Secure and confidential collaboration architecture

A collaboration architecture for federated collaboration, the collaboration architecture including:

• an enrollment service module configured to:
• receive, from a first collaborator, a first enrollment request;
• receive, from a second collaborator, a second enrollment request;
• issue respective acceptances of the first and second enrollment requests;
• a service distributor configured to:
• responsive to issuing the acceptance of the first enrollment request, provide software programs including first and second machine learning (ML) models and collaboration services to the first collaborator, the first ML model trained to monitor an intellectual property (IP) repository of the first collaborator for changes to data stored thereon, the second ML model trained based on IP goals of the second collaborator;
• an entity interface configured to:
• receive, from the second collaborator, a communication indicating interest in the IP associated with IP data of the first collaborator;
• and
• a large language model (LLM) interface configured to:
• responsive to receiving the communication indicating interest, prompt a large language model (LLM), to generate a collaboration agreement regarding the IP data that changed;
• and
• receive an executed collaboration agreement at the collaboration architecture.

A non-transitory machine-readable medium including instructions that, when executed by a machine, cause the machine to perform operations for secure, federated collaboration, the operations comprising:

• receiving, from a first collaborator and at a collaboration architecture, a first enrollment request;
• receiving, from a second collaborator and at a collaboration architecture, a second enrollment request;
• issuing, by the collaboration architecture, respective acceptances of the first and second enrollment requests;
• responsive to issuing the acceptance of the first enrollment request, providing, by the collaboration architecture, software programs including first and second machine learning (ML) models and collaboration services to the first collaborator;
• the first ML model trained to monitor an intellectual property (IP) repository of the first collaborator for changes to data stored thereon;
• the second ML model trained based on IP goals of the second collaborator;
• receiving, from the second collaborator, a communication indicating interest in the IP associated with IP data of the first collaborator;
• responsive to receiving the communication indicating interest, prompting a large language model (LLM), to generate a collaboration agreement regarding the IP data that changed;
• and
• receiving an executed collaboration agreement at the collaboration architecture.