DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
The following claim(s) is/are pending in this office action: 1-20
The following claim(s) is/are amended: -
The following claim(s) is/are cancelled: -
The following claim(s) is/are new: -
Claim(s) 1-20 is/are rejected. This rejection is FINAL.
Previous Rejections Withdrawn
The 35 USC 112(b) rejection to claim(s) 8, 18 is/are withdrawn based on the amendment.
Response to Arguments
Applicant's arguments filed in the amendment filed 8/25/2026, have been fully considered but they are not persuasive. The reasons are set forth below.
Applicant’s Invention as Claimed
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.
Claim(s) 9 and 20 is/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 pre-AIA the applicant regards as the invention.
Claim 9 claims “comprehensive documentation.” The term “comprehensive” is ambiguous and the boundary between “comprehensive” and non-comprehensive is unclear.
Claim limitation “means for periodically accessing,” “means for updating,” “means for selecting enterprise data” and “means for responding” in Claim 20 invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. Applicant provides no algorithm for the functionalities claimed. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph. Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
The above cited rejections are merely exemplary.
The Applicant(s) are respectfully requested to correct all similar errors.
Claims not specifically mentioned are rejected by virtue of their dependency.
Claim Rejections - 35 USC § 103
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, 3-4, 11, 13-14, and 20 are rejected under 35 U.S.C. 103(a) as being unpatentable over Garrison (US Pub. 2022/0200928) in view of Mermoud (US Pub. 2025/0150321), and further in view of Mammen (US Pub. 2023/0351105).
With respect to Claim 1, Garrison teaches a method, comprising: periodically accessing Information Technology (IT) telemetry data from a plurality of disparate IT platforms (paras. 20-22; network equipment sends telemetry data of their operational status. Paras. 18-19, 23, 26-27; data is sent from disparate data sources, such as multiple enterprise sites. para. 22; continuous update of operational status and configurations.)
including a plurality of servers, network devices, and applications, (para. 20; any number of servers, controllers, endpoint or user devices, virtual machines, operating systems, security software and other software products.)
the IT telemetry data associated with metrics, alerts, and infrastructure configurations (para. 22; data about the operational status. para. 44; faults and errors. para. 22; configurations)
for monitoring and troubleshooting an enterprise IT system; (para. 37; system provides contextual insights for troubleshooting. Para. 39; contextual alerts. Para. 44; monitoring products to get telemetry.)
updating an enterprise IT telemetry structured database using the IT telemetry data from the plurality of disparate IT platforms, (para. 22; continuous update of operational status. Para. 26-37, 119; integrated data from multiple sources.)
selecting enterprise data to provide to a Large Language Model (LLM), wherein selected enterprise data includes access to the IT telemetry structured database, wherein the LLM generates a plurality of schematic inferences from the IT telemetry structured database; (A large language model will be taught later. para. 46-49; AI/ML used for generating insights. Para. 51; enterprise data is filtered to only include data and content relevant to a particular use case. Paras. 92-100; system applies context and filters content related to troubleshooting of the particular network resources. See also paras. 114-115, 122-124; system receives a use case input by a network operator such as a troubleshooting. The system generates a security alert or a support guide related to configuring the device.)
and responding to a first query regarding the enterprise IT system from an enterprise IT administrator using the LLM and the IT telemetry structured database. (para. 41, 100-101; system generates support guide and presents it to user.)
But Garrison does not explicitly teach a Large Language Model.
Mermoud, however, does teach the IT telemetry data associated with log files, system traces, (para. 59; troubleshooting using telemetry data and logs. para. 89; traces.)
a Large Language Model (LLM), (para. 14; LLM-based troubleshooting.)
It would have been obvious to one of ordinary skill prior to the effective filing date to combine the method of Garrison with the Large Language Model in order to make network monitoring and troubleshooting less complex. (Mermoud, paras. 58-63)
But modified Garrison does not explicitly teach the IT telemetry structured database including only data identified as non-confidential.
Mammen, however, does teach the IT telemetry structured database including only data identified as non-confidential; (para. 53; system identifies confidential and non-confidential data and segregates it. AI/ML may use only non-confidential data.)
It would have been obvious to one of ordinary skill prior to the effective filing date to combine the method of Garrison with the only non-confidential data in order to protect user’s privacy. (Mammen, para. 53)
With respect to Claim 3, modified Garrison teaches the method of claim 1, and Mermoud also teaches wherein a first subset of the IT telemetry data is selected based on the first query from the enterprise IT administrator. (paras. 35-36; machine learning takes performance indicator as input. Telemetry is presented to model to train it. paras. 63-65; recipes are used to provide context to troubleshoot a network issue. para. 89-90; telemetry data is used to generate recipe. Paras. 68, 74, 106-109; user prompts, which causes lookup of recipe, which is used to troubleshoot. See also Garrison, para. 44; telemetry includes operational states. Paras. 111, 126; telemetry of asset used in solving issue or making recommendation.)
