DETAILED ACTION
This is responsive to the amendment filed 22 May 2026.
Claims 1-3, 7-14 and 17-20 are currently pending and considered below.
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 .
Response to Arguments
Applicant's arguments filed 22 May 2026 regarding the 35 USC 101 rejections have been fully considered but they are not persuasive.
Applicant argues:
Applicant notes that the "decision system" and "large language model" on pages 3 and 4 of the Office Action are not included in the defined 2019 PEG classification of "Certain methods of organizing human activity", "commercial or legal interactions" or "managing personal behavior or relationships between people". The 2019 PEG states that "Claims that do not recite matter that falls within these enumerated groupings of abstract ideas should not be treated as reciting abstract ideas". (2019 PEG, page 53). Applicant submits that the pending claims do not recite the subject matter described in the enumerated groupings above. Instead, the pending claims recite limitations to:
…
which is not an abstract idea that falls within any of the groupings defined by the 2019 Revised Guidance.
The Examiner respectfully disagrees. Other than reciting generic computer components such as "decision system" and "large language model" nothing in the claims precludes the steps from practically being performed in the mind. For example, a person may extract textual data from a document (e.g. a human may read an email and extract the body of the email); obtain features based on at least one identifier that is an indication of a person's identity who is associated with the document and an indication of how often there are communications with the identified person, wherein the information is obtained from an organizational database (e.g. a human may such features and/or indication from a database); provide a scalar indication for each of a plurality of features of the textual data (e.g. a human may count a plurality of features such as spelling errors); and produce an output based on at least the scalar indications (e.g. a human may determine that the email is spam based on the count of spelling errors).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Applicant further argues:
The 2019 Revised Guidance provides that one consideration which is indicative of a practical application of a judicial exception is "An additional element [that] reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field". (2019 PEG, page 55). Applicant submits that the pending claims recite limitations for an improvement in a computer-related technology. Namely, the pending claims are directed to improvements to an automated document analysis method or an automated system for "blocking transmission of or allowing access to the document based in part on the output". For example, claim 1 includes the limitations of:
"utilise a decision system to produce an output based on at least the scalar
indications; and
blocking transmission of or allowing access to the document based in part on the output". These limitations are an improvement to a method or system for document analysis or processing documents using machine learning combined with an LLM to determine whether a document should be blocked or allowed. More specifically, the claimed limitations for processing documents are an improvement to a technology because the claimed elements enable improvements to document analysis and decisions systems. Therefore, the pending claims are a practical application of the asserted judicial exception because the pending claims, when considered as a whole, include additional elements that reflect an improvement to a computer- related technology. Therefore, the pending claims are directed to a patent-eligible concept under 35 U.S.C. § 101 and should be allowed.
However, producing an output based on at least the scalar indication may be a mental process and was shown as such above. The claims recite the additional elements – a “computer system for document analysis, comprising: one or more computer readable storage media storing program instructions and one or more processors which, in response to executing the program instructions, are configured to”, a “large language model” and a “decision system” (claim 1), a “computer-implemented method, comprising the steps of at a computer system comprising one or more computer readable storage media and one or more processors”, a “large language model” and a “decision system” (claim 14) which are recited at a high-level of generality (i.e., as generic processors performing generic computer functions) such that they amount to no more than mere instructions to apply the exception using a generic computer components.
The claims also recite the additional elements “receive a document” and “block transmission of or allow access to the document based in part on the output”. The claims do not impose any limits on how the document is received or how the transmission is blocked or the access granted. In other words, the claims recite only the idea of a solution or outcome i.e., the claims fail to recite details of how a solution to a problem is accomplished. These limitations therefore represent extra-solution activity because they are mere nominal or tangential addition to the claims. Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are therefore directed to an abstract idea.
Applicant also argues:
The arrangement of non-conventional and non-generic limitations in the pending claims amount to an inventive concept that confine the pending claims to a particular useful application.
Specifically, the claim 1 limitations of:
…
recite a non-conventional and non-generic way to provide document analysis for blocking or allowing of access to a document based on the output of the LLM and the machine learning. Specifically, using the LLM to provide a scalar indication and a decision system (e.g., machine learning) to produce an output in order to block or allow access to the document is not a routine conventional activity in the field of document analysis and access.
Furthermore, the amended claim language does recite a particular useful application where "blocking transmission of or allowing access to the document based in part on the output". The specification provides the example of an email (i.e., document) being blocked or allowed based on the output.
However, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. As stated above, the claims recite the additional limitations of a “computer system for document analysis, comprising: one or more computer readable storage media storing program instructions and one or more processors which, in response to executing the program instructions, are configured to”, a “large language model” and a “decision system” (claim 1), a “computer-implemented method, comprising the steps of at a computer system comprising one or more computer readable storage media and one or more processors”, a “large language model” and a “decision system” (claim 14). However, these are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications (see Applicant’s specification [0030]-[0034] and [0036]-[0037]). Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system.
The claims also recite the additional elements “receive a document” and “block transmission of or allow access to the document based in part on the output”. The claims do not impose any limits on how the document is received or how the transmission is blocked or the access granted. In other words, the claims recite only the idea of a solution or outcome i.e., the claims fail to recite details of how a solution to a problem is accomplished.
These limitations represent the extra-solution activity of gathering data, blocking document transmission and granting document access which are well-understood, routine and conventional activities. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are not patent eligible.
Applicant finally argues:
The present claims can also be compared to the 2024 PEG Example 47, claim 3, which has been incorporated into the MPEP, that is directed to "Anomaly Detection". In Example 47, "The claim recites the additional elements of "(d) detecting a source address associated with the one or more malicious network packets," "(e) dropping the one or more malicious network packets," and "(f) blocking future traffic from the source address." The claim also recites that limitation (a) is performed by a computer." The present claims recite "blocking transmission of or allowing access to the document based in part on the output" which is analogous to Example 47's "dropping of malicious network packets."
However, "(d) detecting a source address associated with the one or more malicious network packets," "(e) dropping the one or more malicious network packets," and "(f) blocking future traffic from the source address" is significantly different than merely "blocking transmission of or allowing access to the document based in part on the output". First, “allow access” may be simply represent an interpersonal action where, for example, one person may give permission to another to read an a particular email. As such “allow access” is not necessarily a technological step. Second, in example 47, claim 3 does more than merely state a desired result as the current claims do. It claims detecting a source address, dropping a malicious packet and blocking future traffic from source address. Further, the specification expressly the resulting technical improvement in network intrusion detection/security i.e. proactive, real-time remediation without the need to wait for an administrator. On the other hand, the current claims use the result of an abstract analysis (i.e. output) to make and access-control decision.
All of Applicant’s arguments regarding the 35 USC 101 rejections have been considered and they are unpersuasive.
Applicant’s arguments with respect to claims 1-3, 7-14 and 17-20 regarding the 35 USC 103 rejections have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(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.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-3, 7-14 and 17-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation "the information" in line 9. The limitation lacks proper antecedent basis in the claim. According to cancelled claim 6, the limitation will be interpreted as ‘the indication’.
Claim 14 suffers from the same deficiency and is likewise rejected.
The dependent claims are rejected for depending upon a rejected claim without providing a remedy.
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 1-3, 7-14 and 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more. The judicial exception is not integrated into a practical application.
In claims 1 and 14, the limitations
That is, other than reciting a “computer system for document analysis, comprising: one or more computer readable storage media storing program instructions and one or more processors which, in response to executing the program instructions, are configured to”, a “large language model” and a “decision system” (claim 1), a “computer-implemented method, comprising the steps of at a computer system comprising one or more computer readable storage media and one or more processors”, a “large language model” and a “decision system” (claim 14) nothing in the claims precludes the steps from practically being performed in the mind. For example, a person may extract textual data from a document (e.g. a human may read an email and extract the body of the email); obtain features based on at least one identifier that is an indication of a person's identity who is associated with the document and an indication of how often there are communications with the identified person, wherein the information is obtained from an organizational database (e.g. a human may such features and/or indication from a database); provide a scalar indication for each of a plurality of features of the textual data (e.g. a human may count a plurality of features such as spelling errors); and produce an output based on at least the scalar indications (e.g. a human may determine that the email is spam based on the count of spelling errors).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements – a “computer system for document analysis, comprising: one or more computer readable storage media storing program instructions and one or more processors which, in response to executing the program instructions, are configured to”, a “large language model” and a “decision system” (claim 1), a “computer-implemented method, comprising the steps of at a computer system comprising one or more computer readable storage media and one or more processors”, a “large language model” and a “decision system” (claim 14) which are recited at a high-level of generality (i.e., as generic processors performing generic computer functions) such that they amount to no more than mere instructions to apply the exception using a generic computer components.
