C. 112(b) as being indefinite. For purposes of this Office action, “the computing device”, as recited in Claim 18, is understood to be any computing device introduced in Claims 1 or 18. Appropriate correction(s) is required.
Regarding Claim 20, since it is unclear as to what the phrase “the computing device” makes antecedent reference to in Claim 20, Claim 20 is rejected under AIA 35 U.S.C. 112(b) as being indefinite. There is insufficient antecedent basis for the phrase “the computing device” recited in Claim 20. For example, it is unclear as to whether the phrase “the computing device” recited in Claim 20 (bolding emphasis added):
references the phrase “a computing device” recited in Claim 1 (bolding emphasis added) upon which Claim 20 depends via Claim 20 reciting “…the method defined by claim 1”;
references second-introduced “a computing device” recited in Claim 20 (bolding emphasis added); or
references both computing devices introduced in Claims 1 and 20.
Therefore, Claim 20 is rejected under AIA 35 U.S.C. 112(b) as being indefinite. For purposes of this Office action, “the computing device”, as recited in Claim 20, is understood to be any computing device introduced in Claims 1 or 20. Appropriate correction(s) is required.
Claims 2-7 and 9-18 depend from independent Claim 1, but do not resolve the above issues and inherit the deficiencies of the parent claim(s); therefore, Claims 2-7 and 9-18 are rejected under 35 U.S.C. 112(b) of the AIA .
Similarly, Claim 20 (via reciting “…the method defined by claim 1”) depends from language recited in independent Claim 1, but does not resolve the above issue(s) and directly inherits the deficiencies of Claim 1; therefore, Claim 20 is rejected under 35 U.S.C. 112(b) of the AIA . Appropriate corrections are required.
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 1-7 and 9-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. During patent examination, the pending claims must be “given their broadest reasonable interpretation consistent with the specification” (MPEP § 2111). In view of this standard and based upon consideration of all of the relevant factors with respect to each claim as a whole, Claims 1-7 and 9-20 are rejected as ineligible subject matter under 35 U.S.C. 101.
Step 1: Claims 1-7 and 9-19 satisfy Step 1 enunciated in Alice Corp. v. CLS Bank International, 573 U.S. __, 134 S. Ct. 2347 (2014). However, Claim 20 does not satisfy Step 1 because Claim 20, in view of Applicant’s disclosure, encompass software per se, which is ineligible subject matter under 35 U.S.C. 101. For example, paragraph [0049] of Applicant’s filed specification mentions that “executable software, for example the terminal management application, that is executable by the processors of the computing device” (e.g., at specification ¶ [0049] with bolding emphases added by Examiner). Thus, Examiner notes that it appears that “non-transitory computer-readable medium instructions” recited in Claim 20 appears to be no more than only instructions, which encompasses software per se. However, under 35 U.S.C. 101, software by itself (e.g., “a non-transitory computer-readable medium instructions”) — regardless if the software is transitory or non-transitory — is not eligible subject matter for a U.S. patent. Since Claim 20 encompasses software per se, Claim 20 is rejected under 35 U.S.C. 101 as being drawn to non-statutory subject matter.
Step 2A: Claims 1-7 and 9-20 are rejected under § 101 because Applicant’s claimed subject matter is directed to an abstract idea without significantly more. The rationale for this finding is that Applicant’s claims recite using an informational request in natural language of a user to manage generation of a user query to obtain saved information for the user, as more particularly recited in the pending claims save for recited (non-abstract claim elements): a processor of a computing device configured to execute a terminal management application responsible for a plurality of Automated Teller Machines (ATMs); a pre-trained Large Language Model (LLM); a user-specific query comprising text; query data comprising message data; appending the pre-defined system message data to the message data; each of Applicant’s recited steps/processes of receiving, querying, inputting, appending data, transmitting, providing and displaying; (only Claim 2) transmitting message data and transmitting pre-defined system message data; (only Claim 3) providing the pre-defined system message as a message; (only Claims 4-7) providing the pre-defined system message as a message; (only Claim 9) receiving, by the terminal management application, the user-specific query as text data input via at least one user input device of a computing device; (only Claim 10) providing the at least one database query statement; (only Claim 11) transmitting, by the terminal management application, the at least one database query statement to the relational database to query the relational database; (only Claim 12) receiving, by the terminal management application, results data; (only Claim 13) transmitting results data to a computing device of a user who provided the user-specific query; (only Claim 14) displaying, on a display of the computing device, at least one result associated with the results data; (only Claim 15) displaying the at least one result in tabular format; (only Claim 16) providing the pre-trained LLM as a generative pre-trained transformer type LLM; (only Claim 17) providing the pre-trained LLM as a generative AI-based chatbot; (only Claim 18) inputting the user-specific query to a web-interface of a browser application executing on a computing device; and receiving, by the terminal management application, the user-specific query from the computing device; (only Claim 19) a computing device comprising at least one processor configured to execute a terminal management application responsible for a plurality of Automated Teller Machines (ATMs); and (only Claim 20) a non-transitory computer-readable medium instructions which, when executed by a computing device, cause the computing device to carry out.