The same motivation to combine as the independent claim applies here.
With respect to Claim 4, modified Garrison teaches the method of claim 1, and Mermoud also teaches wherein a second subset of the IT telemetry data is selected based on a first response to the first query from the enterprise IT administrator. (paras. 63-65; recipes are used to provide context to troubleshoot a network issue. Paras. 80-90; system may automatically generate recipes by reviewing materials or observing telemetry. Para. 98-104, 109; system may track performance of recipes or request recipes when it does not have a good response. Paras. 68-69; system performs learning to discover root cause of an issue. Therefore, the system provides improved responses using different analysis and data (a second subset) based upon how a previous query performed.)
The same motivation to combine as the independent claim applies here.
With respect to Claim 11, it is substantially similar to Claim 1 and is rejected in the same manner, the same art and reasoning applying. Further, Garrison also teaches a computing system, comprising: an input interface configured to (para. 132; network I/O interface to connecting to other systems. Para. 133; I/O interface to input device)
a processor configured to (para. 129; processor)
and an output interface configured to (para. 133; computer monitor)
With respect to Claims 13-14, they are substantially similar to Claims 3-4, respectively, and are rejected in the same manner, the same art and reasoning applying.
With respect to Claim 20, it is substantially similar to Claim 1 and is rejected in the same manner, the same art and reasoning applying. Further, Garrison also teaches a server, comprising: (para. 24; server)
Claims 2, 5-10, 12 and 15-19 are rejected under 35 U.S.C. 103(a) as being unpatentable over Garrison (US Pub. 2022/0200928) in view of Mermoud (US Pub. 2025/0150321), in view of Mammen (US Pub. 2023/0351105) and further in view of Arye (US Pub. 2018/0246950).
With respect to Claim 2, modified Garrison teaches the method of claim 1, but does not explicitly teach PostgreSQL Foreign Data Wrappers.
Arye, however, does teach wherein the IT telemetry data is accessed using PostgreSQL Foreign Data Wrappers (FDWs). (para. 37; PostgreSQL FDW for communications with a database.)
It would have been obvious to one of ordinary skill prior to the effective filing date to combine the method of modified Garrison with the PostgreSQL Foreign Data Wrappers in order to build a scalable database. (Arye, paras. 2-4, 11, 37)
With respect to Claim 5, modified Garrison teaches the method of claim 1, but does not explicitly teach Foreign Data Wrappers.
Arye, however, does teach wherein Foreign Data Wrappers (FDWs) are used to dynamically schematize the IT telemetry data into the IT telemetry structured database. (para. 37; PostgreSQL FDW for communications with a database. para. 103; to scale queries the database creates a virtual hypertable and a schema for the hypertable. Para. 108; dynamic creation of chunks for hypertable.)
It would have been obvious to one of ordinary skill prior to the effective filing date to combine the method of modified Garrison with the PostgreSQL Foreign Data Wrappers in order to build a scalable database. (Arye, paras. 2-4, 11, 37)
With respect to Claim 6, modified Garrison teaches the method of claim 5, and Arye also teaches wherein the FDWs are used to generate dynamic virtual tables and create the IT telemetry structured database. (para. 49; virtual table. Para. 103; hypertable.)
The same motivation to combine as the parent claim applies here.
With respect to Claim 7, modified Garrison teaches the method of claim 6, and Arye also teaches wherein a first FDW is associated with a first external data source and a second FDW is associated with a second external data source. (para. 3-4; different sources may contribute data and conventional systems are insufficient. Para. 11, 32; partitioned database system solves problem and scales using hypertables. Paras. 32, 40-42; hypertable is partitioned by dimensions that may include an identifier for objects or entities. See also Garrison, paras. 18-19, 23, 26-27; data is sent from disparate data sources, such as multiple enterprise sites. paras. 40, 48; data from multiple domains. See also Mermoud, para. 60; interfacing with external systems and domain-specific use cases.)
The same motivation to combine as the parent claim applies here.
With respect to Claim 8, modified Garrison teaches the method of claim 7, and Arye also teaches wherein the first FDW allows for on-the-fly schema generation and transformation. (para. 9; schemas do not need to be predefined. Paras. 32, 34; creation of hypertable with schema with parameters. Different chunks of the same hypertable can have different schemas. Para. 103; altering of schema. Para. 108; dynamic creation of chunks. Para. 116; alteration of chunk size at runtime and modification of schema.)
The same motivation to combine as the parent claim applies here.