The claims also recite the additional elements “receive a document” and “block transmission of or allow access to the document based in part on the output”. The claims do not impose any limits on how the document is received or how the transmission is blocked or the access granted. In other words, the claims recite only the idea of a solution or outcome i.e., the claims fail to recite details of how a solution to a problem is accomplished. These limitations therefore represent extra-solution activity because they are mere nominal or tangential addition to the claims. Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are therefore directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. As stated above, the claims recite the additional limitations of a “computer system for document analysis, comprising: one or more computer readable storage media storing program instructions and one or more processors which, in response to executing the program instructions, are configured to”, a “large language model” and a “decision system” (claim 1), a “computer-implemented method, comprising the steps of at a computer system comprising one or more computer readable storage media and one or more processors”, a “large language model” and a “decision system” (claim 14). However, these are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications (see Applicant’s specification [0030]-[0034] and [0036]-[0037]). Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system.
The claims also recite the additional elements “receive a document” and “block transmission of or allow access to the document based in part on the output”. The claims do not impose any limits on how the document is received or how the transmission is blocked or the access granted. In other words, the claims recite only the idea of a solution or outcome i.e., the claims fail to recite details of how a solution to a problem is accomplished.
These limitations represent the extra-solution activity of gathering data, blocking document transmission and granting document access which are well-understood, routine and conventional activities. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are not patent eligible.
Moreover, see Recentive Analytics, Inc. v. Fox Corp. (Fed. Cir. April 18, 2025)- “Machine learning is a burgeoning and increasingly important field and may lead to patent-eligible improvements in technology. Today, we hold only that patents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under § 101.”
The dependent claims, when analyzed as a whole, are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations fail to establish that the claims are not directed to an abstract idea.
The dependent claims recite:
wherein the decision system comprises a machine learning model;
wherein the decision system comprises a rules-based system;
wherein the document is an email and the textual data comprises the text body of the email;
wherein at least one of the scalar indications is an indication of the quantity of content relating to a feature;
wherein at least one of the scalar indications is an indication of the strength of language in relation to a feature;
wherein the at least one feature of the textual data include at least one of the urgency of language used, spelling accuracy, pressure applied to recipient to take certain action, language which appears disingenuous, offers which are “too good to be true”, and attempts to sell products;
wherein the step of requesting a scalar indication comprises requesting a plurality of scalar indications from the large language model for at least one of the features, wherein each of the plurality of scalar indications are requested using a different form of a question;
wherein the decision system utilises the average, minimum or maximum of the plurality of scalar indications for a feature;
wherein the step of requesting a scalar indication comprises requesting the large language model to verify a deliberately false scalar indication to verify confidence in a scalar indication provided by the large language model.
The additional recited limitations further narrow the steps of the independent claims without however providing “a practical application of” or "significantly more than" the underlying “Mental Processes” abstract idea. Therefore, the dependent claims are also not patent eligible.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-3, 7-9, 11, 14, 17 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Schweighauser et al. (US 2019/0222606) in view of Sambamoorthy et al. (US 2022/0279015) and Qadrud-Din et al. (US 11,995,411).
Claim 1:
Schweighauser discloses a computer system for document analysis, comprising:
one or more computer readable storage media storing program instructions and one or more processors which, in response to executing the program instructions ([0038]), are configured to:
receive a document (“As soon as one or more new/incoming messages or emails have been sent internally by one user within the entity 114 from an email account on the electronic messaging system 116 to another user within the entity 114, the message collection and analysis component 106 of the AI engine 104 is configured to collect such new electronic messages sent”, [0018]);
extract textual data from the document (“the message collection and analysis component 106 is configured to use the unique communication patterns identified to examine and extract various features or signals from the collected electronic messages”, [0020]);
obtain features based on at least one identifier that is an indication of a person's identity who is associated with the document (“the electronic messages are examined for one or more of names or identifications of sender and recipient(s)”, [0020]);
request an AI model to provide a scalar indication for each of a plurality of features of the textual data (“The fraud detection component 108 is then configured to utilize one or more of the following features and/or criteria that are unique to the email account to make a determination of whether the email account has been compromised (e.g., taken over by an attacker) or not: … Number of embedded links in the email sent by the email account; … Length of the longest URL in the email sent by the email account”, [0021]-[0024], see also “the fraud detection component 108 is configured to compute term frequency-inverse document frequency (TF-IDF) of each word offline”, [0028]);
utilise a decision system to produce an output based on at least the scalar indications; and block transmission of or allow access to the document based in part on the output (“If the fraud detection component 108 determines that the email account has been compromised, it is configured to block (remove, delete, modify) or quarantine electronic messages sent from the compromised email account in real time, and automatically notify the user, intended recipient(s) of the electronic message and/or an administrator of the electronic communication system 116 of the email account takeover attack”, [0034]).