However, using an informational request in natural language of a user to manage generation of a user query to obtain saved information for the user, as currently recited in Applicant’s pending claims and further explained below, encompasses mental processes and/or a certain method of organizing human activity — (i) fundamental economic principle or practice; and/or (ii) commercial interaction (including sales activities or behaviors; business relations). See Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1139, 120 USPQ2d 1474 (Fed. Cir. 2016) (holding that claims to the mental process of “translating a functional description of a logic circuit into a hardware component description of the logic circuit” are directed to an abstract idea, because the claims “read on an individual performing the claimed steps mentally or with pencil and paper”). MPEP 2106.04(a)(2)(II)(A) provides examples of “fundamental economic principles or practices” and MPEP 2106.04(a)(2)(II)(B) provides additional discussion and examples of commercial or legal interactions. This judicial exception (i.e., abstract idea exception) is not integrated into a practical application because each claim as a whole, having the combination of additional elements beyond the judicial exception(s), does not integrate the exception into a practical application of the exception and, therefore, the pending claims are “directed to” a judicial exception under USPTO Step 2A. More specifically, each claim as a whole does not appear to reflect the combination of additional elements as: (1) improving the functioning of a computer itself or improving another technology or technical field, (2) applying the judicial exception with, or by use of, a particular machine/manufacture that is integral to the claim, (3) effecting a transformation or reduction of a particular article to a different state or thing, or (4) applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment. Instead, any improvement is to the underlying abstract idea of using an informational request in natural language of a user to manage generation of a user query to obtain saved information for the user. SAP Am., Inc. v. InvestPic, LLC, No. 2017-2081, 2018 U.S. App. LEXIS 12590, Slip. Op. 13 (Fed. Cir. May 15, 2018) (“What is needed is an inventive concept in the non-abstract realm.”). Examiner notes that Applicant's recited use or usage of “a pre-trained Large Language Model (LLM)” in Claims 1, 10, 16-17 and 19 each appear as a high-level black box with no detail about the recited pre-trained LLM itself or any LLM processes/logic, such as how the model operates on input data to produce an output(s), such as Applicant’s “at least one database query statement” recited in each of the independent claims. In addition, Examiner notes that no detail of any training or pre-training algorithm appears to be mentioned in Applicant's disclosure and, therefore, no specific way of training or pre-training the LLM exists within Applicant's recited use of an LLM. Consequently, Applicant's mere recitation to "pre-trained LLM" is not sufficient to amount to a practical application under Step 2A, Prong 2 of the Subject Matter Eligibility (SME) analysis. Applicant’s additional elements, taken individually and in combination, do not appear to be integrated into a practical application since they embody mere instructions to implement the abstract idea on a computer or mere use of a computer as a tool to perform the abstract idea, do no more than generally linking the use of the abstract idea to a particular technological environment or field of use {e.g., a computer network in network communication with Automated Teller Machines (ATMs), a user computing device, and a relational database, such as illustrated in Figure 1 of Applicant’s drawings}, and amount to no more than combining the abstract idea with insignificant extra-solution activity including each of Applicant’s recited operations/processes of receiving, querying, inputting, appending, transmitting, providing and displaying, as further explained below. For the reasons discussed above, Applicant’s pending claims are directed to an abstract idea that is not integrated into a practical application under Step 2A, Prong 2 of the Subject Matter Eligibility (SME) analysis of 35 U.S.C. 101.
Step 2B: Under Step 2B enunciated in Alice Corp. v. CLS Bank International, 573 U.S. __, 134 S. Ct. 2347 (2014), Applicant’s instant claims do not recite limitations, taken individually and in combination, that are sufficient to amount to “significantly more” than the abstract idea because Applicant’s claims do not recite, as further explained in detail below, an improvement to another technology or technical field, an improvement to the functioning of a computer itself, an application with or by a particular machine, a transformation or reduction of a particular article to a different state or thing, unconventional steps confining the claim to a particular useful application, or meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment.
Examiner notes that each of Claims 1-7 and 9-18 is drawn to a method; however, the method steps do not recite, require, or indicate implementation by a particular machine since none of limitations recited in Applicant’s method claims are performed by any computer or processing device since recited use of a terminal management application encompasses a software program where any implied computing device does no more than assist/help a person perform such steps/processes or thoughts when the person is using the software program on the computing device. Even if a computer/machine was implied, Applicant’s claim limitations taken individually and in combination would be merely instructions to implement the abstract idea on a computer and would require no more than generally linking the use of an abstract idea to a particular technological environment or field of use (e.g., a computer network in network communication with Automated Teller Machines (ATMs), a user computing device, and a relational database, such as illustrated in Figure 1 of Applicant’s drawings), and having the abstract idea combined with insignificant extra-solution activity including each of Applicant’s recited operations/processes of receiving, querying, inputting, appending, transmitting, providing and displaying, as further explained below. Examiner also notes that albeit limitations recited in the Claims 19-20 are performed by the generically recited “a computing device” comprising “at least one processor”, these claim limitations taken individually and in combination are merely instructions to implement the abstract idea on a computer and require no more than a generic computer device with a generic processor to generally link Applicant’s abstract idea to a particular technological environment or field of use {e.g., a computer network in