US 2026/0099549 A1 · GENERATIVE MODEL-BASED AUTOMATIC REPORT GENERATION AND UPDATING

Abstract

Systems and methods are disclosed herein for generative model-based automatic report generation and updating. A report generation system uses RAG search techniques and machine-learned models to generate reports responsive to user-specified prompts using data sets retrieved from third-party data sources. The system continually monitors the third-party data sources to identify changes to the underlying data sets by sending, to each data source, a first database query specifying an historical time period and a second database query specifying a recent time period. The system compares the responsive data sets, and if the system determines that an update condition has occurred, the system automatically generates and transmits to the user an updated report notifying the user of the change or development relevant to the underlying query.

Claims20

Dependent claims

A method comprising:

sending, by a report generation system, a first database query to a corpus of third-party data sources that provided data used to generate a report responsive to a user-defined prompt, the first database query requesting data covering a historical time period;
sending, by the report generation system, a second database query to the corpus of third-party data sources, the second database query requesting data covering a recent time period;
calculating, using a trained machine-learned model, a similarity metric between a first data set received responsive to the first database query and a second data set received responsive to the second database query, the model configured to automatically generate numerical similarity scores responsive to differences between processed features of the data sets;
responsive to the similarity metric exceeding a threshold value, automatically generating an updated report responsive to the user-defined prompt;
and
sending the updated report to the user.

3 more elements

A non-transitory computer readable storage medium comprising computer executable instructions that when executed by one or more processors causes the one or more processors to perform operations comprising:

sending, by a report generation system, a first database query to a corpus of third-party data sources that provided data used to generate a report responsive to a user-defined prompt, the first database query requesting data covering a historical time period;
sending, by the report generation system, a second database query to the corpus of third-party data sources, the second database query requesting data covering a recent time period;
calculating, using a trained machine-learned model, a similarity metric between a first data set received responsive to the first database query and a second data set received responsive to the second database query, the model configured to automatically generate numerical similarity scores responsive to differences between processed features of the data sets;
responsive to the similarity metric exceeding a threshold value, automatically generating an updated report responsive to the user-defined prompt;
and
sending the updated report to the user.

3 more elements

A computer system comprising:

one or more processors;
and
a non-transitory computer readable storage medium comprising computer executable instructions that when executed by one or more processors causes the one or more processors to perform operations comprising:
sending, by a report generation system, a first database query to a corpus of third-party data sources that provided data used to generate a report responsive to a user-defined prompt, the first database query requesting data covering a historical time period;
sending, by the report generation system, a second database query to the corpus of third-party data sources, the second database query requesting data covering a recent time period;
calculating, using a trained machine-learned model, a similarity metric between a first data set received responsive to the first database query and a second data set received responsive to the second database query, the model configured to automatically generate numerical similarity scores responsive to differences between processed features of the data sets;
responsive to the similarity metric exceed exceeding a threshold value, automatically generating an updated report responsive to the user-defined prompt;
and
sending the updated report to the user.

6 more elements

Dependencies are inferred from the claim text.

Generative model-based automatic report generation and updating

Life of this patent

Generative model-based automatic report generation and updating

Life of this patent

Abstract

Claims20