Abstract: A network optimization controller (NOC) performs operations including obtaining, from a secure access service edge (SASE) device executing a security service, a first data set defining a security performance metric provided by the security service, and obtaining, from the SASE, a second data set defining a network performance metric associated with a network device. The operations further include defining a policy based at least in part on the first data set and the second data set, determining if the policy has been violated, and changing a first access modality provided for the network device to access an end host to a second access modality based at least in part on the policy being violated. The first access modality and the second access modality define different methods of access to the end host.

Abstract: In one embodiment, a processor receives data indicative of a plurality of conversations involving a primary user. The processor identifies a subset of the plurality of conversations that are regarding a particular topic. The processor adds a conversation to the subset based on a match between one or more keywords in the conversation matching a list of keywords associated with the particular topic. The processor uses a machine learning-based model to identify one or more context characteristics of the conversations in the identified subset. The processor updates the subset of conversations by adding at least one of the conversations to the subset based on the at least one conversation having at least one context characteristic identified by the machine learning-based model. The processor provides data indicative of the updated subset of conversations to a user interface for review by the primary user.

Abstract: In one embodiment, a processor receives data indicative of a plurality of conversations involving a primary user. The processor identifies a subset of the plurality of conversations that are regarding a particular topic. The processor adds a conversation to the subset based on a match between one or more keywords in the conversation matching a list of keywords associated with the particular topic. The processor uses a machine learning-based model to identify one or more context characteristics of the conversations in the identified subset. The processor updates the subset of conversations by adding at least one of the conversations to the subset based on the at least one conversation having at least one context characteristic identified by the machine learning-based model. The processor provides data indicative of the updated subset of conversations to a user interface for review by the primary user.