network communication with Automated Teller Machines (ATMs), a user computing device, and a relational database, such as illustrated in Figure 1 of Applicant’s drawings}, and no more than a combination of the abstract idea with insignificant extra-solution activity including each of Applicant’s recited operations/processes of receiving, querying, inputting, appending, transmitting, providing and displaying, as further explained below. As mentioned above, the claim elements in addition to the abstract idea arguably include: a processor of a computing device configured to execute a terminal management application responsible for a plurality of Automated Teller Machines (ATMs); a pre-trained Large Language Model (LLM); a user-specific query comprising text; query data comprising message data; appending the pre-defined system message data to the message data; each of Applicant’s recited steps/processes of receiving, querying, inputting, appending data, transmitting, providing and displaying; (only Claim 2) transmitting message data and transmitting pre-defined system message data; (only Claim 3) providing the pre-defined system message as a message; (only Claims 4-7) providing the pre-defined system message as a message; (only Claim 9) receiving, by the terminal management application, the user-specific query as text data input via at least one user input device of a computing device; (only Claim 10) providing the at least one database query statement; (only Claim 11) transmitting, by the terminal management application, the at least one database query statement to the relational database to query the relational database; (only Claim 12) receiving, by the terminal management application, results data; (only Claim 13) transmitting results data to a computing device of a user who provided the user-specific query; (only Claim 14) displaying, on a display of the computing device, at least one result associated with the results data; (only Claim 15) displaying the at least one result in tabular format; (only Claim 16) providing the pre-trained LLM as a generative pre-trained transformer type LLM; (only Claim 17) providing the pre-trained LLM as a generative AI-based chatbot; (only Claim 18) inputting the user-specific query to a web-interface of a browser application executing on a computing device; and receiving, by the terminal management application, the user-specific query from the computing device; (only Claim 19) a computing device comprising at least one processor configured to execute a terminal management application responsible for a plurality of Automated Teller Machines (ATMs); and (only Claim 20) a non-transitory computer-readable medium instructions which, when executed by a computing device, cause the computing device to carry out. However, each of these components is recited at a high level of generality that taken individually and in combination perform corresponding generic computer functions of receiving, querying, inputting, appending, transmitting, providing and displaying — there is no indication that the combination of elements improves the functioning of a computer or improves any other technology since the additional elements taken individually and collectively merely provide generic computer implementations known to the industry. Furthermore, Examiner notes that none of the processes/steps recited in the pending claims taken individually and in combination impose a meaningful limit on the claim’s scope since none of recited processes/steps taken individually and in combination involve activity that amounts to more than generic computer functions/activity. The steps/processes of receiving, querying, inputting, appending, transmitting, providing and displaying, as currently recited individually and in combination in Applicant’s claims, are considered to be generic computer functions since they involve having the abstract idea combined with insignificant extra-solution activity, and generally linking the use of an abstract idea to a particular technological environment or field of use previously known to the industry — each of the steps of receiving encompasses a data input/loading or retrieving function performed by virtually all general purpose computers {see Alice Corp., 134 S. Ct. at 2360; see Ultramercial, 772 F.3d at 716‐17; see buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355 (Fed. Cir. 2014); see Cyberfone Systems, LLC v. CNN Interactive Group, Inc., 558 Fed. Appx. 988, 993 (Fed. Cir. 2014); and see Mayo Collaborative Serv. v. Prometheus Labs., Inc., 566 U.S. __, 132 S.Ct. 1289, 101 USPQ2d 1961 (2012)}; each of the steps of inputting and querying encompasses a data recognition/inquiry function or retrieving function performed by virtually all general purpose computers {see Content Extraction and Transmission LLC v. Wells Fargo Bank, N.A., 776 F.3d 1343, 113 U.S.P.Q.2d 1354 (Fed. Cir. 2014), hereinafter “Content Extraction”, for data recognition); each of the steps of appending encompasses a data saving or depositing function performed by virtually all general purpose computers {see Alice Corp., 134 S. Ct. at 2360; Cyberfone Systems, LLC v. CNN Interactive Group, Inc., 558 Fed. Appx. 988 (Fed. Cir. 2014), hereinafter “Cyberfone”; and Content Extraction and Transmission LLC v. Wells Fargo Bank, N.A., 776 F.3d 1343, 113 U.S.P.Q.2d 1354 (Fed. Cir. 2014), hereinafter “Content Extraction”, for data storage}; and each of the steps of transmitting, providing and displaying, encompasses a data output/transmittal function performed by virtually all general purpose computers {see Ultramercial, 772 F.3d at 716‐17; see buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355 (Fed. Cir. 2014); and see Cyberfone Systems, LLC v. CNN Interactive Group, Inc., 558 Fed. Appx. 988, 993 (Fed. Cir. 2014)}. In addition, Examiner notes that Applicant’s disclosure mentions that “executable software…, when executed by the processor(s), causes the computing device 130 to carry out the methodology described herein” (original specification paragraph [0049]). Examiner notes that it may be worth being mindful of the “July 2015 Update: Subject Matter Eligibility” document, at page 7, second and sixth bullet points (July 30, 2015) regarding various well‐understood, routine, and conventional functions of a computer. Employing well-known computer functions individually and in combination to execute an abstract idea, even when limiting the use of the idea to one particular environment, does not add significantly more, similar to how limiting the computer-implemented abstract idea in Flook (Parker v. Flook, 437 U.S. 584, 19 U.S.P.Q. 193 (1978)) to petrochemical and oil-refining industries was insufficient. For the reasons discussed above, Applicant’s pending claims do not satisfy Step 2B enunciated in Alice Corp. v. CLS Bank International, 573 U.S. __, 134 S. Ct. 2347 (2014).
