Prosecution Insights
Last updated: May 29, 2026
Application No. 19/064,246

ENTITY INFORMATION GENERATION

Final Rejection §103
Filed
Feb 26, 2025
Priority
Mar 18, 2024 — provisional 63/566,605
Examiner
HOANG, SON T
Art Unit
2169
Tech Center
2100 — Computer Architecture & Software
Assignee
Sentry Insurance Company
OA Round
2 (Final)
83%
Grant Probability
Favorable
3-4
OA Rounds
1y 8m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 83% — above average
83%
Career Allowance Rate
758 granted / 909 resolved
+28.4% vs TC avg
Strong +35% interview lift
Without
With
+35.0%
Interview Lift
resolved cases with interview
Typical timeline
2y 11m
Avg Prosecution
15 currently pending
Career history
928
Total Applications
across all art units

Statute-Specific Performance

§101
4.0%
-36.0% vs TC avg
§103
88.5%
+48.5% vs TC avg
§102
3.6%
-36.4% vs TC avg
§112
1.0%
-39.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 909 resolved cases

Office Action

§103
DETAILED ACTION 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 Amendment In response to the amendment filed on January 28, 2026: The abstract is amended. Claims 1, 3, 13, 14, and 20 are amended. Claims 1-20 are pending. Response to Arguments In response to the remarks filed on January 28, 2026: a. Objection to the abstract is withdrawn in view of Applicant’s amendment. b. 35 U.S.C. 101 rejections of the pending claims are withdrawn in view of Applicant’s amendment. The amended “intercepting, by one or more processors/first server, a message conveyed between a transmission server and a reception server, the transmission server and the reception server separate from the one or more processors/first server” integrates the data collection into practical application per step 2A – prong 2 of the abstract idea analysis. Each independent claims 1, 13, and 20 no longer recites “receiving data” generically but a specific, non-intrusive “man-in-the-middle” network configuration. The monitoring processors/server are structurally required to be separate from the transactional (transmission/reception) servers. As supported by the disclosure ([0003]-[0004] of instant specification), this specific passive-interception architecture solves a rooted technical problem (i.e., the data silo and harmonization issue). By intercepting messages in transit between separate servers, the system can aggregate data without requiring the reprogramming, harmonization or modification of the legacy transmission and reception servers. Thus, claims 1, 13, and 20 and all respective dependent claims are statutory under 35 U.S.C. 101 abstract idea analysis. 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 1-5, 7-10, 12-18, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Bellavista et al. (Pub. No. US 2025/0142345, filed on August 3, 2022; hereinafter Bellavista) in view of Webster (Pat. No. US 9319524, published on April 19, 2016). Regarding claim 1, Bellavista clearly shows and discloses a method (Abstract) comprising: intercepting, by one or more processors, a message conveyed between a transmission server and a reception server (the data that the communication network 10 intercepts as part of LI includes copies of the content of communications transmitted between the communication devices 12. The content of communications may, for example, include any material or information concerning the substance, purport, or meaning of the communications, [0048]), the transmission server and the reception server separate from the one or more processors (FIG. 1 shows that a point of intercepted (POI) 18 in the communication network 10 intercepts data in this way as part of LI. The POI 18 may be a physical, logical, or functional point at which data is intercepted. The POI 18 may for instance be, or be hosted at, an access element, a network connectivity element, or a service element in the communication network 10, [0049-[0050]); extracting, by one or more processors, a signal corresponding to a first interaction with an entity from the message (the intercepted data may include material or information related to the interception of communications transmitted between the communication devices 12. Such intercepted-related information (IRI) may for example include dialing, signaling, or addressing information that identifies the origin, direction, destination, or termination of each communication generated or received by a subscriber by means of any equipment, facility, or service of a service provider, [0048]. In step 1310, the host 1302 initiates a transmission carrying the user data towards the UE 1306. The host 1302 may initiate the transmission responsive to a request transmitted by the UE 1306. The request may be caused by human interaction with the UE 1306 or by operation of the client application executing on the UE 1306, [0185]); determining, by the one or more processors, an indication of an entity identity based on the signal (Consider an example in which the application-layer control protocol is the Session Initiation Protocol (SIP) such that the application-layer control messages 24 are SIP messages. In one such embodiment, each application-layer control session 26 corresponds to a SIP call leg. A SIP call may refer to a collection of one or more SIP call legs, where a SIP call leg refers to a one-to-one signaling relationship between two SIP user agents. In this context, the session identity (SID) field 28 may be a Call-ID field. The Call-ID field's value may be set to a cryptographically random identifier which is unique across SIP call legs, [0055]. The network mediation device 32 stores the couple [“Call-ID”, “extendedSession”] for the first SIP message intercepted. The value of “extendedSession” is a counter that will be increased at each new SMS service interception, e.g., as