Oversaw accurate flow of information from the enterprise server side to the client side and vice versa, enabling the client to maintain its health in accordance with the network policies and get regular updates from the server of the various checks or remediations needed to sustain network access.

Involved in ideation of the intermodule communication framework, facilitating parsing of data from the server end and client end.

Designed and developed an architecture for server-driven Custom Notifications System that can appear at the various stages of the remediation cycle.

Designed and developed procedures to implement "Scan-again" feature that enables the client to restart server discovery.

Worked on generating and accessing a Unique Identifier for each client to enable keeping a database for security and other reasons, by levering the power of over 120 million endpoints. This data can benefit the admin in varied different ways primarily in gaining more insight into user and endpoint behavior with full visibility across the extended enterprise.

Worked on implementing a mechanism to show custom notification that are configurable by the admin in case the client doesn't meet certain requirements. A critical aspect of working with clients is managing the various notifications, and a synchronous flow of data from a server to the client. This project involved a major shift from only hard coded notifications to costumer configurable custom notifications.

Developed an internal tool to parse and analyse dumps from DART(AnyConnect Diagnostics and Reporting Tool), using a ML model to process the data and gather more insights about the defect database.

Categorized a wide variety of data taken as an input from a corpus of over 50K entries made on the companies’ defect filing portal.

The data learning model effectively achieved an efficiency of about 89% in identifying the category of a new defect.