Salesforce is helping their top customers go all-in on AI. Salesforce Data Cloud and Einstein AI in particular are helping companies leverage this massive opportunity for scaling up business intelligence.

But running AI models on data can introduce risks, and much more so when sensitive or ultra-sensitive data is involved. This is true for any AI model using data from any system, because sending data to an AI model does not guarantee output and can lead to sensitive data erroneously being exposed to third-parties. 

So how can enterprises ensure this data is protected against accidental exposure? That’s where Odaseva comes in.

Protecting and securing Salesforce data used in AI models doesn’t have to hinder innovation

Typically, the more measures an organization takes to protect and secure data, the more access to this data is restricted and therefore lessens its ability to be used for business insights. 

But that doesn’t have to be the case. With Odaseva, protecting and securing data used in AI models doesn’t have to hinder innovation. Enterprises don’t have to sacrifice business intelligence for data security thanks to Odaseva’s best-in-class data security technology that enables organizations to run AI models on Salesforce data without risking exposure to third parties.

So just how does this work? Our new eBook, “Securing Data in AI Models: Mitigate Risk with Odaseva, Salesforce Data Cloud & Einstein AI” details:

1. Three risks when running AI models on sensitive data
2. How Salesforce mitigates AI data security risks with Einstein GPT Trust Layer
3. How Odaseva expands on Salesforce’s protection with end-to-end encryption, tokenization, and data masking
4. The difference between tokenization, masking, and pseudonymization and how each method differs in pre-processing and post-processing

Get the eBook now to learn how securing the Salesforce data that goes into Data Cloud helps enterprises get the best of both worlds – security and innovation.