determined according to a service expiration timer. When a new SMS message is intercepted, the “In-Reply-To” field is detected and the network mediation device 32 verifies if the header contains the Call-ID number fetched from the internal cache according to the previous step. If case of a match, the network mediation device 32 gets the “extendedSession” value from the cache and provides it towards the handover interface 33 for the new SMS message, [0094]. The user data is associated with a particular human user interacting with the UE 1306. The request may be caused by human interaction with the UE 1306 or by operation of the client application executing on the UE 1306. The transmission may pass via the network node 1304. Accordingly, in step 1312, the network node 1304 transmits to the UE 1306 the user data that was carried in the transmission that the host 1302 initiated, [0185]). Webster then additionally or alternatively discloses: extracting, by one or more processors, a signal corresponding to a first interaction with an entity (In the event that the user device transmits an inquiry, such as a request for service or assistance via a dialed call, an application message generation selection option on a smartphone application or via another option, such as SMS messaging, the message may be generated 250 and transmitted from the user device 242 to a customer support site 244, [Column 6, Lines 4-18]); determining, by the one or more processors, an indication of an entity identity based on the signal (The message may be received and processed to identify and authorize 252 the user via the user's phone number, IP address, username, credentials, electronic certificate, etc., [Column 6, Lines 4-18]); receiving, by the one or more processors, a query associated with the entity, based on the entity identity (The user may be paired with a particular account and/or a set of user preferences stored in a database 246. The user account or preferences may be derived from previous calls or interactions received from the user and/or user selections, user subscription data, etc, [Column 6, Lines 4-18], [Column 8, Line 34 – Column 9, Line 6]); generating, by the one or more processors and responsive to the query, interaction basis information, the interaction basis information based on the signal (The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's social networking account information by performing a predictive analysis via a likelihood function 290. The basic operation of the likelihood function may identify a frequency of terms related to a broader subject, such as sports, politics, movies, etc., and identify the user's preferences accordingly. For example, in the above example the written terms may mostly relate to politics and all such terms may be written by a user, submitted in blog postings and/or were comments submitted electronically and on a server of the social networking platform, [Column 8, Line 34 – Column 9, Line 6]); and presenting, by the one or more processors, the interaction basis information via a user interface (As a result, the weight for “politics” may be equal to four for that preference while the weight for “sports” may be equal to two, which is a lower weighted user preference. The user device may first be presented with a question related to sports, such as “do you want to hear about new sports packages for your online cable service?” or “are you satisfied with your sports packages?”, [Column 8, Line 34 – Column 9, Line 6]). It would have been obvious to an ordinary person skilled in the art at the time of the invention was effectively filed to incorporate the teachings of Webster with the teachings of Bellavista for the purpose of providing a seamless transactional experience for users based on personalized interactive options using derived preferences from the extracted identities of the users. Regarding claim 2, Webster further discloses: storing, by the one or more processors, a first data record corresponding to the signal, the first data record comprising the entity identity and an indication of a first communications channel for the first interaction (A user's preferred channel of communication may be identified via his or her preferences. In one example, a user may initiate a first medium of communication, via a text message, smartphone application, call, etc. As a result, the user call processing system may identify the inquiry from the user and apply one or more preferences to the result, [Column 10, Lines 7-17]); determining, by the one or more processors, a second communications channel associated with the query, the second communications channel different from the first communications channel (phone calls which are dialed out of a user device a one option among many options to contact a customer support service center. In another example embodiment, the user may be accessing customer support via any communication channel/medium, such as email, live chat applications, website access, and mobile device applications. For example, transmitting menu options and/or automatically selecting a menu option for a user may be performed responsive to identifying the user and one or more of his or her preferences for processing customer support inquiries, [Column 9, Line 61 – Column 10, Line 6]); and retrieving, by the one or more processors, the first data record based on the entity identity, wherein the generation of the interaction basis information is based on the first communications channel and the second communications channel (retrieving a user profile from memory that includes the history information based on previous interactions between the user device and the customer call center server (e.g., calls, messages, spoken dialogue, account information, etc.), [Column 