Computer Systems and Methods for Generating Predictive Change Events

A non-transitory computer-readable medium, wherein the non-transitory computer-readable medium is provisioned with program instructions that, when executed by at least one processor, cause a computing system to:

• store a data representation of a construction project, wherein the data representation comprises data items corresponding to a plurality of categories of data items;
• receive, from a client station via a network interface, data defining a new data item for the construction project corresponding to a particular category of data items;
• based on the new data item for the construction project and the particular category of the new data item:
• (i) automatically predict that a change event for the construction project is needed by inputting the new data item into a first machine learning model trained to predict a need for a change event from data items corresponding to certain categories of data items, including the particular category of the new data item;
• (ii) automatically determine initial recommended data for the predicted change event;
• and
• (iii) automatically determine additional data for the predicted change event corresponding to a particular class of additional data by inputting the initial recommended data for the predicted change event into a second machine learning model trained to predict one or more classes of additional data for a change event, including the particular class of the determined additional data for the predicted change event, from a set of initial data for the change event;
• and
• based at least on the determined additional data for the predicted change event, automatically create a data item representing the predicted change event, wherein the created data item is associated with the data representation of the construction project.

A method carried out by a computing system, the method comprising:

• storing a data representation of a construction project, wherein the data representation comprises data items corresponding to a plurality of categories of data items;
• receiving, from a client station via a network interface, data defining a new data item for the construction project corresponding to a particular category of data items;
• based on the new data item for the construction project and the particular category of the new data item:
• (i) automatically predicting that a change event for the construction project is needed by inputting the new data item into a first machine learning model trained to predict a need for a change event from data items corresponding to certain categories of data items, including the particular category of the new data item;
• (ii) automatically determining initial recommended data for the predicted change event;
• and
• (iii) automatically determining additional data for the predicted change event corresponding to a particular class of additional data by inputting the initial recommended data for the predicted change event into a second machine learning model trained to predict one or more classes of additional data for a change event, including the particular class of the determined additional data for the predicted change event, from a set of initial data for the change event;
• and
• based at least on the determined additional data for the predicted change event, automatically creating a data item representing the predicted change event, wherein the created data item is associated with the data representation of the construction project.