Systems and methods for proactive response generation in multi-user sessions

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 perform a method including:
• receiving an instruction message for an automated agent to enter a processing state, wherein the instruction message is transmitted through a real-time chat interface by a user of a set of users;
• analyzing the instruction message to detect that a task is to be performed, wherein analyzing the instruction message includes determining that performing the task requires additional information, and wherein determining includes classifying the automated agent in a standby state;
• generating a survey message in the real-time chat interface to request additional information from the set of users;
• processing responses from the set of users to the survey message in the real-time chat interface, wherein processing includes inputting the responses into a natural language processor to determine the additional information;
• and
• adding a task message to the real-time chat interface, wherein adding the task message includes classifying the automated agent in the processing state, and wherein the method does not include a request from the set of users to perform the task using the additional information, thereby improving efficiency of the real-time chat interface.

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 perform a method comprising:

• receiving an instruction message for an automated agent to enter a processing state, wherein the instruction message is transmitted through a real-time chat interface by a user of a set of users;
• analyzing the instruction message to detect that a task is to be performed, wherein analyzing the instruction message includes determining that performing the task requires additional information, and wherein determining includes classifying the automated agent in a standby state;
• generating a survey message in the real-time chat interface to request additional information from the set of users;
• processing responses from the set of users to the survey message in the real-time chat interface, wherein processing includes inputting the responses into a natural language processor to determine the additional information;
• and
• adding a task message to the real-time chat interface, wherein adding the task message includes classifying the automated agent in the processing state, and wherein the method does not include a request from the set of users to perform the task using the additional information, thereby improving efficiency of the real-time chat interface.