10, Lines 44-55]. The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's social networking account information by performing a predictive analysis via a likelihood function 290, [Column 8, Line 34 – Column 9, Line 6]). Regarding claim 3, Webster further discloses intercepting a message conveyed between a transmission server and a reception server, the transmission server and the reception server separate from the one or more processors; and storing the signal comprises: storing the message; and storing an indication of the transmission server or the reception server (A user's preferred channel of communication may be identified via his or her preferences. In one example, a user may initiate a first medium of communication, via a text message, smartphone application, call, etc. As a result, the user call processing system may identify the inquiry from the user and apply one or more preferences to the result. In one example, the user may text an inquiry for an upgrade in service and receive an email with information regarding the upgrade since that is the user's preference to communicate with email, [Column 10, Lines 7-17]). Regarding claim 4, Webster further discloses the signal is one signal of a plurality of signals, each of the plurality of signals corresponding to a different interaction with the entity (the user may have posted information on a blog, such as jokes and comments to certain friend accounts of the user, such as references to certain sports teams, comments about recent movies, political comments, vacation information, etc., [Column 8, Line 34 – Column 9, Line 6]), and comprising: retrieving, by the one or more processors, the plurality of signals associated with the entity (Those words may be identified and stored in the user's profile account. The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's social networking account information by performing a predictive analysis via a likelihood function 290, [Column 8, Line 34 – Column 9, Line 6]); prioritizing, by the one or more processors, the plurality of signals based on the query (The algorithm of the likelihood function would then likely extract a main preference to be [politics] and a secondary preference to be [sports] based on the various information submitted from the user account. Those preferences then can be queued in order depending on their relevance. The relevance may be based on an assigned weight value proportional to the number of times the words appear for that category, [Column 8, Line 34 – Column 9, Line 6]); and presenting, by the one or more processors, the interaction basis information based on the prioritization (As a result, the weight for “politics” may be equal to four for that preference while the weight for “sports” may be equal to two, which is a lower weighted user preference. The user device may first be presented with a question related to sports, such as “do you want to hear about new sports packages for your online cable service?” or “are you satisfied with your sports packages?”, [Column 8, Line 34 – Column 9, Line 6]). Regarding claim 5, Webster further discloses: matching, by the one or more processors, the entity identity to a field of a machine-readable record generated based on an entity action, to contextualize a human-readable record (the user may have called the customer support 244 and spoke words, such as “sports”, “football”, “movies”, “high speed Internet”, “affordable”, “NFL”, “NCAA”, “Sweet Sixteen tournament”, “European Soccer”, “HBO”, “movie packages”, “late night entertainment”, “foreign film”, “children shows”, “comedy”, etc. Those words may be recorded, converted to text and stored in the user's profile, [Column 6, Lines 19-56]); parsing, by the one or more processors, the human-readable record to determine a content of the first interaction (The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's history information by performing a predictive analysis via a likelihood function 258, [Column 9, Lines 19-56]); and generating, by the one or more processors, the interaction basis information based on the content of the first interaction (During the user history identification procedure, the inquiry/call purpose may be identified via a predictive analysis that applied the likelihood function to a prediction operation that labels the user's inquiry as being associated with a particular purpose 260. The next determination may be to determine whether the inquiry message or call should be responded to with a promotional advertisement or whether the user needs immediate support 262. If the call requires support from a technical perspective or other service oriented issue, the call may be automatically forwarded to a call center agent in the corresponding department 264 that can respond with an automated all service, an automated text message service or even a live agent service, [Column 6, Line 57 – Column 7, Line 7], [Column 8, Line 34 – Column 9, Line 6]). Regarding claim 7, Webster further discloses the interaction basis information comprises historical records of the first interaction (the user may have posted information on a blog, such as jokes and comments to certain friend accounts of the user, such as references to certain sports teams, comments about recent movies, political comments, vacation information, etc. Those words may be identified and stored in the user's profile account. The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's social networking account information, [Column 8, Line 34 – Column 9, Line 6]) and a plurality of further interactions with the entity (if the user has updated his or her profile 274 to include entries in a blog, profile information, posted links, photos, locations, places, sports, entertainment, special interests, charities, etc., then