Response to an Amendment
This office action is a response to a Communication made on 02/13/2026.
Claims 1, 6, 9, 14, 17 and 20 are currently amended.
Claims 1-20 are pending for this application.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1, 9 and 17 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Applicant’s arguments, see remarks on page 7-8, filed 02/13/2026, with respect to the rejection(s) of claim(s) 1, 9 and 17 under 102(a)(1) have been considered and regarding the amended feature of “the first electronic resource associated with a first entity and the second electronic resource associated with a second entity” are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Ringhiser et al. (US 2021/0058844) in view of Gershony et al. (US 2017/0180276).
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.
Claim(s) 1-5, 7-13 and 15-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ringhiser et al. (US 2021/0058844), hereinafter “Ringhiser” in view of Gershony et al. (US 2017/0180276), hereinafter “Gershony”.
With respect to claim 1, Ringhiser discloses a method comprising steps of:
identifying engagement between a user and a first chatbot (¶0033, teaches identify an intent of the language used by the user during engagement with the bot. The intent monitor 132 may monitor turns of conversation between a customer and a bot via the bot's logic), the first chatbot associated with a first electronic resource (¶0027, teaches the network environment (i.e. network resource as first electronic resource) 100 includes a bot 104 that executes via an electronic device 106, and a bot 105 that executes via an electronic device 107), the engagement corresponding to a first topic (¶0036, teaches the subject (i.e. topic) of the bot conversation);
analyzing the engagement, and identifying a second chatbot, the second chatbot configured to provide engagement functionality with a second electronic resource related to a second topic (¶0027, teaches the network environment (i.e. network resource as first electronic resource or second electronic resource) 100 includes a bot 104 that executes via an electronic device 106, and a bot 105 that executes via an electronic device 107, ¶0036, teaches the system may pass the conversation to a second bot, ¶0049, teaches intent monitors to analyze user input within a conversation…the system may transparently pass along the subject of the bot dialog (i.e. second topic));and
executing a handoff of the engagement from the first chatbot to the second chatbot (¶0033-¶0034, teaches identify an intent of the language used by the user during engagement with the bot. The intent monitor 132 may monitor turns of conversation between a customer and a bot via the bot's logic … the machine learning algorithm may learn when a bot is triggered to handoff to a second bot or human support agent, ¶0039, teaches In response to an assessment of the factors that triggers a handoff, a type of handoff may be determined and the handoff is performed to enable control of the conversation by another second bot or human support agent), the handoff enabling the user to continue the engagement respective to the second topic with the second chatbot (¶0036, teaches the recognition that a second bot or human support agent is better equipped to solve the user's issues (i.e. second topic) is a trigger that causes a handoff from the current bot to the second bot or human support agent, ¶0075, teaches executing the determined handoff to the second bot or the human support agent, wherein the second bot or the human support agent engages the user in conversation to execute functionality desired by the user, see ¶0059-¶006).
However, Ringhiser remains silent on the first electronic resource associated with a first entity and the second electronic resource associated with a second entity.
Gershony discloses the first electronic resource associated with a first entity and the second electronic resource associated with a second entity (¶0005, teaches determining a first bot of a first type based on the one or more messages and determining a second bot of a second type based on the one or more messages. The second type is different from the first type… a bot of a first type may be a restaurant reservation bot and a bot of a second type may be a food order bot, ¶0077-¶0080, teaches A first bot of a first type may be determined for the first user based on the messages. The bot may be a human agent, an automated agent, an automatic responder, etc. In some implementations, the bot may be a hybrid where communications are provided by multiple entities (i.e. first and second entity) that may include a human agent at some points, and an automatic agent at some other points… the first bot may be selected over the second bot based on content (i.e. resource) within the one or more messages. For example, the first bot may be selected based on “meet” appearing more times than “order” in the messages, ¶0083, teaches the messaging application 103 determines that a given message of the messages includes one or more terms that are associated with invocation of two or more bots. For example, a given message of “reservations?” may be associated with invocation of both a restaurant reservation bot and a separate airline reservation bot. In some of those implementations, the messaging application 103 selects one of the bots over the other bots based on one or more additional terms of an additional message of the messages also being associated with invocation of the selected bot, but not being associated with invocation of the non-selected bot(s), ¶0095, teaches messages that are part of an initial conversation between two or more users to determine one or more entities that may be associated with an action).