Consequently, based upon consideration of all of the relevant factors with respect to each claim as a whole, Claims 1-7 and 9-20 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. For information regarding 35 U.S.C. 101, please see Subject Matter Eligibility (SME) guidance and instructional materials at https://www.uspto.gov/patents/laws/examination-policy/subject-matter-eligibility, which includes guidance, memoranda, and updates regarding SME under 35 U.S.C. 101.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 (AIA ) 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 of this title, 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 1-7 and 9-20 are rejected under 35 U.S.C. 103 of the AIA as being unpatentable over U.S. Patent Application Publication No. 2026/0037505 of Vu et al. (hereinafter “Vu”) in view of U.S. Patent Application Publication No. 2002/0082994 of Kathy Ann Herziger (hereinafter “Herziger”).
Regarding Claim 1, Vu discloses a computer-implemented method for automatically generating, responsive to a user-specific query, at least one database query statement for querying a relational database that comprises data associated with a plurality of business items, [the method] comprising (e.g., “data-driven companies to track the real-time state of its business in order to quickly understand and diagnose any emerging issues, trends, or anomalies” such as based on “financial business metrics” —Vu at ¶ [0028]; “business information is stored in the form of relational databases that store, process, and retrieve data” —Vu at ¶ [0028]; and “Artificial intelligence-based solutions, such as chatbots… to communicate interchangeably with both a human and various backend systems…using Structured Query Language (SQL)” and “chatbots (referred to as skill bots) … interact with users and fulfill specific types of tasks, such as tracking inventory,… creating…reports, …checking a bank account… and the like” —Vu at ¶¶ [0003] and [0061]; “Using a NL2LF service, users such as business analysts can extract information from their systems without thorough knowledge of a specific programming language and system schemas” —Vu at ¶ [0125]):
receiving, by a processor of a computing device configured to execute a terminal management application responsible for a plurality of business items, a user-specific query requesting information associated with the plurality of business items, the user-specific query comprising natural language text (e.g., “receiving an input natural language utterance from a user” such as “natural language statements, queries, requests, and questions (i.e., sentences)” —Vu at ¶¶ [0013] and [0005]; “User inputs 110 are generally in a natural language form and…can be in text form, such as when a user types in a sentence, a question, a text fragment…” —Vu at ¶ [0054]; “query posed by a user using a digital assistant or chatbot” and “A bot (also referred to as a skill, chatbot, chatterbot, or talkbot) is a computer program that can perform conversations with end users. The bot can generally respond to natural-language messages (e.g., questions or comments)….” —Vu at ¶¶ [0124] and [0045]; “End users interact with the bot through conversational interactions… just as end users interact with other people… and the bot … asking the end user how it can help. End users also interact… with a banking bot that is …trained…” —Vu at ¶ [0047]; “User inputs 110 are generally in a natural language form and are referred to as utterances. A user utterance 110 can be in text form, such as when a user types in a sentence, a question, a text fragment…” and “utterances… can be phrased as questions, commands, requests, and the like” such as “to track the real-time state of its business in order to quickly understand and diagnose any emerging issues, trends, or anomalies” —Vu at ¶¶ [0054], [0049] and [0028]; and “chatbots (referred to as skill bots) … interact with users and fulfill specific types of tasks, such as tracking inventory,… creating…reports, …checking a bank account… and the like” such as based on “business information… stored in …relational databases” —Vu at ¶¶ [0061] and [0028]);
generating, by the application, query data comprising: (i) message data representing the user-specific query (e.g., Vu at ¶¶ [0003], [0005], [0012]–[0013], [0029]–[0030], [0041], [0125], [0131]–[0145], [0163] and [0191]), and (ii) pre-defined system message data representing a pre-defined system message that includes information describing a schema of the relational database, relational mappings between database entities, and syntax rules for generating a database query statement (e.g., Vu at ¶¶ [0003], [0005], [0012]–[0013], [0029]–[0030], [0041], [0050], [0125]–[0126], [0131]–[0145], [0158], [0162]–[0163] and [0191]);
appending the pre-defined system message data to the message data to generate the query data (e.g., Vu at ¶¶ [0003], [0005], [0012]–[0013], [0029]–[0030], [0041], [0125], [0131]–[0145], [0163], [0179] and [0191]);
transmitting the query data to a pre-trained Large Language Model (LLM) (e.g., “natural language statements, queries, requests, and questions (i.e., sentences) can be transformed into a machine-oriented language that can be executed by an application (e.g., chatbot, model, program, machine, etc.)” —Vu at ¶ [0005]; “input natural language utterance from a user; converting, using the trained machine learning model, the input natural language utterance to an output logical form based on the input natural language utterance and database schema information” and “the machine learning model is a large language model pretrained for a task of converting an input natural language utterance to an output logical form” —Vu at ¶¶ [0013] and [0012]; “a pretrained NL2LF model (as described herein a pretrained Large Language Model (LLM))” such as “a pretrained Text-to-SQL model” —Vu at ¶¶ [0041] and [0163]; “Efforts to bridge this communication gap have led to… a new type of processing called NL [natural language] interfaces to databases systems (NLIDB), which facilitates search capabilities…. such as natural language [(NL)] to logical form (NL2LF), NL to SQL (NL2SQL)” —Vu at ¶ [0029]; “the NL2LF model is a machine learning model trained to generate final representations from NL utterances. Thereafter, the utterance in the desired query format may be executed on a backend system via a LF execution engine supporting the desired query format such as database to obtain data relevant to the query and formulate a response to the NL utterance (e.g., an answer to the user's question) for review by a user” —Vu at ¶ [0030]; “Using a NL2LF service, users… can extract information from their systems without thorough knowledge of a specific programming language and system schemas” —Vu at ¶ [0125]; and Vu at ¶ [0191]);