the user may be identified as having a special interest or preference that is associated with a service or product that can be offered by the customer support system 115, [Column 7, Line 44 – Column 8, Line 6]). Regarding claim 8, Webster further discloses routing, by the one or more processors, a communication channel associated with a second entity interaction to a resource based on the interaction basis information (the user may be accessing customer support via any communication channel/medium, such as email, live chat applications, website access, and mobile device applications. For example, transmitting menu options and/or automatically selecting a menu option for a user may be performed responsive to identifying the user and one or more of his or her preferences for processing customer support inquiries, or perhaps bypassing a menu and providing direct access to an automated customer support dialogue operation of the customer service processing system, [Column 9, Line 61 – [Column 10, Line 6]). Regarding claim 9, Webster further discloses the query includes an indication of an interaction basis (The users that may have elected to have billing information as their top priority will be identified according to a confirmed menu option choice that is stored in the user's profile information. The profile information will be retrieved based on the identified user information and used as a flag or identifier by the call processing system as a trigger to provide an automated ‘present balance due’ parameter to the user without delay, [Column 3, Lines 24-49]). Regarding claim 10, Webster further discloses the interaction basis information comprises a prediction of an interaction basis, based on the historical records (The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's history information by performing a predictive analysis via a likelihood function 258. The basic operation of the likelihood function may identify a frequency of terms related to a broader subject and identify the user's preferences accordingly, [Column 6, Lines 19-56], [Column 8, Line 34 – Column 9, Line 6]). Regarding claim 12, Webster further discloses: the first interaction with the entity comprises a first electronic communication (In the event that the user device transmits an inquiry, such as a request for service or assistance via a dialed call, an application message generation selection option on a smartphone application or via another option, such as SMS messaging, the message may be generated 250 and transmitted from the user device 242 to a customer support site 244, [Column 6, Lines 4-18]); the indication of the entity identity comprises a telephone number associated with the first electronic communication (The message may be received and processed to identify and authorize 252 the user via the user's phone number, IP address, username, credentials, electronic certificate, etc., [Column 6, Lines 4-18]); the query is generated responsive to a telephonic communication associated with the telephone number, the query generated during the telephonic communication (The user may be paired with a particular account and/or a set of user preferences stored in a database 246. The user account or preferences may be derived from previous calls or interactions received from the user and/or user selections, user subscription data, etc, [Column 6, Lines 4-18]); the interaction basis information is based on a data record generated based on the signal (The user history may be retrieved 254, [Column 6, Lines 4-18]. The user may have called the customer support 244 and spoke words, such as “sports”, “football”, “movies”, “high speed Internet”, “affordable”, “NFL”, “NCAA”, “Sweet Sixteen tournament”, “European Soccer”, “HBO”, “movie packages”, “late night entertainment”, “foreign film”, “children shows”, “comedy”, etc. Those words may be recorded, converted to text and stored in the user's profile. The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's history information by performing a predictive analysis via a likelihood function 258, [Column 6, Lines 19-56]); and the interaction basis information is presented to a display for a client support agent receiving the telephonic communication (The user history may be retrieved 254 and forwarded 256 to the customer support server 244, [Column 6, Lines 4-18]). Regarding claim 13, Bellavista clearly shows and discloses a non-transitory computer-readable medium having machine instructions stored thereon, the instructions being executable by a processor to cause the processor to perform operations (Figure 13) comprising: intercepting a message conveyed between a transmission server and a reception server (the data that the communication network 10 intercepts as part of LI includes copies of the content of communications transmitted between the communication devices 12. The content of communications may, for example, include any material or information concerning the substance, purport, or meaning of the communications, [0048]), the transmission server and the reception server separate from the processor (FIG. 1 shows that a point of intercepted (POI) 18 in the communication network 10 intercepts data in this way as part of LI. The POI 18 may be a physical, logical, or functional point at which data is intercepted. The POI 18 may for instance be, or be hosted at, an access element, a network connectivity element, or a service element in the communication network 10, [0049-[0050]); extracting a signal corresponding to a first interaction with an entity from the message (the intercepted data may include material or information related to the interception of communications transmitted between the communication devices 12. Such intercepted-related information (IRI) may for example include