Salesforce Com, Inc.

Salesforce, Inc.

Nikhil Kataria

Kiran Hariharan Nair

Joel Ragnar Palmert

Merwan Hade

Alexander John Trzeciak

Michael Moriarty

Jia Lian Wang

System and methods are described for generating recommendations from dynamically-mapped data. In one implementation, a database system receives a first request to generate a recommendation objection and a second request to retrieve additional data to include in the recommendation object. The database system retrieves the recommendation data from a first database table. The database system identifies the additional data in a second database table that is stored separately from the first database table. The database system generates the recommendation object to include the recommendation data from the first database, and maps the additional data to one or more fields of the recommendation object.

Generation of recommendations from dynamically-mapped data

Containerized workflow engines executing metadata for user-defined applications are described. A system utilizes user selections for configuring a user-defined application to identify application definition metadata. The system stores the application definition metadata for the user-defined application into a persistent storage. A workflow engine executes in a software container in response to receiving user context details and an invocation of the user-defined application. The workflow engine retrieves the application definition metadata from the persistent storage. The workflow engine inputs the user context details and executes the application definition metadata. The workflow engine outputs a result based on executing the application definition metadata.

Containerized workflow engines executing metadata for user-defined applications

Growing community of inventors

Emeryville, CA, United States of America

Nikhil Kataria