Abstract: A method is provided. The method may include, in response to electronically receiving a document, automatically classifying the document and different parts of the document, by electronically identifying a document type associated with the document and electronically tagging data associated with the different parts of the document based on classification rules. The method may further include automatically extracting the tagged data associated with the automatically classified document based on data extraction rules. The method may further include detecting first feedback associated with the classification rules and second feedback associated with the data extraction rules. The method may further include automatically generating and updating validation rules based on the identified document type, the detected first feedback, and the detected second feedback to validate the automatically classified document and the automatically tagged and extracted data.

Abstract: A method is provided. The method may include, in response to electronically receiving a document, automatically classifying the document and different parts of the document, by electronically identifying a document type associated with the document and electronically tagging data associated with the different parts of the document based on classification rules. The method may further include automatically extracting the tagged data associated with the automatically classified document based on data extraction rules. The method may further include detecting first feedback associated with the classification rules and second feedback associated with the data extraction rules. The method may further include automatically generating and updating validation rules based on the identified document type, the detected first feedback, and the detected second feedback to validate the automatically classified document and the automatically tagged and extracted data.

Abstract: Techniques are described relating to automated deployment of an application in a managed services domain of a cloud computing environment. One or more of such techniques may minimize human interaction or intervention during deployment of the application. An associated method includes receiving from a client system a request to deploy the application in a target environment and analyzing the request via a machine learning knowledge model. Additionally, the method includes requesting from the client system access to the target environment and, upon receiving access to the target environment, validating the target environment through inspection. Upon validating the target environment, the method further includes facilitating presentation of an application deployment plan through an interface of the client system.

Abstract: Systems, methods, and computer program products leverage artificial intelligence, and machine learning to process image enhancements using image enhancement techniques and algorithms. Image enhancements are determined to be best suited for enhancing each image as a function of each images' calculated validation parameters by an analytics engine. The images are each categorized by the image quality as a function of the validation parameters. Images identified as having an improvement space are further processed by querying the images' validation parameters using a knowledge base comprising historical data describing past image enhancements and historical validation parameters to the current image. A matrix of recommended enhancements, along with a predicted success rate for improving the image quality is provided to a user interface.

Abstract: Systems, methods, and computer program products leverage artificial intelligence, and machine learning to process image enhancements using image enhancement techniques and algorithms. Image enhancements are determined to be best suited for enhancing each image as a function of each images' calculated validation parameters by an analytics engine. The images are each categorized by the image quality as a function of the validation parameters. Images identified as having an improvement space are further processed by querying the images' validation parameters using a knowledge base comprising historical data describing past image enhancements and historical validation parameters to the current image. A matrix of recommended enhancements, along with a predicted success rate for improving the image quality is provided to a user interface.

Abstract: Techniques are described relating to automated deployment of an application in a managed services domain of a cloud computing environment. One or more of such techniques may minimize human interaction or intervention during deployment of the application. An associated method includes receiving from a client system a request to deploy the application in a target environment and analyzing the request via a machine learning knowledge model. Additionally, the method includes requesting from the client system access to the target environment and, upon receiving access to the target environment, validating the target environment through inspection. Upon validating the target environment, the method further includes facilitating presentation of an application deployment plan through an interface of the client system.