dialing, signaling, or addressing information that identifies the origin, direction, destination, or termination of each communication generated or received by a subscriber by means of any equipment, facility, or service of a service provider, [0048]. In step 1310, the host 1302 initiates a transmission carrying the user data towards the UE 1306. The host 1302 may initiate the transmission responsive to a request transmitted by the UE 1306. The request may be caused by human interaction with the UE 1306 or by operation of the client application executing on the UE 1306, [0185]); determining an indication of an entity identity based on the signal (Consider an example in which the application-layer control protocol is the Session Initiation Protocol (SIP) such that the application-layer control messages 24 are SIP messages. In one such embodiment, each application-layer control session 26 corresponds to a SIP call leg. A SIP call may refer to a collection of one or more SIP call legs, where a SIP call leg refers to a one-to-one signaling relationship between two SIP user agents. In this context, the session identity (SID) field 28 may be a Call-ID field. The Call-ID field's value may be set to a cryptographically random identifier which is unique across SIP call legs, [0055]. The network mediation device 32 stores the couple [“Call-ID”, “extendedSession”] for the first SIP message intercepted. The value of “extendedSession” is a counter that will be increased at each new SMS service interception, e.g., as determined according to a service expiration timer. When a new SMS message is intercepted, the “In-Reply-To” field is detected and the network mediation device 32 verifies if the header contains the Call-ID number fetched from the internal cache according to the previous step. If case of a match, the network mediation device 32 gets the “extendedSession” value from the cache and provides it towards the handover interface 33 for the new SMS message, [0094]. The user data is associated with a particular human user interacting with the UE 1306. The request may be caused by human interaction with the UE 1306 or by operation of the client application executing on the UE 1306. The transmission may pass via the network node 1304. Accordingly, in step 1312, the network node 1304 transmits to the UE 1306 the user data that was carried in the transmission that the host 1302 initiated, [0185]). Webster then additionally or alternatively discloses: extracting a signal corresponding to a first interaction with an entity (In the event that the user device transmits an inquiry, such as a request for service or assistance via a dialed call, an application message generation selection option on a smartphone application or via another option, such as SMS messaging, the message may be generated 250 and transmitted from the user device 242 to a customer support site 244, [Column 6, Lines 4-18]); determining an entity identity based on the signal (The message may be received and processed to identify and authorize 252 the user via the user's phone number, IP address, username, credentials, electronic certificate, etc., [Column 6, Lines 4-18]); receiving a query associated with the entity identity (The user may be paired with a particular account and/or a set of user preferences stored in a database 246. The user account or preferences may be derived from previous calls or interactions received from the user and/or user selections, user subscription data, etc, [Column 6, Lines 4-18]); generating, responsive to the query, interaction basis information based on the signal (The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's social networking account information by performing a predictive analysis via a likelihood function 290. The basic operation of the likelihood function may identify a frequency of terms related to a broader subject, such as sports, politics, movies, etc., and identify the user's preferences accordingly. For example, in the above example the written terms may mostly relate to politics and all such terms may be written by a user, submitted in blog postings and/or were comments submitted electronically and on a server of the social networking platform, [Column 8, Line 34 – Column 9, Line 6]); prioritizing the interaction basis information for display (The algorithm of the likelihood function would then likely extract a main preference to be [politics] and a secondary preference to be [sports] based on the various information submitted from the user account. Those preferences then can be queued in order depending on their relevance. The relevance may be based on an assigned weight value proportional to the number of times the words appear for that category, [Column 8, Line 34 – Column 9, Line 6]); and presenting prioritized interaction basis information via a user interface (As a result, the weight for “politics” may be equal to four for that preference while the weight for “sports” may be equal to two, which is a lower weighted user preference. The user device may first be presented with a question related to sports, such as “do you want to hear about new sports packages for your online cable service?” or “are you satisfied with your sports packages?”, [Column 8, Line 34 – Column 9, Line 6]). It would have been obvious to an ordinary person skilled in the art at the time of the invention was effectively filed to incorporate the teachings of Webster with the teachings of Bellavista for the purpose of providing a seamless transactional experience for users based on personalized interactive options using derived preferences from the extracted identities of the users. Regarding claim 14, Webster further discloses storing a data record corresponding to a message, the data record comprising the entity identity (the