Granted Patent B2

US 12,353,522 · App. 17/943,267 · Granted Jul 8, 2025

Inventor: Martijn Van der Schaaf (Zuidland, NL)

Assignee: Acronis International GmbH

G06F21/105G06Q30/018G06F21/1073

Abstract

Claims (65)

1. A method for monitoring software items using a generated contract, the method comprising:

transmitting a quote for viewing on a computing device associated with a first person, wherein the quote comprises a list of software items included in a transaction;

in response to receiving an approval of the quote by the first person, generating a contract governing the transaction by:

extracting the list of software items from the quote;

retrieving software item information for each of the list of software items;

executing a first machine learning model trained to classify each of a plurality of historical contracts into various software item types, wherein executing comprises: classifying, using the first machine learning model trained on the plurality of historical contracts to distinguish between subscription-based and non-subscription-based items, each respective software item of the list of software items into a subscription-based software item and a non-subscription-based software item based on the software item information; and

executing a second machine learning model trained to identify, in the plurality of historical contracts, reoccurring usage conditions associated with a particular software item type, and generate at least one template for the reoccurring usage conditions, wherein the particular software item type is a subscription-based software item;

executing a third machine learning model trained to populate the at least one template with information in the quote, wherein training the third machine learning model comprises:

identifying training usage condition templates from training contracts and associated quotes;

determining numbers and terms taken from the associated quotes and entered into the training usage condition templates; and

identifying information in an arbitrary quote that should be entered into a given contract based on the determined numbers and terms;

determining, based on the software item information and for inclusion in the contract, usage conditions that the first person has to comply with to access software items in the list of software items, wherein the usage conditions comprise the at least one template populated with the information in the quote, wherein determining the usage conditions comprises:

for each respective subscription-based software item, determining a usage term period after which the subscription-based software item is no longer accessible to the first person, in accordance with a first usage condition of the usage conditions; and

monitoring compliance with the usage conditions using the contract; and

in response to detecting non-compliance with at least one of the usage conditions, blocking access to a corresponding software item in the list of software items, wherein detecting the non-compliance comprises in response to detecting that the usage term period for the respective subscription-based software item has elapsed, blocking access to the respective subscription-based software item for the first person.

2. The method of claim 1 , wherein the list of software items includes one or more of: a software application, a hardware device, a software-as-a-service, a platform-as-a-service, an infrastructure-as-a-service, and a container-as-a-service.

3. The method of claim 1 , further comprising:

in response to receiving the approval, retrieving at least one pre-existing contract associated with the first person by looking up an identifier of the first person or a vendor providing the list of software items in a contracts database.

4. The method of claim 3 , further comprising:

determining whether to include the transaction in the at least one pre-existing contract, wherein generating the contract is further in response to determining not to include the transaction in the at least one pre-existing contract.

5. The method of claim 4 , further comprising:

in response to determining to include the transaction in the at least one pre-existing contract, including the usage conditions and the list of software items in the at least one pre-existing contract.

6. The method of claim 1 , wherein the contract is a smart contract for a blockchain.

7. The method of claim 1 , wherein the software item information comprises for each respective software item one or more of: a unique identifier, an software item type, a fee, a usage description, and a developer description.

8. A system for monitoring software items using a generated contract, comprising:

a memory; and

a hardware processor communicatively coupled with the memory and configured to:

transmit a quote for viewing on a computing device associated with a first person, wherein the quote comprises a list of software items included in a transaction;

in response to receiving an approval of the quote by the first person, generate a contract governing the transaction by:

extracting the list of software items from the quote;

retrieving software item information for each of the list of software items;

executing a first machine learning model trained to classify each of a plurality of historical contracts into various software item types, wherein executing comprises: classifying, using the first machine learning model trained on the plurality of historical contracts to distinguish between subscription-based and non-subscription-based items, each respective software item of the list of software items into a subscription-based software item and a non-subscription-based software item based on the software item information; and

executing a second machine learning model trained to identify, in the plurality of historical contracts, reoccurring usage conditions associated with a particular software item type, and generate at least one template for the reoccurring usage conditions, wherein the particular software item type is a subscription-based software item;