Therefore, it would be obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Ringhiser’s first and second bot with the first electronic resource associated with a first entity and the second electronic resource associated with a second entity of Gershony, in order to uniquely identify, manage, and relate different pieces of digital information (Gershony).
For claim 9, it is a system claim corresponding to the method of claim 1. Therefore claim 9 is rejected under the same ground as claim 1.
For claim 17, it is a non-transitory computer-readable storage medium claim corresponding to the method of claim 1. Therefore claim 17 is rejected under the same ground as claim 1.
With respect to claims 2, 10 and 18, Ringhiser in view of Gershony discloses the method of claim 1, further comprising:
determining, based on the analysis of the engagement, that the engagement transitioned from the first topic to the second topic, wherein the handoff to the second chatbot is based on the transition determination (Ringhiser, ¶0036, teaches the recognition that a second bot or human support agent is better equipped to solve the user's issues (i.e. second topic) is a trigger that causes a handoff from the current bot to the second bot or human support agent…passing the conversation to the second bot or human support agent may include transmitting the subject (i.e. first topic) of the bot conversation, ¶0075, teaches executing the determined handoff to the second bot or the human support agent, wherein the second bot or the human support agent engages the user in conversation to execute functionality desired by the user).
With respect to claims 3 and 11, Ringhiser in view of Gershony discloses the method of claim 1, further comprising the first chatbot and the second chatbot remaining available for interaction with the user during the handoff (Ringhiser, ¶0030, teaches one or more bots may be available in the network environment 100, ¶0033, teaches the intent monitor 132 may identify an intent of the language used by the user. The intent monitor 132 may monitor turns of conversation between a customer and a during engagement with the bot bot via the bot's logic.¶0068, teaches enable a two-way handoff from a bot to a second bot or human support agent, and from the second bot or human support agent to the first bot. Through the two-way handoff, the first bot may automatically reengage in conversation with the user, or the second bot/human support agent can deliberately transfer control back to the first bot at an appropriate juncture. The present techniques enable a single human support agent can scale human provided support more effectively across a larger number of user-bot interactions).
With respect to claims 4 and 12, Ringhiser in view of Gershony discloses the method of claim 1, further comprising the first chatbot and the second chatbot remaining available for interaction with the user after the handoff (Ringhiser, ¶0030, teaches one or more bots may be available in the network environment 100, ¶0068, teaches enable a two-way handoff from a bot to a second bot or human support agent, and from the second bot or human support agent to the first bot. Through the two-way handoff, the first bot may automatically reengage in conversation with the user, or the second bot/human support agent can deliberately transfer control back to the first bot at an appropriate juncture. The present techniques enable a single human support agent can scale human provided support more effectively across a larger number of user-bot interactions.
With respect to claims 5, 13 and 19, Ringhiser in view of Gershony discloses the method of claim 1, further comprising:
outputting, via a large language model (LLM), a prompt requesting approval of the second chatbot (Ringhiser, ¶0019, teaches the user may be presented with an option to approve a handoff, ¶0032, teaches the machine learning module 130 enables the bot to learn from the entities and intents extracted from the user input via natural language processing (i.e. LLM).);
receiving, in response to the prompt, feedback from the user (Ringhiser, ¶0019, teaches the first bot may use feedback to train and update the learning models to improve the bot's responses over time based on each user);
analyzing, via the LLM, the feedback (Ringhiser, ¶0019, teaches the first bot may use feedback to train and update the learning models to improve the bot's responses over time based on each user, ¶0032, teaches the machine learning module 130 enables the bot to learn from the entities and intents extracted from the user input via natural language processing (i.e. LLM)); and
performing the handoff to the second chatbot based on the LLM analysis of the feedback (Ringhiser, ¶0058, teaches during this exchange or turn of communication, the intent monitor may operate to capture data, feedback, known information of the user, or other attributes that may be used to grow or train a model that determines when handoffs occur, ¶0032, teaches the machine learning module 130 enables the bot to learn from the entities and intents extracted from the user input via natural language processing (i.e. LLM)).