user may have called the customer support 244 and spoke words, such as “sports”, “football”, “movies”, “high speed Internet”, “affordable”, “NFL”, “NCAA”, “Sweet Sixteen tournament”, “European Soccer”, “HBO”, “movie packages”, “late night entertainment”, “foreign film”, “children shows”, “comedy”, etc. Those words may be recorded, converted to text and stored in the user's profile, [Column 8, Line 34 – Column 9, Line 6]), wherein receiving the signal comprises establishing a connector with a monitoring port, the connector configured to intercept the message (when the user device transmits an inquiry message to the customer support system 115, the user's social networking information (when the user device transmits an inquiry message to the customer support system 115, the user's social networking information e.g., FACEBOOK®, TWITTER®, LINKEDIN®, etc.), and the information may be parsed to identify terms that match a predefined list of terms used to identify and create preferences associated with the user. For example, if the user has updated his or her profile 274 to include entries in a blog, profile information, posted links, photos, locations, places, sports, entertainment, special interests, charities, etc., then the user may be identified as having a special interest or preference that is associated with a service or product that can be offered by the customer support system 115, [Column 7, Line 44 – Column 8, Line 6]). Regarding claim 15, Webster further discloses the interaction basis information is based on: the first interaction (the user may have posted information on a blog, such as jokes and comments to certain friend accounts of the user, such as references to certain sports teams, comments about recent movies, political comments, vacation information, etc. Those words may be identified and stored in the user's profile account. The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's social networking account information, [Column 8, Line 34 – Column 9, Line 6]); and a plurality of further interactions with the entity (if the user has updated his or her profile 274 to include entries in a blog, profile information, posted links, photos, locations, places, sports, entertainment, special interests, charities, etc., then the user may be identified as having a special interest or preference that is associated with a service or product that can be offered by the customer support system 115, [Column 7, Line 44 – Column 8, Line 6]). Regarding claim 16, Webster further discloses the prioritization is based on: a recency of one or more data records of the interaction basis information (the politics related terms “gun control”, “Obama”, “Congress”, etc., may appear four times in the user's personal stored information and the terms “LA Lakers” and “NFL” are two instances of sports terms, and may be required to appear over a recent window of time, such as 10, 20, 30, 60 days, [Column 8, Line 34 – Column 9, Line 6]); a communications channel for the one or more data records of the interaction basis information (The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's social networking account information by performing a predictive analysis via a likelihood function 290, [Column 8, Line 34 – Column 9, Line 6]); and a content of the one or more data records of the interaction basis information (the user may have posted information on a blog, such as jokes and comments to certain friend accounts of the user, such as references to certain sports teams, comments about recent movies, political comments, vacation information, etc, [Column 8, Line 34 – Column 9, Line 6]). Regarding claim 17, Webster further discloses routing an electronic communication to a client support agent based on the interaction basis information (if a user is a platinum customer, the application would look at agent availability and transfer the user directly to an agent if one is available or provide the user with their favorite menu choices, [Column 10, Lines 28-43]). Regarding claim 18, Webster further discloses the query includes an indication of an interaction basis (The users that may have elected to have billing information as their top priority will be identified according to a confirmed menu option choice that is stored in the user's profile information. The profile information will be retrieved based on the identified user information and used as a flag or identifier by the call processing system as a trigger to provide an automated ‘present balance due’ parameter to the user without delay, [Column 3, Lines 24-49]). Regarding claim 20, Bellavista clearly shows and discloses a first server (Figure 1) configured to: intercept a message conveyed between a transmission server and a reception server (the data that the communication network 10 intercepts as part of LI includes copies of the content of communications transmitted between the communication devices 12. The content of communications may, for example, include any material or information concerning the substance, purport, or meaning of the communications, [0048]), the transmission server and the reception server separate from the first server (FIG. 1 shows that a point of intercepted (POI) 18 in the communication network 10 intercepts data in this way as part of LI. The POI 18 may be a physical, logical, or functional point at which data is intercepted. The POI 18 may for instance be, or be hosted at, an access element, a network connectivity element, or a service element in the communication network 10, [0049-[0050]); extract from a plurality of connectors corresponding to a plurality of data sources, a first plurality of signals corresponding to one or more first entity interactions from the message (the intercepted data may include material or information related