Abstract: In one embodiment, a method includes identifying datasets associated with a party and identifying one or more decentralized identifiers (DIDs) associated with the datasets. The method also includes generating an aggregated dataset associated with the DIDs and generating a training dataset associated with the aggregated dataset. The method further includes using one or more machine learning algorithms to recognize patterns within the training dataset.

Abstract: In one embodiment, a method includes receiving a legal document associated with a party and classifying the legal document into one or more classifications. The method also includes obtaining a party decentralized identifier (DID) associated with the party. The method also includes generating a data model using the party DID and the one or more classifications. The method further includes generating a hybrid legal document using the data model.

Abstract: In one embodiment, a method includes receiving a request for a transaction from a first party and identifying a second party for the transaction. The first party is associated with a first party decentralized identifier (DID), and the second party is associated with a second party DID. The method also includes receiving negotiation data from the first party and the second party and generating a data model using the first party DID, the second party DID, and the negotiation data. The method further includes generating a hybrid legal document using the data model and a legal prose document.