With respect to Claim 9, modified Garrison teaches the method of claim 8, and Garrison also teaches wherein a repository of domain-specific information (paras. 18-19, 23, 26-27; data is sent from disparate data sources, such as multiple enterprise sites. paras. 40, 48; data from multiple domains. See also Mermoud, para. 60; interfacing with external systems and domain-specific use cases.)
including best practices, (para. 111; contextual help resources for best practices.)
troubleshooting guides, (para. 47, 92; use cases for troubleshooting and troubleshooting contextual data. Para. 63; troubleshooting related advisories.)
and comprehensive documentation is provided along with IT telemetry data. (paras. 28, 32; product and service guides and product documentation. para. 46; instruction and user manuals. Para. 27; telemetry data.)
With respect to Claim 10, modified Garrison teaches the method of claim 9, and Mermoud also teaches wherein the IT telemetry structured database and the LLM are provided as Software as a Service (SaaS) (paras. 42-45, 50; SAAS for providing services.)
The same motivation to combine as the independent claim applies here.
And Garrison also teaches connected to a Virtual Private Cloud (VPC). (paras. 21-22; cloud portal in a cloud-based infrastructure. Para. 142; virtual private network. In the event this does not render a VPC obvious, Examiner takes official notice of VPCs and it would have been obvious to one of ordinary skill prior to the effective filing date to provide the LLM as a SAAS via a VPC in order to improve the security of communications by utilizing a private channel.)
With respect to Claims 12, 15-18, they are substantially similar to Claims 2, 5-8, respectively, and are rejected in the same manner, the same art and reasoning applying.
With respect to Claim 19, it is substantially similar to Claim 10, except missing the subject matter of Claim 9. It is rejected in the same manner, the same art and reasoning applying.
Remarks
Applicant argues at Remarks, pg. 5 that Claims 8/18, 9, and 20 are not indefinite. With respect to Claims 8/18, Examiner agrees and withdraws the rejection.
With respect to Claim 9, Applicant argues that “comprehensive documentation, in context, simply refers to the documentation category within a described repository of domain-specific troubleshooting materials, parallel to ‘best practices’ and ‘troubleshooting guides’ in the same clause.” Examiner disagrees this is a reasonable interpretation. Claim 9 stats “wherein a repository of domain-specific information including best practices, troubleshooting guides, and comprehensive documentation is provided along with IT telemetry data.” The word “comprehensive” limits the word “documentation.” Applicant’s argument that “comprehensive documentation” “simply refers to the documentation category” reads the word “comprehensive” out of the claim, because “documentation” standing by itself refers to the documentation category.
With respect to Claim 20, Applicant does not dispute the claims invoke means-plus, but argues that the structure for the functions are disclosed. Applicant then points to things that are not sufficient structure because the described structure of special purpose computer functionality requires disclosure of the algorithm that achieves the function, and Applicant does not point to algorithms. Applicant apparently asserts the limitation “means for selecting enterprise data to provide to a Large Language Model (LLM), wherein selected enterprise data includes access to the IT telemetry structured database, wherein the LLM generates a plurality of schematic inferences from the IT telemetry structured database” is described by “the data-selection function is performed by the described structured vector augmented generation component that filters and provides selected schematized data to the LLM.” But obviously “component” is not structure that describes an algorithm, and “filter and provides selected schematized data to the LLM” is just a restatement of the function of “selecting enterprise data to provide to a LLM…wherein the LLM generates a plurality of schematic inferences from the IT telemetry structured database.” Similarly, the description of the query-response function is that it is “performed by the described structured LLM in conjunction with the IT telemetry structured database” which is no description of how the function is performed at all, it is merely a statement of what components perform it. The description of “the periodic telemetry-access function” is similar in that it is only described by the components that perform it. The description of “creating virtual tables in a PostgreSQL database” is not an algorithm for achieving the function of “means for updating an enterprise IT telemetry structured database using the IT telemetry data from the plurality of disparate IT platforms, the IT telemetry structured database including only data identified as non-confidential” for at least the reason that it fails to disclose identifying and including only non-confidential data.
Examiner maintains the 112b rejections to Claims 9 and 20.
Applicant argues at Remarks, pgs. 6-8 that the claims are nonobvious because of the limitation that “the LLM generates a plurality of schematic inferences from the IT telemetry structured database.” Applicant’s logic here appears to be that “The four references cited across both 103 rejections divide these two ingredients without ever combining them.”
Applicant improperly piecemeals. Applicant does not appear to dispute that Garrison generates insights using artificial intelligence and machine learning based on aggregated telemetry data. Thus, Garrison is deficient with respect to the limitation only inasmuch as it does not explicitly nominate a LLM as the AI/ML insight mechanism. Applicant acknowledges that Examiner explained this at Non-Final, pg. 6. Examiner cited Mermoud for the LLM. Applicant expressly acknowledges Mermoud teaches a LLM. Examiner cited Mammen for a database that includes only non-confidential information. With respect to some dependent claims, Applicant expressly recognizes that Arye teaches a structured database. (Remarks, pg. 6)
Consequently, when Applicant states “Every pairing among these references leaves the same gap” what Applicant appears to mean is that no single reference, standing on its own, anticipates a LLM drawing the IT telemetry structured database. Examiner agrees, which is why this is not an anticipation rejection.
