DETAILED ACTION
The following is a Final Office Action in response to communications filed May 11, 2026. Claims 1, 7, 11, and 17 are amended; claims 6 and 16 are canceled; and claims 21–22 are newly added. Currently, claims 1–5, 7–15, and 17–22 are pending.
Response to Amendment/Argument
Applicant’s Response is sufficient to overcome the previous rejection of claims 7–9 and 17–19 under 35 U.S.C. 112(b) 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. Accordingly, the previous rejection of claims 7–9 and 17–19 under 35 U.S.C. 112(b) is withdrawn.
However, Applicant’s Response necessitates a new ground of rejection under 35 U.S.C. 112(b), and Examiner directs Applicant to the relevant explanation below.
Applicant’s Response is sufficient to overcome the previous rejection of claims 1–5, 7–15, and 17–20 under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. More particularly, the additional elements of claims 1 and 11, including the elements reciting “in response to a selection of an icon on the interactive interface, performing, by the device, a recommended action provided by the subset of detectors to fix the problem statement for the customer workload,” integrate the abstract idea into a practical application under Step 2A Prong Two because the additional elements embody an improvement to other technology. Accordingly, the previous rejection of claims 1–5, 7–15, and 17–20 under 35 U.S.C. 101 is withdrawn.
With respect to the previous rejections under 35 U.S.C. 102 and 35 U.S.C. 103, Applicant’s remarks have been fully considered but are moot in view of the updated grounds of rejection asserted below.
Claim Rejections - 35 USC § 112(b)
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 1–5, 7–15, and 17–22 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.
Claims 1 and 11 recite “the subset of detectors” in the element reciting “performing … a recommended action”. There is insufficient antecedent basis for this limitation in the claims.
Claims 1 and 11 further recite “the problem statement” in the element reciting “performing … a recommended action”. There is insufficient antecedent basis for this limitation in the claims.
For purposes of examination, claims 1 and 11 are interpreted as reciting “[[the]] a subset of detectors” and “[[the]] a problem statement” in the element reciting “performing … a recommended action”.
In view of the above, claims 1 and 11 are rejected under 35 U.S.C. 112(b) 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.
Claims 2–5, 7–10, 12–15, and 17–22, which depend from claims 1 and 11, inherit the deficiencies described above. As a result, claims 2–5, 7–10, 12–15, and 17–22 are similarly rejected under 35 U.S.C. 112(b) 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.
Claims 4 and 14 recite “a problem statement” and “a subset of detectors” in the step for “identifying”. As noted above, however, claims 1 and 11 previously recite “a problem statement” and “a subset of detectors”. Therefore, the scope of claims 4 and 14 is indefinite because it is unclear whether Applicant intends for the recitations of claims 4 and 14 to reference the recitations of claims 1 and 11 or intends to introduce a second, different “problem statement” and/or “subset of detectors”.
For purposes of examination, claims 4 and 14 are interpreted as reciting “[[a]] the problem statement” and “[[a]] the subset of detectors” in the step for “identifying”.
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, 11–13, and 22 are rejected under 35 U.S.C. 103 as being unpatentable over S NANAL et al. (U.S. 2020/0180148) in view of Saraiya et al. (U.S. 2021/0406041).