to the interception of communications transmitted between the communication devices 12. Such intercepted-related information (IRI) may for example include dialing, signaling, or addressing information that identifies the origin, direction, destination, or termination of each communication generated or received by a subscriber by means of any equipment, facility, or service of a service provider, [0048]. In step 1310, the host 1302 initiates a transmission carrying the user data towards the UE 1306. The host 1302 may initiate the transmission responsive to a request transmitted by the UE 1306. The request may be caused by human interaction with the UE 1306 or by operation of the client application executing on the UE 1306, [0185]); determine, based on one or more of the first plurality of signals, an indication of an entity identity (Consider an example in which the application-layer control protocol is the Session Initiation Protocol (SIP) such that the application-layer control messages 24 are SIP messages. In one such embodiment, each application-layer control session 26 corresponds to a SIP call leg. A SIP call may refer to a collection of one or more SIP call legs, where a SIP call leg refers to a one-to-one signaling relationship between two SIP user agents. In this context, the session identity (SID) field 28 may be a Call-ID field. The Call-ID field's value may be set to a cryptographically random identifier which is unique across SIP call legs, [0055]. The network mediation device 32 stores the couple [“Call-ID”, “extendedSession”] for the first SIP message intercepted. The value of “extendedSession” is a counter that will be increased at each new SMS service interception, e.g., as determined according to a service expiration timer. When a new SMS message is intercepted, the “In-Reply-To” field is detected and the network mediation device 32 verifies if the header contains the Call-ID number fetched from the internal cache according to the previous step. If case of a match, the network mediation device 32 gets the “extendedSession” value from the cache and provides it towards the handover interface 33 for the new SMS message, [0094]. The user data is associated with a particular human user interacting with the UE 1306. The request may be caused by human interaction with the UE 1306 or by operation of the client application executing on the UE 1306. The transmission may pass via the network node 1304. Accordingly, in step 1312, the network node 1304 transmits to the UE 1306 the user data that was carried in the transmission that the host 1302 initiated, [0185]). Webster then additionally or alternatively discloses: extract, from a plurality of connectors corresponding to a plurality of data sources, a first plurality of signals corresponding to one or more first entity interactions (In the event that the user device transmits an inquiry, such as a request for service or assistance via a dialed call, an application message generation selection option on a smartphone application or via another option, such as SMS messaging, the message may be generated 250 and transmitted from the user device 242 to a customer support site 244, [Column 6, Lines 4-18]); determine, based on one or more of the first plurality of signals, an indication of an entity identity (The message may be received and processed to identify and authorize 252 the user via the user's phone number, IP address, username, credentials, electronic certificate, etc., [Column 6, Lines 4-18]); receive a query associated with the entity, a data field of the query corresponding to the entity identity (The user may be paired with a particular account and/or a set of user preferences stored in a database 246. The user account or preferences may be derived from previous calls or interactions received from the user and/or user selections, user subscription data, etc, [Column 6, Lines 4-18], [Column 8, Line 34 – Column 9, Line 6]); generate, responsive to the query, interaction basis information for presentation, the interaction basis information based on the signal (The user's profile may be retrieved when the user seeks access to the customer support service 244 and then preferences may be derived from the user's social networking account information by performing a predictive analysis via a likelihood function 290. The basic operation of the likelihood function may identify a frequency of terms related to a broader subject, such as sports, politics, movies, etc., and identify the user's preferences accordingly. For example, in the above example the written terms may mostly relate to politics and all such terms may be written by a user, submitted in blog postings and/or were comments submitted electronically and on a server of the social networking platform, [Column 8, Line 34 – Column 9, Line 6]); and present the interaction basis information (As a result, the weight for “politics” may be equal to four for that preference while the weight for “sports” may be equal to two, which is a lower weighted user preference. The user device may first be presented with a question related to sports, such as “do you want to hear about new sports packages for your online cable service?” or “are you satisfied with your sports packages?”, [Column 8, Line 34 – Column 9, Line 6]). It would have been obvious to an ordinary person skilled in the art at the time of the invention was effectively filed to incorporate the teachings of Webster with the teachings of Bellavista for the purpose of providing a seamless transactional experience for users based on personalized interactive options using derived preferences from the extracted identities of the users. Claims 6, 11, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Bellavista in view of Webster and further