ELECTRONIC DOCUMENT OBLIGATION MONITORING
A method, an apparatus, and a computer-readable storage medium for executing obligation management. One or more document portions are extracted from an electronic document using at least one machine learning model selected from a plurality of machine learning models based on at least one parameter associated with the electronic document. One or more entities are identified in one or more document portions of the electronic document. The entities are sent to a generative artificial intelligence (AI) model. The generative AI model is configured to generate one or more rules defining one or more obligations associated with one or more entities. One or more rules are executed to monitor compliance with one or more obligations by one or more entities.
1 . A computer-implemented method, comprising:
extracting, using at least one processor, one or more document portions from an electronic document using at least one machine learning model selected from a plurality of machine learning models based on at least one parameter associated with the electronic document;
identifying, using the at least one processor, one or more entities in the one or more document portions of the electronic document;
sending, using the at least one processor, the one or more entities to a generative artificial intelligence (AI) model, wherein the generative AI model is configured to generate one or more rules defining one or more obligations associated with the one or more entities; and
executing, using the at least one processor, the one or more rules to monitor compliance with the one or more obligations by the one or more entities.
2 . The method of claim 1 , wherein the identifying includes semantically searching, using the at least one machine learning model, the one or more document portions extracted from the electronic document to determine a content of each document portion in the one or more portions, wherein the one or more rules are determined using the determined content.
3 . The method of claim 1 , wherein the executing includes executing the one or more rules in an enterprise resource planning system.
4 . The method of claim 1 , further comprising
receiving an event associated with at least one of: at least one obligation in the one or more obligations, at least one entity in the one or more entities, and any combination thereof;
identifying at least one rule in the one or more rules and determining, based on the event, compliance of the event with the at least one rule; and
generating a graphical user interface representative of the determining of compliance of the event with the at least one rule.
5 . The method of claim 4 , wherein determining compliance of the event with the at least one rule includes comparing at least one rule condition defined in the at least one rule with at least one event condition associated with the event, wherein the event complies with the at least one rule upon the at least one rule condition meeting the at least one event condition.
6 . The method of claim 1 , wherein the one or more rules are generated based on a determination of a risk score associated with at least one of: the one or more obligations, the one or more entities, and any combinations thereof.
7 . The method of claim 6 , further comprising instructing the generative AI model to determine the risk score based on at least one of the following: a plurality of obligations, a plurality of entities, and any combinations thereof, wherein the plurality of obligations includes the one or more obligations, and the plurality of entities includes the one or more entities.
8 . The method of claim 1 , wherein the one or more document portions include at least one of the following: a text, an audio, a video, an image, a table, and any combination thereof.
9 . The method of claim 1 , wherein the plurality of machine learning models includes at least one of the following: a large language model, at least one generative artificial intelligence model, and any combination thereof.
10 . A system, comprising:
at least one processor; and
at least one non-transitory storage media storing instructions, that when executed by the at least one processor, cause the at least one processor to:
identify one or more entities in one or more document portions of an electronic document, wherein the one or more document portions are extracted from the electronic document using at least one machine learning model;
instruct a generative artificial intelligence (AI) model to generate one or more rules defining one or more obligations associated with the one or more entities; and
execute the one or more rules to determine compliance of the one or more entities with the one or more obligations.
11 . The system of claim 10 , wherein identifying of the one or more entities includes semantically searching, using at least one machine learning model, the one or more document portions extracted from the electronic document to determine a content of each document portion in the one or more portions, wherein the one or more rules are generated based on the determined content.
12 . The system of claim 10 , wherein the execution of the one or more rules includes executing the one or more rules in an enterprise resource planning system.
13 . The system of claim 10 , wherein the at least one processor is configured to
receive an event associated with at least one of: at least one obligation in the one or more obligations, at least one entity in the one or more entities, and any combination thereof;
identify at least one rule in the one or more rules and determine, based on the event, compliance of the event with the at least one rule; and
generate a graphical user interface representative of determining of compliance of the event with the at least one rule.
14 . The system of claim 13 , wherein determining compliance of the event with the at least one rule includes comparing at least one rule condition defined in the at least one rule with at least one event condition associated with the event, wherein the event complies with the at least one rule upon the at least one rule condition meeting the at least one event condition.
15 . The system of claim 10 , wherein the one or more rules are generated based on a determination of a risk score associated with at least one of: the one or more obligations, the one or more entities, and any combinations thereof.
16 . The system of claim 15 , wherein the at least one processor is configured to instruct the generative AI model to determine the risk score based on at least one of the following: a plurality of obligations, a plurality of entities, and any combinations thereof, wherein the plurality of obligations includes the one or more obligations, and the plurality of entities includes the one or more entities.
17 . The system of claim 10 , wherein the one or more document portions include at least one of the following: a text, an audio, a video, an image, a table, and any combination thereof.
18 . A non-transitory computer-readable storage medium, the computer-readable storage medium including instructions that when executed by at least one processor, cause the at least one processor to:
identify one or more entities in one or more document portions of an electronic document, wherein the one or more document portions are extracted from the electronic document using at least one machine learning model;
instruct a generative artificial intelligence (AI) model to generate one or more rules defining one or more obligations associated with the one or more entities, wherein the generative AI model is instructed to determine a risk score based on at least one of the following: a plurality of obligations, a plurality of entities, and any combinations thereof, wherein the plurality of obligations includes the one or more obligations, and the plurality of entities includes the one or more entities;
receive an event associated with at least one of: at least one obligation in the one or more obligations, at least one entity in the one or more entities, and any combination thereof;
identify at least one rule in the one or more rules and determine, based on the event and the risk score, compliance of the event with the at least one rule; and
generate a graphical user interface representative of determining of compliance of the event with the at least one rule.
19 . The non-transitory computer-readable storage medium of claim 18 , wherein identification of the one or more entities includes semantically searching, using the at least one machine learning model, the one or more document portions extracted from the electronic document to determine a content of each document portion in the one or more portions, wherein the one or more rules are determined using the determined content.
20 . The non-transitory computer-readable storage medium of claim 18 , wherein the at least one processor is configured to execute the one or more rules in an enterprise resource planning system.