Automated no-code coding of app-software using a conversational interface and natural language processing
The present disclosure relates to a new and useful platform and system for the automated no-code coding of software Apps and other software using conversational interface based on Natural Language Understanding (NLU) or the associated National Language Processing (NLP) and method of operation and use thereof, more specifically a new platform and system either as a website or even as a stand-alone App-based software with a Natural Language Engine (NLE) for user entry to further power portions or the entire editing of no-code Apps using NLU/NLP and method of use thereof.
1 . A method for generating an app software product through a conversational interface, the method comprising:
receiving, via the conversational interface, a user request to create the app software product during a conversational session;
parsing the user request using a natural language processing (NLP) engine to identify intent and entities;
generating an app software product based on the identified intent and entities, wherein the generation is performed by a no-code generation module executing on a computing system;
deploying the app software product to a live environment upon receiving user confirmation; and
continuously updating the NLP model during the conversational session based on user corrections or confirmations, thereby dynamically improving subsequent intent recognition accuracy.
2 . The method of claim 1 , further comprising refining NLP model weights or keyword mapping in real time based on user feedback or clarification prompts during the conversational session.
3 . The method of claim 1 , wherein the conversational interface is configured to operate in a blind mode, a voice-enabled mode, and a friend mode wherein: the blind mode is configured to generate the app software product in response to solely aural data, the voice-enabled mode is configured to generate the app software product in response to text data and aural data, and the friend mode is configured to generate the app software product in response to the user's interactions with automated prompted communications.
4 . The method of claim 1 , wherein the step of deploying the app software product to a live environment is performed upon receiving the user confirmation via the conversational interface used to create the app software product.
5 . The method of claim 1 , further comprising confirming features of the app software product with the user via the conversational interface during the conversation session before generating the app software product.
6 . A system for generating an app software product through a conversational interface, the system comprising at least one computing device comprising a processor and memory, the system configured to:
receive, via the conversational interface, a user request to create an application during a conversational session;
parse the user request using a natural language processing (NLP) engine to identify intent and entities;
generate an app software product based on the identified intent and entities, wherein the generation is performed by a no-code generation module executing on the at least one computing device;
deploy the app software product to a live environment upon receiving user confirmation; and
continuously update the NLP model during the conversational session based on user corrections or confirmations, thereby dynamically improving subsequent intent recognition accuracy.
7 . The system of claim 1 , wherein the system is further configured to refine NLP model weights or keyword mapping in real time based on user feedback or clarification prompts during the conversational session.
8 . The system of claim 6 , wherein the conversational interface is configured to operate in a blind mode, a voice-enabled mode, and a friend mode wherein:
the blind mode is configured to generate the app software product in response to solely aural data, the voice-enabled mode is configured to generate the app software product in response to text data and aural data, and the friend mode is configured to generate the app software product in response to the user's interactions with automated prompted communications.
9 . The system of claim 6 , wherein the app software product is deployed to a live environment upon receiving the user confirmation via the conversational interface used to create the app software product.
10 . The system of claim 6 , wherein the system is further configured to confirm features of the app software product with the user via the conversational interface during the conversation session before generating the app software product.