Prediction and notification of agreement document expirations
A document management system can include an artificial intelligence-based document manager that can perform one or more predictive operations based on characteristics of a user, a document, a user account, or historical document activity. For instance, the document management system can apply a machine-learning model to determine how long an expiring agreement document is likely to take to renegotiate and can prompt a user to begin the renegotiation process in advance. The document management system can detect a change to language in a particular clause type and can prompt a user to update other documents that include the clause type to include the change. The document management system can determine a type of a document being worked on and can identify one or more actions that a corresponding user may want to take using a machine-learning model trained on similar documents and similar users.
1. A computer-implemented method, comprising:
identifying, using at least one processor, an expiration date associated with an agreement documents, the expiration date is identified, using one or more machine learning models, based on one or more interactions with a content of the agreement document via a notification interface;
applying, using the at least one processor, the one or more machine-learning models to the agreement document, the one or more machine-learning models are trained on historical agreement documents associated with the same document type as the type of the agreement document, and generating, using the one or more machine learning models, a predicted time of negotiation for the agreement document based on the type of the agreement document and an analysis of the content of the agreement document;
at a time more than the predicted time of negotiation for the agreement document before the expiration date associated with the first agreement document, modifying, using the at least one processor, the notification interface with a reminder notification identifying the expiration date of the agreement document and the predicted time of negotiation for the agreement document; and
generating, using the at least one processor, an updated agreement document, wherein the updated agreement document includes at least one update generated based on one or more actions suggested by the one or more machine learning models using the one or more interactions.
2. The method of claim 1 , wherein the expiration date associated with the agreement document comprises a date after which terms of the agreement document are no longer valid.
3. The method of claim 1 , wherein the agreement document comprises one or more of: a contract, an employment agreement, a purchase agreement, a services agreement, or a financial agreement.
4. The method of claim 1 , wherein training of the one or more machine-learning models comprises
accessing the historical agreement documents,
determining how long each historical agreement document took to negotiate, and
training the one or more machine-learning models to correlate a length of negotiation for each historical agreement document with a type of each historical agreement document.
5. The method of claim 1 , wherein the historical agreement documents comprise documents associated with a user, associated with an entity or other user associated with the user, or associated with users with one or more characteristics in common with the user.
6. The method of claim 1 , wherein the notification interface includes an interface element that, when selected, generates the updated first agreement document and modifies one or more of accounts of a user and a counterparty associated with negotiating of the agreement document to enable access to the updated first agreement document.
7. The method of claim 6 , wherein the counterparty comprises a party to the agreement document.
8. A non-transitory computer-readable storage medium storing executable instructions that, when executed by at least one hardware processor, cause the at least one hardware processor to perform:
identify an expiration date associated with an agreement documents, the expiration date is identified, using one or more machine learning models, based on one or more interactions with a content of the agreement document via a notification interface;
apply the one or more machine-learning models to the agreement document, the one or more machine-learning models are trained on historical agreement documents associated with the same document type as the type of the agreement document, and generate, using the one or more machine learning models, a predicted time of negotiation for the agreement document based on the type of the agreement document and an analysis of the content of the agreement document;
at a time more than the predicted time of negotiation for the agreement document before the expiration date associated with the first agreement document, modify, using the at least one processor, the notification interface with a reminder notification identifying the expiration date of the agreement document and the predicted time of negotiation for the agreement document; and
generate an updated agreement document, wherein the updated agreement document includes at least one update generated based on one or more actions suggested by the one or more machine learning models using the one or more interactions.
9. The non-transitory computer-readable storage medium of claim 8 , wherein the expiration date associated with the agreement document comprises a date after which terms of the agreement document are no longer valid.
10. The non-transitory computer-readable storage medium of claim 8 , wherein the agreement document comprises one or more of: a contract, an employment agreement, a purchase agreement, a services agreement, or a financial agreement.
11. The non-transitory computer-readable storage medium of claim 8 , wherein training of the one or more machine-learning models comprises
accessing the historical agreement documents,
determining how long each historical agreement document took to negotiate, and
training the one or more machine-learning models to correlate a length of negotiation for each historical agreement document with a type of each historical agreement document.
12. The non-transitory computer-readable storage medium of claim 8 , wherein the historical agreement documents comprise documents associated with a user, associated with an entity or other user associated with the user, or associated with users with one or more characteristics in common with the user.
13. The non-transitory computer-readable storage medium of claim 8 , wherein the notification interface includes an interface element that, when selected, generates the updated agreement document and modifies one or more of accounts of a user and a counterparty associated with negotiating of the agreement document to enable access to the updated agreement document.
14. The non-transitory computer-readable storage medium of claim 13 , wherein the counterparty comprises a party to the agreement document.
15. A document management system, comprising:
at least one hardware processor; and
a non-transitory computer-readable storage medium storing executable instructions that, when executed, cause the at least one hardware processor to perform:
identify an expiration date associated with an agreement documents, the expiration date is identified, using one or more machine learning models, based on one or more interactions with a content of the agreement document via a notification interface;
apply the one or more machine-learning models to the agreement document, the one or more machine-learning models are trained on historical agreement documents associated with the same document type as the type of the agreement document, and generate, using the one or more machine learning models, a predicted time of negotiation for the agreement document based on the type of the agreement document and an analysis of the content of the agreement document;
at a time more than the predicted time of negotiation for the agreement document before the expiration date associated with the agreement document, modify, using the at least one processor, the notification interface with a reminder notification identifying the expiration date of the agreement document and the predicted time of negotiation for the first agreement document; and
generate an updated agreement document, wherein the updated agreement document includes at least one update generated based on one or more actions suggested by the one or more machine learning models using the one or more interactions.
16. The document management system of claim 15 , wherein the expiration date associated with the agreement document comprises a date after which terms of the agreement document are no longer valid.
17. The document management system of claim 15 , wherein the agreement document comprises one or more of: a contract, an employment agreement, a purchase agreement, a services agreement, or a financial agreement.
18. The document management system of claim 15 , wherein training of the one or more machine-learning models comprises
accessing the historical agreement documents,
determining how long each historical agreement document took to negotiate, and
training the one or more machine-learning models to correlate a length of negotiation for each historical agreement document with a type of each historical agreement document.
19. The document management system of claim 15 , wherein the historical agreement documents comprise documents associated with a user, associated with an entity or other user associated with the user, or associated with users with one or more characteristics in common with the user.
20. The document management system of claim 15 , wherein the notification interface includes an interface element that, when selected, generates the updated agreement document and modifies one or more of accounts of a user and a counterparty associated with negotiating of the agreement document to enable access to the updated agreement document.