Prosecution Insights
Last updated: August 17, 2026
Application No. 18/977,737

DATABASE-AGNOSTIC ASYNCHRONOUS PRODUCT REPLICATION WITH ATOMIC ENTITIES

Non-Final OA §103
Filed
Dec 11, 2024
Examiner
HARMON, COURTNEY N
Art Unit
2159
Tech Center
2100 — Computer Architecture & Software
Assignee
Okta Inc.
OA Round
3 (Non-Final)
63%
Grant Probability
Moderate
3-4
OA Rounds
1y 8m
Est. Remaining
72%
With Interview

Examiner Intelligence

Grants 63% of resolved cases
63%
Career Allowance Rate
273 granted / 436 resolved
+7.6% vs TC avg
Moderate +9% lift
Without
With
+9.0%
Interview Lift
resolved cases with interview
Typical timeline
3y 4m
Avg Prosecution
19 currently pending
Career history
454
Total Applications
across all art units

Statute-Specific Performance

§101
16.4%
-23.6% vs TC avg
§103
66.1%
+26.1% vs TC avg
§102
8.8%
-31.2% vs TC avg
§112
5.7%
-34.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 436 resolved cases

Office Action

§103
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 . This Office Action is sent in response to Applicant's Communication received on June 2, 2026 for application number 18/977,737. This Office hereby acknowledges receipt of the following and placed of record in file: Specification, Drawings, Abstract, Oath/Declaration, and Claims. Response to Arguments Applicant's arguments filed June 2, 2026 regarding the rejection of claims 1, 11, and 20 under 35 U.S.C 103 have been fully considered but they are not persuasive. Examiner is sending a second non-final because independent claims 1, 11, and 20 prior art mappings for limitation that states "migrating the data corresponding to the product, wherein migrating the data comprises: causing each of one or more source agents associated with the one or more source databases to export, into a payload-agnostic data structure, product entity source data associated with the one or more product entities; and causing one or more target agents associated with one or more target databases in the target environment to import, from the payload-agnostic data structure and into the one or more target databases, the product entity source data, wherein the product entity source data is imported in accordance with one or more migration rules" is being rejected under 35 U.S.C. 103 as being unpatentable over Burch et al. (US 2024/0386030) (hereinafter Burch), not Ferris et al. (US 2012/0303739) (hereinafter Ferris) as stated in office action dated 03/09/2026. 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 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. The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. Claims 1, 3-5, 10-11, 13-15, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Kodavati et al. (US 2023/0144349) (hereinafter Kodavati) in view of Burch et al. (US 2024/0386030) (hereinafter Burch), and in further view of Wei et al. (US 2023/0050622)(hereinafter Wei). Regarding claim 1, Kodavati teaches a method by a migration controller device associated with a migration platform, comprising: receiving a request to migrate, from a source environment to a target environment (see Figs. 1-2, para [0037], discloses receiving a migration request from a source computing system to a target computing system), data corresponding to a product associated with a customer (see Figs. 3-4, Fig. 5B, para [0034], para [0052], corresponding to an application/services (product) associated with customers or tenant customers); identifying, in the source environment, one or more source databases that comprise one or more product entities associated with the product (see Figs. 2-3, para [0032], para [0038-0039], discloses identifying in source computing system, source data tables that comprise subset of data (product entity)). Kodavati does not explicitly teach migrating the data corresponding to the product, wherein migrating the data comprises: causing each of one or more source agents associated with the one or more source databases to export, into a payload-agnostic data structure, product entity source data associated with the one or more product entities, wherein the one or more source databases are associated with one or more different database technologies; and causing one or more target agents associated with one or more target databases in the target environment to import, from the payload-agnostic data structure and into the one or more target databases, the product entity source data, wherein the product entity source data is imported in accordance with one or more migration rules. Burch teaches migrating the data corresponding to the product, wherein migrating the data comprises: causing each of one or more source agents associated with the one or more source databases to export, into a payload-agnostic data structure, product entity source data associated with the one or more product entities (see para [0119], discloses request payload indicating tables (product entities) to migrate in a job context in which selected sources tables are to be migrated along with columns/constraints (product entity source data) for each table); and causing one or more target agents associated with one or more target databases in the target environment to import, from the payload-agnostic data structure and into the one or more target databases, the product entity source data (see para [0119], para [0122], discloses loading columns-constraints for tables into target database in a load order for reading source data records), wherein the product entity source data is imported in accordance with one or more migration rules (see para [0118], discloses transform rules defining rules for extraction, transformation and loading data from source to target database). Kodavati/Burch are analogous arts as they are each from the same field of endeavor of database systems. Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Kodavati to include source agent to communicate with source database from disclosure of Burch. The motivation to combine these arts is disclosed by Burch as “improve data migration between databases that store data under different schemas” (para [0005]) and including source agent to communicate with source database are well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success. Kodavati/Burch do not explicitly teach wherein the one or more source databases are associated with one or more different database technologies. Wei teaches , wherein the one or more source databases are associated with one or more different database technologies (see Fig. 3, para [0035], discloses text and media (technologies) content associated with source database). Kodavati/Burch/Wei are analogous arts as they are each from the same field of endeavor of database systems. Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Kodavati/Burch to associate different database technologies with source database from disclosure of Wei. The motivation to combine these arts is disclosed by Wei as “image or video manipulation implemented by a convolutional neural network that has been configured to execute efficiently on the client device” (para [0056]) and associates different database technologies with source database are well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success. Regarding claim 11, Kodavati teaches a migration controller device associated with a migration platform, comprising: one or more memories storing processor-executable code (see Fig. 1, para [0014], discloses memories and code); and one or more processors coupled with the one or more memories and individually or collectively operable to execute the code to cause the migration controller device associated with a migration platform to (see Fig. 1, para [0014], discloses processors): receive a request to migrate, from a source environment to a target environment (see Figs. 1-2, para [0037], discloses receiving a migration request from a source computing system to a target computing system), data corresponding to a product associated with a customer (see Figs. 3-4, Fig. 5B, para [0034], para [0052], corresponding to an application/services (product) associated with customers or tenant customers); identify, in the source environment, one or more source databases that comprise one or more product entities associated with the product (see Figs. 2-3, para [0032], para [0038-0039], discloses identifying in source computing system, source data tables that comprise subset of data (product entity)). Kodavati teaches migrate the data corresponding to the product, wherein migration of the data comprises: cause each of one or more source agents associated with the one or more source databases to export, into a payload-agnostic data structure, product entity source data associated with the one or more product entities, wherein the one or more source databases are associated with one or more different database technologies; and cause one or more target agents associated with one or more target databases in the target environment to import, from the payload-agnostic data structure and into the one or more target databases, the product entity source data, wherein the product entity source data is imported in accordance with one or more migration rules. Burch teaches migrate the data corresponding to the product, wherein migrating the data comprises: cause each of one or more source agents associated with the one or more source databases to export, into a payload-agnostic data structure, product entity source data associated with the one or more product entities (see para [0119], discloses request payload indicating tables (product entities) to migrate in a job context in which selected sources tables are to be migrated along with columns/constraints (product entity source data) for each table); and cause one or more target agents associated with one or more target databases in the target environment to import, from the payload-agnostic data structure and into the one or more target databases, the product entity source data (see para [0119], para [0122], discloses loading columns-constraints for tables into target database in a load order for reading source data records), wherein the product entity source data is imported in accordance with one or more migration rules (see para [0118], discloses transform rules defining rules for extraction, transformation and loading data from source to target database). Kodavati/Burch are analogous arts as they are each from the same field of endeavor of database systems. Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Kodavati to include source agent to communicate with source database from disclosure of Burch. The motivation to combine these arts is disclosed by Burch as “improve data migration between databases that store data under different schemas” (para [0005]) and including source agent to communicate with source database are well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success. Kodavati/Burch do not explicitly teach , wherein the one or more source databases are associated with one or more different database technologies. Wei teaches , wherein the one or more source databases are associated with one or more different database technologies (see Fig. 3, para [0035], discloses text and media (technologies) content associated with source database). Kodavati/Burch/Wei are analogous arts as they are each from the same field of endeavor of database systems. Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Kodavati/Burch to associate different database technologies with source database from disclosure of Wei. The motivation to combine these arts is disclosed by Wei as “image or video manipulation implemented by a convolutional neural network that has been configured to execute efficiently on the client device” (para [0056]) and associates different database technologies with source database are well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success. Regarding claim 20, Kodavati teaches a non-transitory computer-readable medium storing code, the code comprising instructions executable by one or more processors (see Fig. 1, para [0014], discloses processors, memories and code); to: receive a request to migrate, from a source environment to a target environment (see Figs. 1-2, para [0037], discloses receiving a migration request from a source computing system to a target computing system), data corresponding to a product associated with a customer (see Figs. 3-4, Fig. 5B, para [0034], para [0052], corresponding to an application/services (product) associated with customers or tenant customers); identify, in the source environment, one or more source databases that comprise one or more product entities associated with the product (see Figs. 2-3, para [0032], para [0038-0039], discloses identifying in source computing system, source data tables that comprise subset of data (product entity)). Kodavati does not explicitly teach migrate the data corresponding to the product, wherein migrating the data comprises: cause each of one or more source agents associated with the one or more source databases to export, into a payload-agnostic data structure, product entity source data associated with the one or more product entities, wherein the one or more source databases are associated with one or more different database technologies; and cause one or more target agents associated with one or more target databases in the target environment to import, from the payload-agnostic data structure and into the one or more target databases, the product entity source data, wherein the product entity source data is imported in accordance with one or more migration rules. Burch teaches migrate the data corresponding to the product, wherein migrating the data comprises: cause each of one or more source agents associated with the one or more source databases to export, into a payload-agnostic data structure, product entity source data associated with the one or more product entities (see para [0119], discloses request payload indicating tables (product entities) to migrate in a job context in which selected sources tables are to be migrated along with columns/constraints (product entity source data) for each table); and cause one or more target agents associated with one or more target databases in the target environment to import, from the payload-agnostic data structure and into the one or more target databases, the product entity source data (see para [0119], para [0122], discloses loading columns-constraints for tables into target database in a load order for reading source data records), wherein the product entity source data is imported in accordance with one or more migration rules (see para [0118], discloses transform rules defining rules for extraction, transformation and loading data from source to target database). Kodavati/Burch are analogous arts as they are each from the same field of endeavor of database systems. Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Kodavati to include source agent to communicate with source database from disclosure of Burch. The motivation to combine these arts is disclosed by Burch as “improve data migration between databases that store data under different schemas” (para [0005]) and including source agent to communicate with source database are well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success. Kodavati/Burch do not explicitly teach , wherein the one or more source databases are associated with one or more different database technologies. Wei teaches , wherein the one or more source databases are associated with one or more different database technologies (see Fig. 3, para [0035], discloses text and media (technologies) content associated with source database). Kodavati/Burch/Wei are analogous arts as they are each from the same field of endeavor of database systems. Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Kodavati/Burch to associate different database technologies with source database from disclosure of Wei. The motivation to combine these arts is disclosed by Wei as “image or video manipulation implemented by a convolutional neural network that has been configured to execute efficiently on the client device” (para [0056]) and associates different database technologies with source database are well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success. Regarding claims 10 and 19, Kodavati/Burch/Wei teach a method of claim 1 and a device of claim 11. Kodavati does not explicitly teach identifying, based at least in part on the one or more source databases, the one or more target databases into which to import the product entity source data. Burch teaches teach identifying, based at least in part on the one or more source databases, the one or more target databases into which to import the product entity source data (see Figs. 4B-5, para [0119, 0122], para [0138], discloses identifying table and column rules in which to migrate source data to target database). Regarding claims 3 and 13, Kodavati/Burch/Wei teach a method of claim 1 and a device of claim 11. Kodavati do not explicitly teach wherein each source agent of the one or more source agents is configured to communicate with a corresponding source database of the one or more source databases. Burch teaches wherein each source agent of the one or more source agents is configured to communicate with a corresponding source database of the one or more source databases (see para [0034-0036], discloses migration request to migrate source data from source database having a source schema to a destination database). Regarding claims 4 and 14, Kodavati/Burch/Wei teach a method of claim 1 and a device of claim 11. Kodavati do not explicitly teach wherein the one or more migration rules comprise one or more rules for determining, based on a dependency graph, an order for importing the product entity source data. Burch teaches wherein the one or more migration rules comprise one or more rules for determining, based on a dependency graph, an order for importing the product entity source data (see Fig. 6, para [0012], para [0041], discloses dependency graph with multiple parallel paths, and