Utilizing machine learning to prevent intellectual property issues for content during different stages of a project lifecycle

A device, comprising:

• one or more memories;
• and
• one or more processors, communicatively coupled to the one or more memories, configured to:
• receive content data identifying content created by users and metadata associated with the content;
• receive rules data identifying rules associated with utilization of the content;
• utilize the metadata to generate digital DNA signatures for the content in near-real time;
• utilize the metadata and the content data to generate digital identifiers for the content;
• associating the digital identifiers with corresponding digital DNA signatures;
• store, in a repository, the rules data, all of the content of the content data, the digital DNA signatures, and the digital identifiers;
• receive, from a client device, new content that is generated based on particular content of the content data and new metadata associated with the new content;
• utilize the new metadata to generate a new digital DNA signature for the new content;
• process the new digital DNA signature, the rules data, the digital DNA signatures, and the digital identifiers, with a machine learning model, to determine whether the new content violates one or more rules of the rules data;
• and
• perform one or more actions based on whether the new content violates the one or more rules of the rules data.

A non-transitory computer-readable medium storing instructions, the instructions comprising:

• one or more instructions that, when executed by one or more processors, cause the one or more processors to:
• store, in a repository:
• content data identifying content and metadata associated with the content,
• rules data identifying rules associated with utilization of the content, and
• digital DNA signatures, for the content, that are generated in near-real time based on the metadata;
• receive, from a client device, new content that is generated based on particular content of the content data and new metadata associated with the new content;
• utilize the new metadata to generate a new digital DNA signature for the new content;
• process the new digital DNA signature, the rules data, and the digital DNA signatures, with a machine learning model, to determine whether the new content violates one or more rules of the rules data;
• and
• perform one or more actions based on whether the new content violates the one or more rules of the rules data.