With respect to claims 7 and 15, Ringhiser in view of Gershony discloses the method of claim 1, further comprising conversational engagement with the first chatbot comprising conversational interactions with the user and the first chatbot (Ringhiser, ¶0019, teaches the bot can respond to user input based on a conversational context of the input), wherein the conversational interactions comprise at least one of an audible output and displayed content on a device of the user (Ringhiser, ¶0032, teaches the response generation module may transmit the pre-written response to a dialogue client where it is rendered for the user in a text, auditory, or visual format, ¶0052, teaches a user may read the response as generated by the bot. In embodiments, the dialogue client may also render an audio response.).
With respect to claims 8 and 16, Ringhiser in view of Gershony discloses the method of claim 1, further comprising identifying whether either the first electronic resource or the second electronic resource is a network resource (Ringhiser, ¶0027, teaches the network environment (i.e. network resource as first electronic resource) 100 includes a bot 104 that executes via an electronic device 106, and a bot 105 that executes via an electronic device 107).
Claim(s) 6, 14 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ringhiser in view of Gershony, and further in view of Abraham (US 2018/0376002).
With respect to claims 6, 14 and 20, Ringhiser in view of Gershony discloses the method of claim 1. However; Ringhiser in view of Gershony remain silent on further comprising: identifying a set of second chatbots, each of the set of second chatbots providing information related to the second topic; executing auction operations with each of the set of second chatbots, the auction operations enabling each of the set of second chatbots to bid for a slot within a user interface (UI) on a device of the user; and selecting the second chatbot based on the auction operations.
Abraham discloses further comprising:
identifying a set of second chatbots, each of the set of second chatbots providing information related to the second topic (¶0031, teaches conversations handled by the conversation bots (i.e. set of second chatbots), ¶0079, teaches a list of suggested topics, for continuing the call with the client to allow the human agent time to get into the flow of the ongoing conversation);
executing auction operations with each of the set of second chatbots, the auction operations enabling each of the set of second chatbots to bid for a slot within a user interface (UI) on a device of the user (¶0040, teaches the use of such conversation bots in a sales (i.e. auction) context can provide greater sales efficiency by using multiple bots to qualify multiple leads, enabling a human agent to focus his or her time on only the most promising leads or candidates, ¶0054, teaches the personalized conversation bot can train the human agent using proposed responses that are generated in the style/voice of the human agent, ¶0069, teaches provides a human (e.g., a manager) with a user interface that provides the manager with a view of multiple ongoing conversations between conversation bots and contacts, ¶0079, teaches a cost of the offered (i.e. bid) product or service); and
selecting the second chatbot based on the auction operations (¶0040, teaches the use of such conversation bots in a sales context can provide greater sales efficiency by using multiple bots to qualify multiple leads, enabling a human agent to focus his or her time on only the most promising leads or candidates. By eliminating the need for the human agent to spend time with qualifying a sales lead, the human agent is able to ramp up throughput based upon spending more time interacting on calls with viable leads, ¶0057, teaches selecting (410) a personalized conversation bot for the conversation. The personalized conversation bots each can be trained based upon the conversation patterns of specific human agents and are used with the voice of the human agent to which they are related).
Therefore, it would be obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Ringhiser’s multiple bots and subject in view of Gershony’s system with executing auction operations with each of the set of second chatbots, the auction operations enabling each of the set of second chatbots to bid for a slot within a user interface (UI) on a device of the user; and selecting the second chatbot based on the auction operations of Abraham, in order to chose the most relevant chatbot, and chatbot offer for a slot on the screen to interact with the user (Abraham).
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GOLAM MAHMUD whose telephone number is (571)270-0385. The examiner can normally be reached Mon-Fri 8.00-5.00pm.
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/G.M/Examiner, Art Unit 2458
/UMAR CHEEMA/Supervisory Patent Examiner, Art Unit 2458
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