Claims 1 and 11: S NANAL discloses a method executed by a device (See FIG. 1), comprising:
identifying one or more issues for a customer workload running on a cloud service provider (See paragraphs 21–22, in view of paragraph 44, wherein customer issues are identified with respect to cloud-hosted applications);
using a detector to automatically analyze backend telemetry data for the customer workload and generate an insight for the one or more issues observed in the backend telemetry data, wherein the detector is used to troubleshoot the one or more issues (See paragraphs 29–30, in view of paragraphs 23–24, wherein extracted telemetry data is analyzed by a data analyzer to identify and deploy a troubleshooting solution; see also paragraphs 21–22);
adding a search term for the detector that includes key words or phrases that describe the one or more issues (See paragraphs 28–30, wherein the RPA system employs NLP to “select particular keywords indicative of the nature of the error”, wherein knowledge base includes feature keywords indicative of the issues, and wherein the knowledge base is updated based on analysis of executed corrective actions; see also paragraphs 31–32, wherein new solutions are recorded within the knowledge base);
storing the detector and the search term in a datastore (See paragraphs 30–32, wherein updates to the RPA system, including new terms, are recorded within the knowledge base); and
performing, by the device, a recommended action provided by the subset of detectors to fix the problem for the customer workload (See paragraphs 29–30, in view of paragraphs 23–24, wherein the troubleshooting solution identified by the data analyzer is implemented by one or more bots; see also paragraphs 21–22). S NANAL does not expressly disclose the remaining claim elements.
Saraiya discloses presenting, on an interactive interface, the insight (See FIG. 6D and paragraph 63, wherein incidents are displayed on an interactive interface with corresponding information and actions; see also paragraph 7); and
in response to a selection of an icon on the interactive interface, performing a recommended action to fix the problem statement for the customer workload (See FIG. 6D and paragraph 63, wherein, upon selection of an action within the interface, the action is automatically performed; see also paragraph 158, wherein incident issue are reported by a trouble-ticketing system).
S NANAL discloses a system directed to using an analytic RPA system to implement operational solutions. Saraiya discloses a system directed to analyzing and managing incident events by analyzing operational data. Each reference discloses a system directed to implementing solutions based on operational analysis. The technique of using an interactive interface is applicable to the system of S NANAL as they each share characteristics and capabilities, namely, they are directed to implementing solutions based on operational analysis.
One of ordinary skill in the art would have recognized that applying the known technique of Saraiya would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Saraiya to the teachings of S NANAL would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate operational analysis and solution implementation into similar systems. Further, applying an interactive interface to S NANAL would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow improved management.
With respect to claim 11, S NANAL discloses a processor; memory in electronic communication with the processor; and instructions stored in the memory, the instructions being executable (See FIG. 9 and paragraph 54).
Claims 2 and 12: S NANAL discloses the method of claim 1, wherein the insight provides a recommended action to address the one or more issues (See paragraph 29, wherein the RPA system identifies a solution).
Claims 3 and 13: S NANAL discloses the method of claim 1, wherein the insight provides interactive visuals and contextual information that provide a description summarizing the backend telemetry data explaining why the one or more issues are occurring in the customer workload (See paragraphs 51–52, wherein the RPA system displays summaries for issues and actions on a dashboard).
Claim 22: S NANAL does not expressly disclose the elements of claim 22.
Saraiya discloses wherein the interactive interface includes a list of areas analyzed in the customer workload by the detector and an indication that the areas are operating correctly or an indication that the areas have the one or more issues (See FIG. 6A–E and paragraphs 56, 60, and 62, wherein the interface displays monitored locations, lists analyzed service areas, and indicates impacted and nonimpacted services within a service-dependency graph).
One of ordinary skill in the art would have recognized that applying the known technique of Saraiya would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 1.
Claims 4–5, 7–10, 14–15, and 17–20 are rejected under 35 U.S.C. 103 as being unpatentable over S NANAL et al. (U.S. 2020/0180148) in view of Saraiya et al. (U.S. 2021/0406041), and in further view of Gross et al. (U.S. 2021/0263828).
Claims 4 and 14: As disclosed above, S NANAL and Saraiya disclose the elements of claim 1.
S NANAL discloses the method of claim 1, further comprising: receiving a problem from a customer for the customer workload (See paragraphs 21–22, in view of paragraph 44, wherein customer issues are identified with respect to cloud-hosted applications); and
receiving the insight from the detector based on analysis of the backend telemetry data for the customer workload, wherein the insight provides a recommended action to address the one or more issues (See paragraphs 29–30, in view of paragraphs 23–24, wherein extracted telemetry data is analyzed to identify and deploy a troubleshooting solution; see also paragraphs 21–22). S NANAL and Saraiya do not expressly disclose the remaining claim elements.