automatically generating, by the pre-trained LLM based on the query data including the pre-defined system message data, at least one database query statement in Structured Query Language (SQL) (e.g., “SQL is a standard database management language for interacting with relational databases. SQL can be used for storing, manipulating, retrieving, and… otherwise managing data held in a relational database management system (RDBMS)…. SQL includes statements or commands that are used to interact with relational databases” —Vu at ¶ [0004]; and Vu at ¶¶ [0003], [0005], [0012]–[0013], [0029]–[0030], [0041], [0125], [0131]–[0145], [0163] and [0191]);
receiving, by the application, the SQL database query statement from the pre-trained LLM (e.g., “SQL is a standard database management language for interacting with relational databases. SQL can be used for storing, manipulating, retrieving, and… otherwise managing data held in a relational database management system (RDBMS)…. SQL includes statements or commands that are used to interact with relational databases” —Vu at ¶ [0004]; “a pretrained NL2LF model (as described herein a pretrained Large Language Model (LLM))” such as “a pretrained Text-to-SQL model” —Vu at ¶¶ [0041] and [0163]; and Vu at ¶¶ [0003], [0005], [0012]–[0013], [0029]–[0030], [0041], [0125], [0131]–[0145], [0163] and [0191]);
transmitting the SQL database query statement to the relational database (e.g., Vu at ¶¶ [0003], [0005], [0012]–[0013], [0029]–[0030], [0041], [0125], [0131]–[0145], [0163], [0167] and [0191]; “chatbots (referred to as skill bots) … interact with users and fulfill specific types of tasks, such as tracking inventory,… creating…reports, …checking a bank account… and the like” such as based on “business information… stored in …relational databases” —Vu at ¶¶ [0061] and [0028]); and
querying the relational database using the SQL database query statement to obtain information associated with the plurality (e.g., “natural language statements, queries, requests, and questions (i.e., sentences) can be transformed into a machine-oriented language” such as via “NL2LF system is powered by a deep learning model (e.g., a NL2LF model such as a LLM) configured to convert a natural language (NL) utterance (e.g., a query posed by a user using a digital assistant or chatbot) into a logical form, for example,…SQL…. If an intermediate database query language format is used then the intermediate database query language can be used to generate a query in a specific system query language (e.g., SQL), which can then be executed for querying a system such as a database to obtain an answer to the user's utterance” —Vu at ¶¶ [0005] and [0124]; “utterances… can be phrased as questions, commands, requests” such as “to track the real-time state of its business in order to quickly understand and diagnose any emerging issues, trends, or anomalies” —Vu at ¶¶ [0049] and [0028]; “Text-to-SQL model generates SQL queries…. the LLM would generate the …SQL query” —Vu at ¶ [0158]; “converting, using the trained machine learning model, the input natural language utterance to an output logical form based on the input natural language utterance and database schema information; executing the output logical form on a database corresponding to the database schema information to obtain a result; and providing the result to the user” and “the machine learning model is a large language model pretrained for a task of converting an input natural language utterance to an output logical form” —Vu at ¶¶ [0013] and [0012]; “chatbots (referred to as skill bots) … interact with users and fulfill specific types of tasks, such as tracking inventory,… creating…reports, …checking a bank account… and the like” such as based on “business information… stored in …relational databases” —Vu at ¶¶ [0061] and [0028]; “SQL is a standard database management language for interacting with relational databases. SQL can be used for storing, manipulating, retrieving, and… otherwise managing data held in a relational database management system (RDBMS)…. SQL includes statements or commands that are used to interact with relational databases” —Vu at ¶ [0004]; and Vu at ¶¶ [0003], [0005], [0012]–[0013], [0029]–[0030], [0041], [0125], [0131]–[0145], [0163], [0167] and [0191]), but Vu fails to disclose the plurality of business items including a plurality of Automated Teller Machines (ATMs). However, Herziger teaches “an ATM management application … provid[ing] an ATM operator with a comprehensive set of ATM management information…. The ATM management application can include…: a currency management module, a status inquiry module…. [and] other modules that perform management of other functions related to an ATM” —Herziger at ¶ [0009]; as well as receiving, by a terminal management application responsible for a plurality of business items including Automated Teller Machines (ATMs), a user-specific query requesting information associated with the plurality of the ATMs (e.g., “a system for managing an ATM…. accept a query from a user for data corresponding to … different currency amounts and to output data corresponding to the… different currency amounts to the user” —Herziger at ¶ [0012]; “As illustrated in FIG. 5, a status query screen 310 can be displayed that allows the user to define search criteria used to qualify which ATMs 20 the user would like to evaluate” —Herziger at ¶ [0057]; and Herziger at ¶ [0158]). Therefore, it would have been obvious to one skilled in the art, before the effective filing date of the claimed invention, to incorporate the plurality of business items including a plurality of Automated Teller Machines (ATMs), as taught by Herziger, into the method/system disclosed by Vu, which is directed toward “data-driven companies to track the real-time state of its business… to quickly understand and diagnose any emerging issues, trends, or anomalies” such as based on “financial business metrics” (e.g., Vu at ¶ [0028]) as well as end users interacting with chatbots, such as banking bots, to gain financial/business information (e.g., Vu at ¶ [0047]; “business analysts can extract information from their systems” —Vu at ¶ [0125]; and “chatbots (referred to as skill bots) … interact with users and fulfill specific types of tasks, such as tracking inventory,… creating…reports, …checking a bank account… and the like” —Vu at ¶ [0061]), because such incorporation would be applying a known technique to a known device (method, or product) ready for improvement to yield predictable results (see MPEP § 2143).
