Salesforce Com, Inc.

Intuit, Inc.

Jigna Bhatt

Thomas Nicholas Valine

Colbert Guan

Sampath Tulava

Ruofan Zhang

Lucinda Foss

Lesley Kim Grossblatt

Charles Shieh

Systems, methods, and computer-readable media for providing a Policy Enforcement as a Service (PEaaS) are described. A processor may, in response to identification of a suspension of user(s) for one of one or more services, generate a suspension value indicative of the suspension and transmit the suspension value to a corresponding one of third party platforms of the service(s), respectively. The suspension value usable by the corresponding third party platform to determine whether to deny request(s) from the user for the distributed service, or not. A service of the service(s) comprises a distributed service provided by a plurality of hosts. In response to the service corresponding to the suspension including the distributed service, the suspension value may be transmitted to the first host, and the suspension value may be propagated to the one or more second hosts, respectively. Other embodiments may be described and/or claimed.

Data consistency of policy enforcement for distributed applications

Systems, methods, and computer-readable media for providing a Policy Enforcement as a Service (PEaaS) are described. A processing device may collect set(s) of policy parameter values from one or more third party platforms, respectively, by communication with remote interface(s) employed on the one or more third party platforms, respectively; each set of policy parameter values defines a threshold for issuing a user suspension for a service provided by a respective one of the third party platforms; collect one or more sets of usage metrics for the one or more services from the one or more third party platforms, respectively, by communication with the remote interface(s); the communication with the remote interface(s) to collect the sets of usage metric(s) is asynchronous with communications by which the remote interface(s) received the usage metrics. Other embodiments may be described and/or claimed.

Opaque interface for enclosed/wrapped asynchronous pushing and/or pulling data between policy enforcement as a service (PEaaS) components

Systems, methods, and computer-readable media for providing a Policy Enforcement as a Service (PEaaS) are described. The PEaaS may allow customer service providers to define policies for usage restrictions to be implemented across their distributed systems/platforms. The policy enforcement mechanisms of the PEaaS may prevent users from overloading the systems/platforms of the customer service providers. The PEaaS may also include mechanisms for asynchronously (or 'lazy') tracking user infractions or suspensions. The lazy tracking mechanism may track and perform asynchronous (async) computation of infraction records and suspension sets/lists. Other embodiments may be described and/or claimed.

Policy enforcement as a service for third party platforms with asynchronous user tracking mechanisms

Systems, methods, and computer-readable media for providing a Policy Enforcement as a Service (PEaaS) are described. The PEaaS may allow customer service providers to define policies for usage restrictions to be implemented across their distributed systems/platforms. The policy enforcement mechanisms of the PEaaS may prevent users from overloading the systems/platforms of the customer service providers. Other embodiments may be described and/or claimed.

Policy enforcement as a service for third party platforms

The invention relates to a method to interview a candidate. The method steps include providing a virtual interview assistant comprising an interview plan, a recording module, an analysis module, and a candidate screening criteria, wherein the recording module is configured to record at least one recording selected from a group consisting of video recording, audio recording, and physiological parameter recording, and wherein the analysis module configured for analyzing the at least one recording, collecting a candidate interview response by interviewing the candidate using the virtual interview assistant based on the interview plan, wherein at least a portion of the candidate interview response is collected using the recording module, analyzing the candidate interview response using the analysis module to generate a candidate profile, and presenting the candidate profile to a recruiter based on the candidate screening criteria, wherein the recruiter makes a recruiting decision regarding the candidate based on the candidate profile.

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San Francisco, CA, United States of America

Jigna Bhatt