Gross discloses receiving a problem statement from a customer (See paragraph 49, wherein a customer use case is provided as an inquiry);
identifying a subset of detectors from the datastore to use with the problem statement (See paragraphs 47–49, wherein a model is selected from a library of models to address the customer use case); and
receiving the insight from the subset of detectors based on analysis of the backend telemetry data, wherein the insight provides a recommended action to address the one or more issues (See paragraphs 47–49, wherein the selected model recommends configuration adjustments in response to the identified problem).
As disclosed above, S NANAL discloses a system directed to using an analytic RPA system to implement operational solutions, and Saraiya discloses a system directed to analyzing and managing incident events by analyzing operational data. Gross discloses a system directed to recommending and implementing data center configuration solutions by analyzing operational data. Each reference discloses a system directed to implementing solutions based on operational analysis. The technique of using a subset of detectors to address a problem statement is applicable to the systems of S NANAL and Saraiya as they each share characteristics and capabilities, namely, they are directed to implementing solutions based on operational analysis.
One of ordinary skill in the art would have recognized that applying the known technique of Gross would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Gross to the teachings of S NANAL and Saraiya would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate operational analysis and solution implementation into similar systems. Further, applying a subset of detectors to address a problem statement to S NANAL and Saraiya would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow more detailed analysis and more reliable results.
Claims 5 and 15: S NANAL discloses the method of claim 4, wherein identifying the subset of detectors further comprises:
running a natural language processing (NLP) search on the problem (See paragraph 28, wherein the data processor applies NLP on the received error messages);
identifying the one or more issues for the customer workload based on the NLP search (See paragraphs 28–30, wherein the RPA system employs NLP to “select particular keywords indicative of the nature of the error”, wherein knowledge base includes feature keywords indicative of the issues, and wherein the knowledge base is updated based on analysis of executed corrective actions; see also paragraphs 31–32, wherein new solutions are recorded within the knowledge base); and
comparing the one or more issues to the search term of the detector (See paragraphs 28–30, wherein the RPA system employs NLP to “select particular keywords indicative of the nature of the error”, wherein knowledge base includes feature keywords indicative of the issues, and wherein the knowledge base is updated based on analysis of executed corrective actions; see also paragraphs 31–32, wherein new solutions are recorded within the knowledge base). S NANAL and Saraiya do not expressly disclose the remaining claim elements.
Gross discloses a problem statement (See paragraph 49, wherein a customer use case is provided as an inquiry); and
adding the detector to the subset of detectors when a match occurs between the one or more issues and the term for the detector (See FIG. 7 and paragraphs 34 and 52, wherein a new model is selected upon reconfiguration of the data center based on new matching characteristics; see also FIG. 6 and paragraph 47, wherein detector models are added to the library in an ongoing process).
One of ordinary skill in the art would have recognized that applying the known technique of Gross would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 4.
Claims 7 and 17: S NANAL discloses the method of claim 1, further comprising: creating, using an interactive interface, a new detector bot for an issue in the customer workload (See paragraphs 31–32, wherein a user creates a new solution, thereby training a new bot for automated resolution of the customer problem);
adding the search term for the new detector bot that includes the key words or the phrases that describe the issue (See paragraphs 30–32, in view of paragraphs 28–29, wherein issues and solutions are stored in the knowledge base with respect to associated keywords, and wherein new solutions/bots implicitly include keyword associations); and
storing the new detector bot and the search term in the datastore (See paragraphs 30–32, in view of paragraphs 28–29, wherein issues and solutions are stored in the knowledge base with respect to associated keywords, and wherein new solutions/bots implicitly include keyword associations). S NANAL and Saraiya do not expressly disclose the remaining claim elements.
Gross discloses creating a new detector (See FIG. 6 and paragraph 47, wherein detector models are added to the library in an ongoing process).
