SYSTEMS AND METHODS FOR AN AI-BASED CONVERSATIONAL WEB APPLICATION
Disclosed are systems and methods that provide a decision-intelligence (DI)-based, computerized framework that provides advancements in how users interact with chatbots, as well as how they can engage with content and services over a computer network. The disclosed framework provides a conversational web experience whereby a user can engage with a chatbot or chatbots simultaneously and/or sequentially via a series of handoffs that are correlated to the context of the user's engagement. Thus, the types and/or interactive content the user is engaging with on the Internet can drive the types, quantities and/or timing of how chatbots are presented to the user for purposes of facilitating the engagement of the user with network hosted content.
1 . A method comprising steps of:
identifying engagement between a user and a first chatbot, the first chatbot associated with a first electronic resource, the engagement corresponding to a first topic;
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; and
executing a handoff of the engagement from the first chatbot to the second chatbot, the handoff enabling the user to continue the engagement respective to the second topic with the second chatbot.
2 . 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.
3 . The method of claim 1 , further comprising the first chatbot and the second chatbot remaining available for interaction with the user during the handoff.
4 . The method of claim 1 , further comprising the first chatbot and the second chatbot remaining available for interaction with the user after the handoff.
5 . The method of claim 1 , further comprising:
outputting, via a large language model (LLM), a prompt requesting approval of the second chatbot;
receiving, in response to the prompt, feedback from the user;
analyzing, via the LLM, the feedback; and
performing the handoff to the second chatbot based on the LLM analysis of the feedback.
6 . The method of claim 1 , further comprising:
identifying a set of second chatbots, each of the second chatbot 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.
7 . The method of claim 1 , further comprising conversational engagement with the first chatbot comprising conversational interactions with the user and the first chatbot, wherein the conversational interactions comprise at least one of an audible output and displayed content on a device of the user.
8 . The method of claim 1 , further comprising identifying whether either the first electronic resource or the second electronic resource is a network resource.
9 . A system comprising:
a processor configured to:
identify engagement between a user and a first chatbot, the first chatbot associated with a first electronic resource, the engagement corresponding to a first topic;
analyze the engagement, and identify a second chatbot, the second chatbot configured to provide engagement functionality with a second electronic resource related to a second topic; and
execute a handoff of the engagement from the first chatbot to the second chatbot, the handoff enabling the user to continue the engagement respective to the second topic with the second chatbot.
10 . The system of claim 9 , wherein the processor is further configured to:
determine, 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.
11 . The system of claim 9 , wherein the processor is further configured for the first chatbot and the second chatbot to remain available for interaction with the user during the handoff.
12 . The system of claim 9 , wherein the processor is further configured for the first chatbot and the second chatbot to remain available for interaction with the user after the handoff.
13 . The system of claim 9 , wherein the processor is further configured to:
output, via a large language model (LLM), a prompt requesting approval of the second chatbot;
receive, in response to the prompt, feedback from the user;
analyze, via the LLM, the feedback; and
perform the handoff to the second chatbot based on the LLM analysis of the feedback.
14 . The system of claim 9 , wherein the processor is further configured to:
identify a set of second chatbots, each of the second chatbot providing information related to the second topic;
execute 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
select the second chatbot based on the auction operations.
15 . The system of claim 9 , wherein the processor is further configured for the conversational engagement with the first chatbot comprising conversational interactions with the user and the first chatbot, wherein the conversational interactions comprise at least one of an audible output and displayed content on a device of the user.
16 . The system of claim 9 , wherein the processor is further configured to:
identify whether either the first electronic resource or the second electronic resource is a network resource.
17 . A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions that when executed by a device, perform a method comprising:
identifying engagement between a user and a first chatbot, the first chatbot associated with a first electronic resource, the engagement corresponding to a first topic;
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; and
executing a handoff of the engagement from the first chatbot to the second chatbot, the handoff enabling the user to continue the engagement respective to the second topic with the second chatbot.
18 . The non-transitory computer-readable storage medium of claim 17 , 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.
19 . The non-transitory computer-readable storage medium of claim 17 , further comprising:
outputting, via a large language model (LLM), a prompt requesting approval of the second chatbot;
receiving, in response to the prompt, feedback from the user;
analyzing, via the LLM, the feedback; and
performing the handoff to the second chatbot based on the LLM analysis of the feedback.
20 . The non-transitory computer-readable storage medium of claim 17 , further comprising:
identifying a set of second chatbots, each of the second chatbot 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.