Systems and methods for external system integration

A computer-implemented method, comprising:

• receiving a message associated with a user, wherein the message is associated with an intent;
• facilitating a communications session between the user and an automated bot, wherein the automated bot, wherein when the communications session is facilitated, the automated bot automatically extracts the intent from the message;
• training a machine learning model using a sample dataset, wherein the sample dataset includes sample messages and corresponding actions performable to address intents associated with the sample messages;
• processing the intent and one or more messages exchanged during the communications session through the machine learning model to identify an action performable to address the intent;
• providing the action, wherein when the action is received at the automated bot, the automated bot autonomously executes the action to address the intent;
• generating a ticket, wherein the ticket is used to track the one or more messages and the action as the one or more messages are exchanged and the action is performed;
• and
• updating the machine learning model based on the intent and performance of the action.

A system, comprising:

• one or more processors;
• and
• memory storing thereon instructions that, as a result of being executed by the one or more processors, cause the system to:
• receive a message associated with a user, wherein the message is associated with an intent;
• facilitate a communications session between the user and an automated bot, wherein the automated bot, wherein when the communications session is facilitated, the automated bot automatically extracts the intent from the message;
• train a machine learning model using a sample dataset, wherein the sample dataset includes sample messages and corresponding actions performable to address intents associated with the sample messages;
• process the intent and one or more messages exchanged during the communications session through the machine learning model to identify an action performable to address the intent;
• provide the action, wherein when the action is received at the automated bot, the automated bot autonomously executes the action to address the intent;
• generate a ticket, wherein the ticket is used to track the one or more messages and the action as the one or more messages are exchanged and the action is performed;
• and
• update the machine learning model based on the intent and performance of the action.

A non-transitory, computer-readable storage medium storing thereon executable instructions that, as a result of being executed by one or more processors of a computer system, cause the computer system to:

• receive a message associated with a user, wherein the message is associated with an intent;
• facilitate a communications session between the user and an automated bot, wherein the automated bot, wherein when the communications session is facilitated, the automated bot automatically extracts the intent from the message;
• train a machine learning model using a sample dataset, wherein the sample dataset includes sample messages and corresponding actions performable to address intents associated with the sample messages;
• process the intent and one or more messages exchanged during the communications session through the machine learning model to identify an action performable to address the intent;
• provide the action, wherein when the action is received at the automated bot, the automated bot autonomously executes the action to address the intent;
• generate a ticket, wherein the ticket is used to track the one or more messages and the action as the one or more messages are exchanged and the action is performed;
• and
• update the machine learning model based on the intent and performance of the action.