Rather, the logic is that the claimed IT telemetry structured database is obvious over the teachings from all three references – Garrison teaches an aggregated datastore, knowledge and configuration database, as well as data about device operational status, Mermoud teaches log files and system traces which is part of the IT telemetry data, and Mammen discloses identifying and segregating confidential data so that the database only includes non-confidential data. Garrison then discloses drawing upon this data to gain insights, but does not particularly name a LLM. Mermoud supplies the LLM as a particular means of analysis. Consequently, the fact that no references have a LLM draw upon the claimed database is not relevant, because the rejection is based upon the teachings from the combination of references.
Applicant likens this to a network card and a cryptographic chip “that each exist as fully functional, independently documented components, but are never directly connected to each other.” Examiner need not debate some hypothetical, the concrete situation presented is sufficient: Examiner agrees that two things, each independently existing in the prior art, may (without more) not be sufficient to render the interaction between the two things obvious. In other words, were this a situation where Examiner merely pointed to a LLM and merely pointed to a IT telemetry database, those two things by themselves are insufficient for obviousness. But simple combination is generally obvious (see MPEP 2143(I)(A)) when it yields expected results, and further this situation goes beyond two noninteracting things. Garrison discloses the same type of data (IT Telemetry) being drawn upon by the general class of analysis mechanisms (AI/ML algorithms) as is claimed. Therefore, the claimed type of “interaction” was known to the prior art, which is unsurprising because if one wants to gain insights as to the workings of IT devices one would expect to draw upon data describing the workings of IT devices.
Applicant next argues, in considering Examiner’s combination, that including the Mermoud LLM is insufficient because “Garrison’s own insight generation operations on Garrison’s unstructured inventory, not on Arye’s schematized tables…” Examiner takes this as argument that Garrison fails to teach an IT telemetry structured database. But, as above, the database is obvious over the combination of three references, and Applicant does not explain why Garrison fails to teach the structured database. Applicant appears to accept that Arye teaches a structured database, but the citations for Arye were for, e.g., hypertable features that are not required for Claim 1. For example, the citations for the database include Garrison, para. 27 which discloses a CMDB. The CMDB “may include configuration information for various enterprise assets” (para. 27) and appears to be “updated” by the telemetry techniques that “continuously update[]” about “configurations” (para. 22). That appears to teach the claim limitation of “updating an enterprise IT telemetry structured database.” And the CMDB and related knowledge bases and telemetry data are used in the insight generation process (paras. 46-51) to gain insights, which is “the LLM generates a plurality of schematic inferences from the IT telemetry structured database” but-for the analysis not being done by a LLM in particular rather than AI/ML more generally. Para. 50 explicitly states “the configuration data from a configuration management database…is analyzed.”
Examiner notes that Applicant describes “Garrison + Mermoud” as “places a LLM beside an unstructured inventory.” But Applicant has no evidentiary basis for the word “unstructured” in that sentence. The inventory (Garrison, para. 38) is a result of the telemetry and configuration analysis and “includes data relating to identification, location, configurations, descriptions and so on for each resource or asset of the enterprise. The inventory is resource information aggregated from the enterprise sites that represent the IT environment of the enterprise, including hardware, software, and service provided by various service providers.” The inventory is described as a “unified end-to-end inventory” (para. 25) that contains aggregated resource information. (para. 38) Relating configurations and descriptions to resources is structure. i.e. When para. 22 states that telemetry updates about software versions, and para. 38 states that the inventory has configurations for each resource, clearly the inventory reflects that, e.g., Device A has been updated to Software Version 2 while Device B is still using Software Version 1. That is a database that relates “Device A” with “Version 2” and “Device B” with “Version 1,” which is structure.
Although the specification is not read into the claims, Examiner notes that Spec, paras. 37-38 talk about aggregating telemetry from various platforms into a unified view, which appears extremely similar to the disclosures of aggregating from various enterprise sites (Garrison para. 38) to make a unified end-to-end inventory. (Garrison, para. 22).
Examiner finds the argument unpersuasive and maintains the rejection. The combination of references teach the IT structured database and render obvious a LLM drawing on the database for insights.
All claims remain rejected.
Conclusion
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 NICHOLAS P CELANI whose telephone number is (571)272-1205. The examiner can normally be reached on M-F 9-5.
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/NICHOLAS P CELANI/Examiner, Art Unit 2449
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