One of ordinary skill in the art would have recognized that applying the known technique of Gross would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 4.
Claims 8 and 18: S NANAL discloses the method of claim 7, wherein creating the new detector further comprises: identifying the backend telemetry data necessary to troubleshoot the issue in the customer workload (See paragraph 35, wherein the data parser analyzing the unstructured data to generate the necessary data in structured form); and
associating the backend telemetry data with the new detector bot in the datastore (See paragraphs 30–32, in view of paragraphs 18 and 27–29, wherein issues and solutions are stored in the knowledge base with respect to associated features, and wherein new solutions/bots implicitly include feature associations). S NANAL and Saraiya do not expressly disclose the remaining claim elements.
Gross discloses a new detector (See FIG. 6 and paragraph 47, wherein new detector models are generated and trained).
One of ordinary skill in the art would have recognized that applying the known technique of Gross would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 4.
Claims 9 and 19: S NANAL discloses the method of claim 7, wherein the new detector bot is a custom detector bot tailored to the customer workload (See paragraphs 31–32, wherein new detector bots are customized for new customer issues). S NANAL and Saraiya do not expressly disclose the remaining claim elements.
Gross discloses a new detector (See FIG. 6 and paragraph 47, wherein new detector models are generated and trained).
One of ordinary skill in the art would have recognized that applying the known technique of Gross would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 4.
Claims 10 and 20: S NANAL discloses the method of claim 1, further comprising: placing the detector bot into a category in response to the key words or the phrases in the search term for the detector matching the category (See paragraph 30, wherein solution bots are mapped according to issues categories). S NANAL and Saraiya do not expressly disclose the remaining claim elements.
Gross discloses placing the detector into a category (See FIG. 6, wherein models are indexed using row and column categories).
One of ordinary skill in the art would have recognized that applying the known technique of Gross would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 4.
Claim 21 rejected under 35 U.S.C. 103 as being unpatentable over S NANAL et al. (U.S. 2020/0180148) in view of Saraiya et al. (U.S. 2021/0406041), and in further view of Caldwell et al. (U.S. 2019/0050239).
Claim 21: As disclosed above, S NANAL and Saraiya disclose the elements of claim 1. Although Saraiya discloses an interactive interface (See citations above), S NANAL and Saraiya do not expressly disclose the remaining elements of claim 21.
Caldwell discloses wherein the interactive interface combines a chatbot with the insight and the chatbot allows a user to enter a natural language problem statement and guides the user through troubleshooting the problem statement (See paragraphs 32 and 38, in view of paragraph 20, wherein the system utilizes a chatbot to assist the user in troubleshooting an issue submitted by the user).
As disclosed above, S NANAL discloses a system directed to using an analytic RPA system to implement operational solutions, and Saraiya discloses a system directed to analyzing and managing incident events by analyzing operational data. Caldwell discloses a system directed to diagnosing and troubleshooting service issues. Each reference discloses a system directed to implementing solutions based on operational analysis. The technique of using a chatbot is applicable to the systems of S NANAL and Saraiya as they each share characteristics and capabilities, namely, they are directed to implementing solutions based on operational analysis.
One of ordinary skill in the art would have recognized that applying the known technique of Gross would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Gross to the teachings of S NANAL and Saraiya would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate operational analysis and solution implementation into similar systems. Further, applying a chatbot to S NANAL and Saraiya would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow more detailed analysis and more reliable results.
Conclusion
The following prior art is made of record and not relied upon but is considered pertinent to Applicant's disclosure:
Ramakrishna et al. (U.S. 2018/0121808) discloses a system directed to using a chatbot for intelligent troubleshooting.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM S BROCKINGTON III whose telephone number is (571)270-3400. The examiner can normally be reached M-F, 8am-5pm, EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rutao Wu can be reached at 571-272-6045. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/WILLIAM S BROCKINGTON III/Primary Examiner, Art Unit 3623
Prosecution Insights