Abstract: Systems and methods include reception of a natural language query of a data source, generation of a first prompt to prompt determination of a plan to respond to the query, receiving the plan from a text generation model in response to the first prompt, generation of a second prompt to prompt determination of an API call and a parsing instruction, the second prompt including the plan, reception of the API call and the parsing instruction from the model in response to the second prompt, reception of a response to the API call from the data source, generation of a third prompt to prompt determination of a parsed response, the third prompt including the response and the parsing instruction, reception of the parsed response from the model in response to the third prompt, and determination of an answer to the query based on the parsed response.

Abstract: Systems and methods include determination of a plurality of instances of a master configuration file, association of each of the plurality of instances with a first respective record of a first database table and with a second respective record of a second database table to determine a plurality of composite data records, determination of correlated features of the master configuration file, the first database table and the second database table based on the plurality of composite data records, and training of a machine learning model based on data of the correlated features of the master configuration file, the first database table and the second database table.