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Hear from our internal security team as they explain how Netskope DLP can be applied for sentiment analysis of user queries in Generative AI web applications. 

 

Learn how to: 

  • Compile positive and negative words into CSV files, creating dictionaries and DLP rules for these words in the Netskope tenant console 

  • Create Realtime policies to perform sentiment analysis on Gen AI categories

  • Identify the intent and thought of users when using Gen AI with policies that check for the overall sentiment of users, whether it is positive or negative

  • Extend this application of DLP profiles to other use cases like detecting social media trolling or abusive messages

For more information, check out our blog post.

 

 

View past events in this series!

 

 

Sentiment analysis is a good idea, but it still relies on customers building their own sentiment keywords.

This is not a developed or prebuilt feature; instead, it requires customer admins to define all the positive and negative keywords.

By contrast, many other DLP vendors can already natively detect sentiment words through their AI models and even perform contextual analysis.

Regarding the question at 18:24, we would also like to know whether Netskope currently supports the latest MIP and Purview. Based on this open feature request, it does not appear to be the case.

 

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