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Vu in view of Herziger as applied to Claim 1 above and Vu teaching transmitting the query data comprises transmitting message data indicative of the user-specific query and transmitting pre-defined system message data indicative of a pre-defined system message for enabling generation of said at least one database query statement (e.g., Vu at ¶¶ [0003], [0005], [0012]–[0013], [0029]–[0030], [0041], [0125], [0131]–[0145], [0163] and [0191]).
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Vu in view of Herziger as applied to Claim 2 above and Vu teaching providing the pre-defined system message as a message comprising information for a schema of the relational database (e.g., Vu at ¶¶ [0003], [0005], [0012]–[0013], [0029]–[0030], [0041], [0125], [0131]–[0145], [0163] and [0191]).
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Vu in view of Herziger as applied to Claim 2 above and Vu teaching providing the pre-defined system message as a message comprising information for a type of syntax to use for said at least one database query statement (e.g., Vu at ¶¶ [0003], [0005], [0012]–[0013], [0029]–[0030], [0041], [0125], [0131]–[0145], [0158], [0163] and [0191]).
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Vu in view of Herziger as applied to Claim 2 above and Vu teaching providing the pre-defined system message as a message comprising information for a relational mapping between entries in the relational database (e.g., Vu at ¶¶ [0003], [0005], [0012]–[0013], [0029]–[0030], [0041], [0050], [0125]–[0126], [0131]–[0145], [0158], [0162]–[0163] and [0191]).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Vu in view of Herziger as applied to Claim 2 above and Vu teaching providing the pre-defined system message as a message comprising information for at least one translated term to use for respective user inputted terminology (e.g., Vu at ¶¶ [0003], [0005], [0012]–[0013], [0029]–[0030], [0041], [0054], [0125]–[0126], [0131]–[0145], [0158], [0163] and [0191]).
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Vu in view of Herziger as applied to Claim 2 above and Vu teaching providing the pre-defined system message as a message comprising information for confidential entries in the relational database (e.g., Vu at ¶¶ [0003], [0005], [0012]–[0013], [0029]–[0030], [0041], [0125], [0131]–[0147], [0163] and [0191]).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Vu in view of Herziger as applied to Claim 2 above and Vu teaching receiving, by the terminal management application, the user-specific query as text data input via at least one user input device of a computing device of a user (e.g., “User inputs 110 are generally in a natural language form and are referred to as utterances. A user utterance 110 can be in text form, such as when a user types in a sentence, a question, a text fragment…” and “utterances… can be phrased as questions, commands, requests, and the like” such as “to track the real-time state of its business in order to quickly understand and diagnose any emerging issues, trends, or anomalies” —Vu at ¶¶ [0054], [0049] and [0028]; and Vu at ¶¶ [0045], [0052] and [0200]).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Vu in view of Herziger as applied to Claim 1 above and Vu teaching providing the at least one database query statement output from the pre-trained LLM in Structured Query Language (SQL) (e.g., “SQL is a standard database management language for interacting with relational databases. SQL can be used for storing, manipulating, retrieving, and… otherwise managing data held in a relational database management system (RDBMS)…. SQL includes statements or commands that are used to interact with relational databases” —Vu at ¶ [0004]; and Vu at ¶¶ [0003], [0005], [0012]–[0013], [0029]–[0030], [0041], [0125], [0131]–[0145], [0163] and [0191]).
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Vu in view of Herziger as applied to Claim 1 above and Vu teaching transmitting, by the terminal management application, the at least one database query statement to the relational database to query the relational database for said information associated with the plurality (e.g., Vu at ¶¶ [0003], [0005], [0012]–[0013], [0029]–[0030], [0041], [0125], [0131]–[0145], [0163], [0167] and [0191]; “chatbots (referred to as skill bots) … interact with users and fulfill specific types of tasks, such as tracking inventory,… creating…reports, …checking a bank account… and the like” such as based on “business information… stored in …relational databases” —Vu at ¶¶ [0061] and [0028]).
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Vu in view of Herziger as applied to Claim 11 above and Vu teaching receiving, by the terminal management application, results data comprising data indicative of said information associated with the plurality from the relational database (e.g., “chatbots (referred to as skill bots) … interact with users and fulfill specific types of tasks, such as tracking inventory,… creating…reports, …checking a bank account… and the like” such as based on “business information… stored in …relational databases” —Vu at ¶¶ [0061] and [0028]; “results are typically processed in the form of charts or graphs to enable users to quickly visualize the results and facilitate data-driven decision making” —Vu at ¶ [0028]; “obtain a result; and providing the result to the user” —Vu at ¶ [0013]; “generating a response to be output to the user responsive to the user utterance, outputting the response to the user” —Vu at ¶ [0057]; “enables a skill bot to output replies to user requests” based on “business information is stored in the form of relational databases that store, process, and retrieve data” —Vu at ¶¶ [0082] and [0028]; and “chatbots… to communicate interchangeably with both a human and various backend systems…using Structured Query Language (SQL)” and “chatbots (referred to as skill bots) … interact with users and fulfill specific types of tasks, such as tracking inventory,… creating…reports, …checking a bank account… and the like” —Vu at ¶¶ [0003] and [0061]).
