Abstract: Various embodiments of systems and methods for trust circle through machine learning are described herein. The method includes identifying a website subscribed with the trust circle for aggregating data based upon a query. The query is received from a user of one or more registered users of the subscribed website. The one or more users' information and their respective authentication token is retrieved from the subscribed website. Based upon the authentication token of the respective user, information of the respective user is retrieved from one or more social media websites. The retrieved one or more users information and their retrieved one or more social media websites information is correlated to generate an output based upon the query. The output comprises reviews by the one or more users as reviewers, relationship of the reviewers with the user raised the query, and ratings clustered based upon various parameters.

Abstract: A request with data is received at an execution environment of an application. In response to the request, a first network packet is automatically created. The first network packet includes the data, orchestration code and application code of the application. The first network packet is sent to a first network node. The first network node executes a first section of the application code in a node execution environment. The section to be executed is determined based on the orchestration code. In response to the execution, a microservice associated with the application is invoked. Upon receiving a response from the microservice, a second network packet is dynamically generated. The second network packet includes the received response, the orchestration code, and one or more sections of the application code. The second network packet is sent to a second network node.

Abstract: A request with data is received at an execution environment of an application. In response to the request, a first network packet is automatically created. The first network packet includes the data, orchestration code and application code of the application. The first network packet is sent to a first network node. The first network node executes a first section of the application code in a node execution environment. The section to be executed is determined based on the orchestration code. In response to the execution, a microservice associated with the application is invoked. Upon receiving a response from the microservice, a second network packet is dynamically generated. The second network packet includes the received response, the orchestration code, and one or more sections of the application code. The second network packet is sent to a second network node.

Abstract: Various embodiments of systems and methods for trust circle through machine learning are described herein. The method includes identifying a website subscribed with the trust circle for aggregating data based upon a query. The query is received from a user of one or more registered users of the subscribed website. The one or more users' information and their respective authentication token is retrieved from the subscribed website. Based upon the authentication token of the respective user, information of the respective user is retrieved from one or more social media websites. The retrieved one or more users information and their retrieved one or more social media websites information is correlated to generate an output based upon the query. The output comprises reviews by the one or more users as reviewers, relationship of the reviewers with the user raised the query, and ratings clustered based upon various parameters.