executing a third machine learning model trained to populate the at least one template with information in the quote, wherein training the third machine learning model comprises:

identifying training usage condition templates from training contracts and associated quotes;

determining numbers and terms taken from the associated quotes and entered into the training usage condition templates; and

identifying information in an arbitrary quote that should be entered into a given contract based on the determined numbers and terms;

determining, based on the software item information and for inclusion in the contract, usage conditions that the first person has to comply with to access software items in the list of software items, wherein the usage conditions comprise the at least one template populated with the information in the quote, wherein determining the usage conditions comprises:

for each respective subscription-based software item, determining a usage term period after which the subscription-based software item is no longer accessible to the first person, in accordance with a first usage condition of the usage conditions; and

monitoring compliance with the usage conditions using the contract; and

in response to detecting non-compliance with at least one of the usage conditions, blocking access to a corresponding software item in the list of software items, wherein detecting the non-compliance comprises in response to detecting that the usage term period for the respective subscription-based software item has elapsed, blocking access to the respective subscription-based software item for the first person.

9. The system of claim 8 , wherein the list of software items includes one or more of: a software application, a hardware device, a software-as-a-service, a platform-as-a-service, an infrastructure-as-a-service, and a container-as-a-service.

10. The system of claim 8 , wherein the hardware processor is further configured to:

in response to receiving the approval, retrieve at least one pre-existing contract associated with the first person by looking up an identifier of the first person or a vendor providing the list of software items in a contracts database.

11. The system of claim 10 , wherein the hardware processor is further configured to:

determine whether to include the transaction in the at least one pre-existing contract, wherein generating the contract is further in response to determining not to include the transaction in the at least one pre-existing contract.

12. The system of claim 11 , wherein the hardware processor is further configured to:

in response to determining to include the transaction in the at least one pre-existing contract, include the usage conditions and the list of software items in the at least one pre-existing contract.

13. The system of claim 8 , wherein the contract is a smart contract for a blockchain.

14. The system of claim 8 , wherein the software item information comprises for each respective software item one or more of: a unique identifier, an software item type, a fee, a usage description, and a developer description.

15. A non-transitory computer readable medium storing thereon computer executable instructions for monitoring software items using a generated contract, including instructions for:

transmitting a quote for viewing on a computing device associated with a first person, wherein the quote comprises a list of software items included in a transaction;

in response to receiving an approval of the quote by the first person, generating a contract governing the transaction by:

extracting the list of software items from the quote;

retrieving software item information for each of the list of software items;

executing a first machine learning model trained to classify each of a plurality of historical contracts into various software item types, wherein executing comprises: classifying, using the first machine learning model trained on the plurality of historical contracts to distinguish between subscription-based and non-subscription-based items, each respective software item of the list of software items into a subscription-based software item and a non-subscription-based software item based on the software item information; and

executing a second machine learning model trained to identify, in the plurality of historical contracts, reoccurring usage conditions associated with a particular software item type, and generate at least one template for the reoccurring usage conditions, wherein the particular software item type is a subscription-based software item;

executing a third machine learning model trained to populate the at least one template with information in the quote, wherein training the third machine learning model comprises:

identifying training usage condition templates from training contracts and associated quotes;

determining numbers and terms taken from the associated quotes and entered into the training usage condition templates; and

identifying information in an arbitrary quote that should be entered into a given contract based on the determined numbers and terms;

determining, based on the software item information and for inclusion in the contract, usage conditions that the first person has to comply with to access software items in the list of software items, wherein the usage conditions comprise the at least one template populated with the information in the quote, wherein determining the usage conditions comprises:

for each respective subscription-based software item, determining a usage term period after which the subscription-based software item is no longer accessible to the first person, in accordance with a first usage condition of the usage conditions; and

monitoring compliance with the usage conditions using the contract; and

in response to detecting non-compliance with at least one of the usage conditions, blocking access to a corresponding software item in the list of software items, wherein detecting the non-compliance comprises in response to detecting that the usage term period for the respective subscription-based software item has elapsed, blocking access to the respective subscription-based software item for the first person.

Assignments (3)

Continuity (1)

References Cited (18)