transformation rules indicating groupings to be transformed in parallel). Regarding claims 5 and 15, Kodavati/Burch/Wei teach a method of claim 1 and a device of claim 11. Kodavati do not explicitly teach wherein the one or more product entities comprise a tenant, a user, a permission, an organization, a token, or a user search. Burch teaches wherein the one or more product entities comprise a tenant, a user, a permission, an organization, a token, or a user search (see Fig. 6, Table 1, para [0150], discloses ‘mapping_customer’). Claims 2 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Kodavati et al. (US 2023/0144349) (hereinafter Kodavati) in view of Burch and Wei as applied to claims 1 and 11, and in further view of Ji et al. (US 2022/0318211)(hereinafter Ji). Regarding claims 2 and 12, Kodavati/Burch/Wei teach a method of claim 1 and a device of claim 11. Kodavati/Burch/Wei do not explicitly teach while performing the migration of the data corresponding to the product: streaming one or more data streams from the one or more source databases into buffer storage; causing the one or more source agents to listen for database events at the one or more data streams; receiving, from a first source agent of the one or more source agents, an indication that a database event associated with a first entity is detected at first data stream corresponding to a first source database of the one or more source databases; causing, based at least in part on detecting the database event, the first source agent to collect, from one or more other source databases, data associated with one or more additional entities that are associated with the first entity; causing the first source agent to store the collected data in the buffer storage; and causing, after completion of the migration, the one or more target agents to apply data from the buffer storage to the one or more target databases in accordance with the one or more migration rules. Ji teaches while performing the migration of the data corresponding to the product: streaming one or more data streams from the one or more source databases into buffer storage (see Fig. 1A, Fig. 4C, para [0067], discloses network data stream into buffer); causing the one or more source agents to listen for database events at the one or more data streams (see Figs. 2A-2C,Fig. 4C, para [0033], para [0067], discloses storing messages in buffer); receiving, from a first source agent of the one or more source agents, an indication that a database event associated with a first entity is detected at first data stream corresponding to a first source database of the one or more source databases (see Fig. 4C, para [0067], discloses data conversion engine receiving data list table); causing, based at least in part on detecting the database event, the first source agent to collect, from one or more other source databases, data associated with one or more additional entities that are associated with the first entity (see Fig. 4C, para [0067], discloses distributing received messages into multiple buffer chains , generating a parent thread to coordinate multiple child threads); causing the first source agent to store the collected data in the buffer storage (see para [0067], discloses for first data table thread stored in buffer chain) ; and causing, after completion of the migration, the one or more target agents to apply data from the buffer storage to the one or more target databases in accordance with the one or more migration rules (see Fig. 1A, Fig. 4C, para [0040], para [0067], discloses data converted into new format is stored in target database according to setup operations to allocate resources for receiving data and allocating resources for converting the received data into a format to be stored in a target database). Kodavati/Burch/Wei/Ji are analogous arts as they are each from the same field of endeavor of database systems. Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Kodavati/Burch/Wei to stream data streams from source database to buffer storage from disclosure of Ji. The motivation to combine these arts is disclosed by Ji as “improve the efficiency and reliability of data migration from source server 110 to target server” (para [0044]) and streaming data streams from source database to buffer storage are well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success. Claims 6-7 and 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over Kodavati et al. (US 2023/0144349) (hereinafter Kodavati) in view of Burch and Wei as applied to claims 1 and 11, and in further view of Tuchman et al. (US 2016/0162588)(hereinafter Tuchman). Regarding claims 6 and 16, Kodavati/Burch/Wei teach a method of claim 1 and a device of claim 11. Kodavati/Burch/Wei do not explicitly teach wherein the request to migrate data is received based at least in part on a subscription ratio associated with the source environment satisfying a threshold ratio. Tuchman teaches wherein the request to migrate data is received based at least in part on a subscription ratio associated with the source environment satisfying a threshold ratio (see para [0382-0383], para [0403], discloses migration based on global metrics (subscriptions ratio) associated with document sources, satisfying a fixed threshold number of documents) Kodavati/Burch/Wei/Tuchman are analogous arts as they are each from the same field of endeavor of database systems. Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Kodavati/Burch/Wei to include subscription ration satisfying a threshold ratio from disclosure of Tuchman. The motivation to combine these arts is disclosed by Tuchman as “evaluate efficacy and/or return on investment of advertising and/or other media campaigns and/or to recommend actions for improvement” (para [0022]) and including subscription ration satisfying a threshold ratio are well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success. Regarding claims 7 and 17, Kodavati/Burch/Wei teach a method of claim 1 and a device of claim 11. Kodavati/Burch/Wei do not explicitly teach wherein the request to migrate data is received based at least in part on an availability of multi-subscriber resources in the source environment satisfying a threshold. Tuchman teaches wherein the request to migrate data is received based at least in part on an availability of multi-subscriber resources in the source environment satisfying a threshold (see Fig. 10, para [0385], discloses global metrics satisfying a threshold to identify correlations). Kodavati/Burch/Wei/Tuchman are analogous arts as they are each from the same field of endeavor of database systems. Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Kodavati/Burch/Wei to include subscription ration satisfying a threshold ratio from disclosure of Tuchman. The motivation to combine these arts is disclosed by Tuchman as “evaluate efficacy and/or return on investment of advertising and/or other media campaigns and/or to recommend actions for improvement” (para [0022]) and including subscription ration satisfying a threshold ratio are well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success. Claims 8-9 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Kodavati et al. (US 2023/0144349) (hereinafter Kodavati) in view of Burch and Wei as applied to claims 1 and 11, and in further view of Tian et al. (US 2020/0326876)(hereinafter Tian). Regarding claims 8 and 18, Kodavati/Burch/Wei teach a method of claim 1 and a device of claim 11. Kodavati/Burch/Wei do not explicitly teach monitoring one or more quality of service (QoS) metrics associated with the one or more source databases and the one or more target databases, wherein the one or more QoS metrics comprise a quantity of records migrated to the one or more target databases, a quantity of records remaining in the one or more source databases, a percentage of the records from the one or more source databases that have been successfully migrated to the one or more target databases, a time lag associated with the migration, or a data freshness. Tian teaches monitoring one or more quality of service (QoS) metrics associated with the one or more source databases and the one or more target databases, wherein the one or more QoS metrics comprise a quantity of records migrated to the one or more target databases (see Fig. 2, para [0037], para [0121-0122], discloses quality of service, QoS for source bucket migration according to migration policy parameters for bucket), a quantity of records remaining in the one or more source databases, a percentage of the records from the one or more source databases that have been successfully migrated to the one or more target databases, a time lag associated with the migration, or a data freshness (see Figs. 2-3, para [0015], para [0099-0100], discloses determining if object migration policy is successfully configured, such as object migration processing on a specific quantity of buckets). Kodavati/Burch/Wei/Tian are analogous arts as they are each from the same field of endeavor of database systems. Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Kodavati/Burch/Wei to include Quality of service, QoS metrics from disclosure of Tian. The motivation to combine these arts is disclosed by Tian as “improving access efficiency” (para [0030]) and including Quality of service, QoS metrics is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success. Regarding claims 9 and 18, Kodavati/Burch/Wei teach a method of claim 1 and a device of claim 11. Kodavati/Burch/Wei do not explicitly teach based at least in part on at least one QoS metric of the one or more QoS metrics satisfying a service level threshold: sending, to an operator, a notification of the at least one QoS metric, or initiating a second request to migrate data corresponding to the product. Tuchman teaches based at least in part on at least one QoS metric of the one or more QoS metrics satisfying a service level threshold: sending, to an operator, a notification of the at least one QoS metric, or initiating a second request to migrate data corresponding to the product (see Fig. 3, Table 3, para [0149], discloses notifying storage client that object migration policy is successfully configured). Kodavati/Burch/Wei/Tian are analogous arts as they are each from the same field of endeavor of database systems. Before the effective filing date of the invention it would have been obvious to a person of ordinary skill in the art to modify the system of Kodavati/Burch/Wei to include Quality of service, QoS metrics from disclosure of Tian. The motivation to combine these arts is disclosed by Tian as “improving access efficiency” (para [0030]) and including Quality of service, QoS metrics is well known to persons of ordinary skill in the art, and therefore one of ordinary skill would have good reason to pursue the known options within his or her technical grasp that would lead to anticipated success. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See Singh et al. US Publication No. 2024/0176767. Any inquiry concerning this communication or earlier communications from the examiner should be directed to COURTNEY HARMON whose telephone number is (571)270-5861. The examiner can normally be reached M-F 9am - 5pm. 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, Ann Lo can be reached at 571-272-9767. 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. /Courtney Harmon/Primary Examiner, Art Unit 2159
Read full office action

Prosecution Timeline

Dec 11, 2024
Application Filed
Oct 24, 2025
Non-Final Rejection mailed — §103
Jan 16, 2026
Response Filed
Mar 09, 2026
Non-Final Rejection mailed — §103
Jun 02, 2026
Response Filed
Jun 23, 2026
Non-Final Rejection mailed — §103 (current)

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Prosecution Projections

3-4
Expected OA Rounds
63%
Grant Probability
72%
With Interview (+9.0%)
3y 4m (~1y 8m remaining)
Median Time to Grant
High
PTA Risk
Based on 436 resolved cases by this examiner. Grant probability derived from career allowance rate.

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