Processing system performing dynamic training response output generation control

A method comprising:

• at a computing platform comprising at least one processor, a communication interface, and memory:
• receive, from a user device, a request for a dynamic training interface;
• generate, in response to receiving the request for the dynamic training interface, initial dynamic training interface information;
• generate one or more commands directing the user device to generate an initial dynamic training interface using the initial dynamic training interface information;
• send, via the communication interface, the initial dynamic training interface information and the one or more commands directing the user device to generate the initial dynamic training interface using the initial dynamic training interface information;
• receive, from the user device and in response to the initial dynamic training interface, a training request input;
• generate one or more commands directing a natural language understanding (NLU) engine to perform natural language understanding and processing on the training request input to determine a natural language result output;
• send, to the NLU engine, the training request input and the one or more commands directing the NLU engine to perform natural language understanding and processing on the training request input to determine the natural language result output;
• receive, from the NLU engine, the natural language result output;
• determine one or more third party data sources that correspond to the natural language result output;
• generate one or more commands directing the one or more third party data sources to send source data corresponding to the natural language result output;
• send, to the one or more third party data sources, the one or more commands directing the one or more third party data sources to send source data corresponding to the natural language result output;
• receive, from the one or more third party data sources, the source data corresponding to the natural language result output;
• generate a dynamic training response output based on the natural language result output and the source data;
• generate one or more commands directing the user device to cause display of the dynamic training response output;
• send, to the user device, the dynamic training response output and the one or more commands directing the user device to cause display of the dynamic training response output;
• establishing a wireless data connection with a profile correlation computing platform;
• generating one or more commands directing the profile correlation computing platform to update based on the natural language result output;
• sending, using the wireless data connection with the profile correlation computing platform, the one or more commands directing the profile correlation computing platform to update based on the natural language result output;
• determining, based on an indication from a user, that a final dynamic training response output has been sent;
• determining, after determining that the final dynamic training response output has been sent, that an agent is requested;
• generating one or more commands to identify an agent corresponding to the user of the user device;
• sending, to the profile correlation computing platform, the one or more commands to identify the agent corresponding to the user, wherein sending the one or more commands causes the profile correlation computing platform to determine the agent using one or more machine learning algorithms and one or more machine learning datasets;
• receiving an indication of the agent from the profile correlation computing platform;
• and
• generating one or more commands directing the user device to cause display of the indication of the agent.

One or more non-transitory computer-readable media storing instructions that, when executed by a computing platform comprising at least one processor, a communication interface, and memory, cause the computing platform to:

• receive, from a user device, a request for a dynamic training interface;
• generate, in response to receiving the request for the dynamic training interface, initial dynamic training interface information;
• generate one or more commands directing the user device to generate an initial dynamic training interface using the initial dynamic training interface information;
• send, via the communication interface, the initial dynamic training interface information and the one or more commands directing the user device to generate the initial dynamic training interface using the initial dynamic training interface information;
• receive, from the user device and in response to the initial dynamic training interface, a training request input;
• generate one or more commands directing a natural language understanding (NLU) engine to perform natural language understanding and processing on the training request input to determine a natural language result output;
• send, to the NLU engine, the training request input and the one or more commands directing the NLU engine to perform natural language understanding and processing on the training request input to determine the natural language result output;
• receive, from the NLU engine, the natural language result output;
• determine one or more third party data sources that correspond to the natural language result output;
• generate one or more commands directing the one or more third party data sources to send source data corresponding to the natural language result output;
• send, to the one or more third party data sources, the one or more commands directing the one or more third party data sources to send source data corresponding to the natural language result output;
• receive, from the one or more third party data sources, the source data corresponding to the natural language result output;
• generate a dynamic training response output based on the natural language result output and the source data;
• generate one or more commands directing the user device to cause display of the dynamic training response output;
• send, to the user device, the dynamic training response output and the one or more commands directing the user device to cause display of the dynamic training response output;
• establish a wireless data connection with a profile correlation computing platform;
• generate one or more commands directing the profile correlation computing platform to update based on the natural language result output;
• send, using the wireless data connection with the profile correlation computing platform, the one or more commands directing the profile correlation computing platform to update based on the natural language result output;
• determine that a final dynamic training response output has been sent;
• determine, after determining that the final dynamic training response output has been sent, that an agent is requested;
• generate one or more commands to identify an agent corresponding to a user of the user device;
• and
• send, to the profile correlation computing platform, the one or more commands to identify the agent corresponding to the user, wherein sending the one or more commands causes the profile correlation computing platform to determine the agent using one or more machine learning algorithms and one or more machine learning datasets.