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Vu in view of Herziger as applied to Claim 12 above and Vu teaching responsive to receiving the results data, transmitting the results data to a computing device of a user who provided the user-specific query (e.g., “chatbots (referred to as skill bots) … interact with users and fulfill specific types of tasks, such as tracking inventory,… creating…reports, …checking a bank account… and the like” such as based on “business information… stored in …relational databases” —Vu at ¶¶ [0061] and [0028]; “results are typically processed in the form of charts or graphs to enable users to quickly visualize the results and facilitate data-driven decision making” —Vu at ¶ [0028]; “obtain a result; and providing the result to the user” —Vu at ¶ [0013]; “generating a response to be output to the user responsive to the user utterance, outputting the response to the user” —Vu at ¶ [0057]; “enables a skill bot to output replies to user requests” based on “business information is stored in the form of relational databases that store, process, and retrieve data” —Vu at ¶¶ [0082] and [0028]; “chatbots… to communicate interchangeably with both a human and various backend systems…using Structured Query Language (SQL)” and “chatbots (referred to as skill bots) … interact with users and fulfill specific types of tasks, such as tracking inventory,… creating…reports, …checking a bank account… and the like” —Vu at ¶¶ [0003] and [0061]; “query posed by a user using a digital assistant or chatbot” and “A bot (also referred to as a skill, chatbot, chatterbot, or talkbot) is a computer program that can perform conversations with end users. The bot can generally respond to natural-language messages (e.g., questions or comments)….” —Vu at ¶¶ [0124] and [0045]; and Vu at ¶¶ [0045], [0052] and [0200]).
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Vu in view of Herziger as applied to Claim 13 above and Vu teaching displaying, on a display of the computing device, at least one result associated with the results data (e.g., Vu at ¶¶ [0045], [0052], [0200] and [0245]).
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Vu in view of Herziger as applied to Claim 14 above and Vu teaching displaying the at least one result in tabular format (e.g., “results are typically processed in the form of charts or graphs to enable users to quickly visualize the results and facilitate data-driven decision making” —Vu at ¶ [0028]; Vu at ¶¶ [0128]–[0129]; and Vu at ¶ [0140]–[0143]).
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Vu in view of Herziger as applied to Claim 1 above and Vu teaching providing the pre-trained LLM as a generative pre-trained transformer type LLM (e.g., Vu at ¶¶ [0003], [0005], [0012]–[0013], [0028]–[0030], [0041], [0124]–[0125], [0131]–[0145], [0158], [0163] and [0191]).
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Vu in view of Herziger as applied to Claim 1 above and Vu teaching providing the pre-trained LLM as a generative AI-based chatbot (e.g., Vu at ¶¶ [0003], [0005], [0012]–[0013], [0028]–[0030], [0041], [0124]–[0125], [0131]–[0145], [0158], [0163] and [0191]).
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Vu in view of Herziger as applied to Claim 1 above and Vu teaching inputting the user-specific query to a web-interface of a browser application executing on a computing device of a user (e.g., Vu at ¶¶ [0045], [0052] and [0200]); and receiving, by the terminal management application, the user-specific query from the computing device (e.g., “receiving an input natural language utterance from a user” such as “natural language statements, queries, requests, and questions (i.e., sentences)” —Vu at ¶¶ [0013] and [0005]; “query posed by a user using a digital assistant or chatbot” and “A bot (also referred to as a skill, chatbot, chatterbot, or talkbot) is a computer program that can perform conversations with end users. The bot can generally respond to natural-language messages (e.g., questions or comments)….” —Vu at ¶¶ [0124] and [0045]; “End users interact with the bot through conversational interactions… just as end users interact with other people… and the bot … asking the end user how it can help. End users also interact… with a banking bot that is …trained…” —Vu at ¶ [0047]; “User inputs 110 are generally in a natural language form and are referred to as utterances. A user utterance 110 can be in text form, such as when a user types in a sentence, a question, a text fragment…” and “utterances… can be phrased as questions, commands, requests, and the like” such as “to track the real-time state of its business in order to quickly understand and diagnose any emerging issues, trends, or anomalies” —Vu at ¶¶ [0054], [0049] and [0028]; and “chatbots (referred to as skill bots) … interact with users and fulfill specific types of tasks, such as tracking inventory,… creating…reports, …checking a bank account… and the like” such as based on “business information… stored in …relational databases” —Vu at ¶¶ [0061] and [0028]).
Regarding Claim 19, Vu in view of Herziger teaches a computing device comprising: at least one processor configured to execute a terminal management application configured (e.g., Figures 1-3 and 6-10 of Vu) to perform respective processes/steps as recited in Claim 1, and, therefore, Claim 19 is rejected on the same corresponding basis(es) as applied above with respect to Claim 1.
Regarding Claim 20, Vu in view of Herziger teaches a non-transitory computer-readable medium instructions which, when executed by a computing device, cause the computing device (e.g., Figures 1-3 and 6-10 of Vu) to carry out respective method processes/steps as recited in Claim 1, and, therefore, Claim 20 is rejected on the same basis(es) as applied above with respect to Claim 1.
Response to Arguments
Applicant’s arguments in the Amendment filed on April 27, 2026, have been fully considered and are not persuasive. Examiner notes further recitation above to U.S. Patent Application Publication No. 2026/0037505 (“Vu”) in an effort to assist Applicant given Applicant’s amendments and arguments in “Amendment”.
Applicant's Arguments in the Amendment
(Pages 7-9) Applicant asserts that the pending claims, as currently amended, are drawn to eligible subject matter under 35 U.S.C. § 101.