in view of Hartman et al. (Pub. No. US 2020/0045178, published on February 6, 2020; hereinafter Hartman). Regarding claim 6, Webster further discloses determining, by the one or more processors, an account type based on the indication of the entity identity, wherein the plurality of signals is prioritized based on the account type (if a user is a platinum customer, the application would look at agent availability and transfer the user directly to an agent if one is available or provide the user with their favorite menu choices, [Column 10, Lines 28-43]). Hartman then discloses the indication of the entity identity is an account number for one account type of a plurality of account types (the external entities 180A-180N may include businesses and other organizations that seek to offer phone-based service or support to their customers (or potential customers) through IVR processes. As another example, the external entities 180A-180N may include individual merchants who offer goods and/or services through a common electronic marketplace that is open to many such merchants, [0022]. The user metadata may include a user's full name, a user's street address, a user's e-mail address, a user's phone number for contacting or being contacted by entities 180A-180N, [0047]). It would have been obvious to an ordinary person skilled in the art at the time of the invention was effectively filed to incorporate the teachings of Hartman with the teachings of Bellavista, as modified by Webster, for the purpose of utilizing known data associated an entity to provide user-friendly support and enable interactive response associated with a request from the entity based at least one the entity’s identity and preferences. Regarding claims 11, and 19, Hartman further discloses: the entity comprises a plurality of sub-entities, each sub-entity associated with a unique identifier (the device-specific accounts may be assigned to another “umbrella” account or a pool of accounts, such as a corporate account associated with an organizational customer of the service provider environment, e.g., for ease of device management, [0047]); and the interaction basis information is based on a first unique identifier associated with the first interaction (the request 131 may include suitable information associated with the entity 180A, such as a phone number at which the entity can be contacted, a name of the entity, an Internet domain name of the entity, and so on, [0025]. The order history may be retrieved from a component of the service provider environment or from a component of the external entity 180A, e.g., a data store associated with that entity, [0031]), and a second unique identifier associated with the query (In response to the request 131, the IVR registration component 130 may generate a certificate 132 that is specific to the entity 180A. The IVR registration component 130 may send the certificate 132 to the computing device 185A or to any other address or storage location at which the entity 180A expects to receive the certificate. The IVR registration component 130 may also store a copy of the certificate 132, e.g., in order to compare the stored copy with a copy retrieved from the entity 180A in the future, [0026]). Relevant Prior Art The following references are considered relevant to the claims: Henning et al. (Pub. No. US 2005/075946) teaches when a customer accesses a web page that has been populated with personalized content delivery code (PCDC), the customer's browser executes the PCDC contained in the web page. Upon execution of the PCDC, the customer's computer sends a query to the content management server(s), in which the PCDC identifies the client, a secondary identifier that reveals additional information about the customer's access. Mummadi et al. (Pub. No. US 2020/0233918) teaches dynamically determining a server for enrollment with a management system. User input is received at an application executing on a user device, such as a portal application that provides access to and authentication for other applications through a catalogue of application icons. If the user input includes a first URL but that URL produces an error when used in conjunction with extensions associated with a management server, the application can automatically use extensions associated with an application-support server. The application can then retrieve a second URL from the application-support server and use it for performing enrollment steps at the management server. Conclusion 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. Contact Information Any inquiry concerning this communication or earlier communications from the Examiner should be directed to Son T. Hoang whose telephone number is (571) 270-1752. The Examiner can normally be reached on Monday – Friday (7:00 AM – 4:00 PM). If attempts to reach the Examiner by telephone are unsuccessful, the Examiner’s supervisor, Sherief Badawi can be reached on (571) 272-9782. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /SON T HOANG/Primary Examiner, Art Unit 2169 March 31, 2026
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Prosecution Timeline

Feb 26, 2025
Application Filed
Nov 03, 2025
Non-Final Rejection mailed — §103
Jan 28, 2026
Response Filed
Jan 28, 2026
Examiner Interview Summary
Jan 28, 2026
Applicant Interview (Telephonic)
Apr 03, 2026
Final Rejection mailed — §103
May 27, 2026
Examiner Interview Summary
May 27, 2026
Applicant Interview (Telephonic)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
83%
Grant Probability
99%
With Interview (+35.0%)
2y 11m (~1y 8m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 909 resolved cases by this examiner. Grant probability derived from career allowance rate.

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