Schweighauser does not explicitly disclose obtaining an indication of how often there are communications with the identified person, wherein the indication is obtained from an organizational database.
In an analogous art similarly detecting fraudulent email, Sambamoorthy discloses obtaining an indication of how often there are communications with the identified person, wherein the indication is obtained from an organizational database (“the computer system queries the historical email signal database—containing email signal containers of past emails inbound to and outbound from the organization—for a set of email signal containers containing the sender and recipient email addresses of the current email. The computer system can then calculate a total count of emails, a total count of email threads, and/or frequency of emails (e.g., a number of emails sent per day, week, or month) previously exchanged between the sender and recipient email addresses prior to the current email”, [0055]).
It would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention to combine the references to yield the predictable result of obtaining an indication of how often there are communications with Schweighauser’s identified person, wherein the indication is obtained from an organizational database because such information were known to help identify high risk email from a particular person/sender (see, Sambamoorthy “if the total count of emails previously exchanged between the sender and recipient email addresses is null, the computer system can predict a very-high risk of an attack attempt within the email. Similarly, if no emails were exchanged between the sender and recipient email addresses until the preceding 24-hour period in which multiple emails were sent from the sender email address to the recipient email address, the computer system can predict a high risk of an attack attempt within the email. Similarly, if the frequency of emails previously exchanged between the sender and recipient email addresses over a long period of time is low (e.g., two emails per year) but the count of emails exchanged between the sender and recipient email addresses within a recent short period of time is relatively high (e.g., three emails within the past 24 hours), the computer system can predict a moderate risk of an attack attempt within the email”, [0056]).
Schweighauser does not explicitly disclose that the AI model is a large language model.
In an analogous art similarly using an AI model to provide a scalar indication for textual data, Qadrud-Din discloses that the AI model is a large language model (“one or more of the relevance scores may be determined based on communication with a remote text generation modeling system”, col. 5, lines 27-30, see also “the text generation model 276 may be a large language model”).
It would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention to combine the references to yield the predictable result of implementing Schweighauser’s AI model as an LLM because LLMs were a known implementation choice for natural language processing and provided a predictable tool in text processing generating excellent results in fields such as text analysis and classification.
Claim 2:
Schweighauser in view of Sambamoorthy and Qadrud-Din discloses a computer system according to claim 1, wherein the decision system comprises a machine learning model (Schweighauser, [0034], note that an AI module is a machine learning model).
Claim 3:
Schweighauser in view of Sambamoorthy and Qadrud-Din discloses a computer system according to claim 1, wherein the decision system comprises a rules-based system (Schweighauser, [0029], note “If a certain domain has been seen in internal communications often during a short period of time, it is deemed to be legitimate” represents an "if-then" rule).
Claim 7:
Schweighauser in view of Sambamoorthy and Qadrud-Din discloses a computer system according to claim 1, wherein the document is an email and the textual data comprises the text body of the email (Schweighauser, [0018]).
Claim 8:
Schweighauser in view of Sambamoorthy and Qadrud-Din discloses a computer system according to claim 1, wherein at least one of the scalar indications is an indication of the quantity of content relating to a feature (Schweighauser, [0021]-[0024]).
Claim 9:
Schweighauser in view of Sambamoorthy and Qadrud-Din discloses a computer system according to claim 1, wherein at least one of the scalar indications is an indication of the strength of language in relation to a feature (Schweighauser, [0024]).
Claim 11:
Schweighauser in view of Sambamoorthy and Qadrud-Din discloses a computer system according to claim 1, wherein the step of requesting a scalar indication comprises requesting a plurality of scalar indications from the large language model for at least one of the features, wherein each of the plurality of scalar indications are requested using a different form of a question (Schweighauser, “maintain a score for each word wherein the score represents the likelihood of the word to be associated with malicious (phishing) emails. In some embodiments, the fraud detection component 108 is configured to compute term frequency-inverse document frequency (TF-IDF) of each word offline”, [0028]).
Claims 14-17 and 19:
Schweighauser in view of Sambamoorthy and Qadrud-Din discloses a computer-implemented method, comprising the steps of at a computer system comprising one or more computer readable storage media and one or more processors (Schweighauser, [0010]) for executing the steps performed by the system of claims 1, 4-5, 7 and 11 as shown above.
Conclusion
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/SAMUEL G NEWAY/Primary Examiner, Art Unit 2657
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