(Pages 10-14) Applicant asserts that independent Claims 1 and 19, as currently amended, are patentable over a combination of U.S. Patent Application Publication Nos. 2026/0037505 (“Vu”) and 2002/0082994 (“Herziger”). “Claim 19…includes a processor which performs the same method steps included in claim 1” per bottom of page 10 of the Amendment.
(Bottom of Page 9 and on Page 14) Applicant asserts that Claims 2-18 and 20 depend on Claim 1, and include respective limitations therein, and are patentably distinguishable over Vu in view of Herziger based on at least the same reasons provided with respect to Claim 1.
Examiner’s Response to Applicant's Arguments
Please see updated/modified § 101 rejections above regarding pending claims being drawn to ineligible subject matter in view of considering all relevant factors with respect to each claim as a whole including amended portions of the independent claims.
Regarding Applicant’s § 101 arguments, Examiner notes that a human being, without the aid of a computer of any kind, could perform a particular way of “generation of executable SQL queries from natural language input” (quoted from page 8 of Applicant’s April 2026 Amendment), such as “to translate natural language queries into executable database queries” via “executable SQL statements” (quoted from page 8 of Applicant’s April 2026 Amendment). Applicant argues the “present claims… address a technological problem… namely, the difficulty of allowing users to query structured relational databases” when those users do not have “knowledge of database schemas or SQL syntax” (quoted from top of page 9 of Applicant’s April 2026 Amendment). Furthermore, regarding Applicant’s argument that “The present claims similarly address a technological problem …, namely, the difficulty of allowing users to query structured relational databases without specialized knowledge of database schemas or SQL syntax, and solve that problem…” (see page 9 of Applicant's April 2026 Amendment), Examiner notes that, unlike DDR Holdings, 773 F.3d 1245 (Fed. Cir. 2014), Applicant’s pending claims do not disclose any improvement or inventive concept rooted in technology. Examiner notes that the basic function(s) of “generation of executable SQL queries from natural language input” (page 8 of April 2026 Amendment) and “translat[ing] natural language queries into executable database queries” via “executable SQL statements” (page 8 of April 2026 Amendment) is readily within the ability of a human to perform without computer aid — i.e. a mere application of an abstract concept to a technological field. Examiner notes that the prohibition against patenting abstract ideas cannot be circumvented by limiting the use of the idea to a particular technological environment, such as “a terminal management environment” (page 7 of Applicant’s April 2026 Amendment) or “an ATM management environment” (page 9 of April 2026 Amendment). Merely adding a computer to perform mental steps does not transform patent-ineligible matter into patent-eligible matter. Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). Thus, based upon consideration of all relevant factors with respect to each claim as a whole, the pending claims are drawn to ineligible subject matter and, therefore, are rejected under 35 U.S.C. 101.
Regarding § 103, please see citations to prior art references of U.S. Patent Application Publication Nos. 2026/0037505 (“Vu”) and 2002/0082994 (“Herziger”) in the § 103 rejections above regarding amended portions of Applicant’s claims. Examiner notes that during patent examination, the pending claims must be “given their broadest reasonable interpretation”. In view of this standard, Examiner asserts § 103 rejections to Applicant’s amended claims, as noted above under § 103. In addition, Examiner notes that patent documents are relevant as prior art for all they contain and that “[a] reference may be relied upon for all that it would have reasonably suggested to one having ordinary skill the art, including nonpreferred embodiments” —MPEP § 2123.
Please see above § 103 rejections with respect to independent Claim 1 for at least the same reasons provided with respect to Claim 1 that Claims 2-18 and 20, depending from Claim 1 and including the limitations therein, are not patentable based on dependency from an independent claim.
Conclusion
The following references are considered pertinent to Applicant's disclosure, and are being made of record albeit the references are not relied upon as a basis for rejection in this Office action:
U.S. Patent No. 12,394,283 issued to Mattison et al. (hereinafter “Mattison ‘283”) for “Generative Artificial Intelligence-based Automated Teller Machine Operation Control” —Title of Mattison ‘283.
U.S. Patent Application Publication No. 2026/0030277 of AGARWAL et al. (hereinafter “Agarwal”) which is classified under CPC classification G06F 16/24522.
U.S. Patent Application Publication No. 2025/0371503 of Horgan et al. (hereinafter “Horgan”)
U.S. Patent Application Publication No. 2025/0371050 of Kasha et al. (hereinafter “Kasha”)
U.S. Patent Application Publication No. 2024/0362278 of PerezLeon et al. (hereinafter “PerezLeon”).
U.S. Patent Application Publication No. 2024/0312317 of Mattison et al. (hereinafter “Mattison”) for “REMOTE VALIDATION OF AUTOMATED TELLER MACHINES (ATMs) USING MACHINE LEARNING” —Title of Mattison.
International Publication No. WO/2024/044475 of TANGARI et al. (hereinafter “Tangari”) having an international filing date of 10 August 2023.
See 2023 IEEE publication included with this final Office action.
See 2022 IEEE publication included with this final Office action.
THIS ACTION IS MADE FINAL. 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 extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Mathew Syrowik whose telephone number is 313-446-4862. The examiner can normally be reached on Monday through Friday 8:30 AM to 4:00 PM (Eastern Time). If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Waseem Ashraf, can be reached at telephone number 517-270-3948. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Mathew Syrowik/ Primary Examiner, Art Unit 3621
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