Immuta adds new tools for anonymizing data and personalized access

Hoping to help data scientists speed up their artificial intelligence and machine learning projects, data management startup Immuta Inc. today is updating its platform with new features that deliver personalized data access and automated differential privacy.

Immuta, which was founded by former National Security Agency technologists in 2014, only came out of stealth mode in February when it announced an $8 million Series A funding round. At the same time, the company touted the unique capabilities of its platform, which is used by data scientists to share raw data safely and securely while ensuring compliance with any regulations they must adhere to.

Now, the startup is pushing out the first major update, with new features that include automated differential privacy controls and personalized data access. The first new feature is designed to allow organizations to access customer data while simultaneously ensuring the privacy of any personally identifiable information. Essentially what it does is it anonymizes sensitive data, so that data scientists can use it in their machine learning and AI algorithms without breaching any governance requirements.

This is an important capability because anonymizing data is not that easy to do, Immuta Chief Executive Officer Matt Carrol (pictured) said in an interview. “What we learned in our time working in the U.S. government, when you want to anonymize information, you can’t do it on large, general data sets,” he said.

He explained that anonymizing data has historically always been a very painstaking process with data scientists forced to write a line of code for each regulation or restriction governing each piece of data. With the update, Immuta has “generalized the types of rules to select how you want to anonymize data and make it work for the data source,” Carrol said. This should ensure compliance with even the strictest of regulations, such as Europe’s incoming General Data Protection Act, which will come into force next year.

The second new feature in Immuta’s platform adds personalized data access in order to provide greater accountability over who can access different kinds of data sets. The feature works by automating the privacy permission process with a catalog-style data management portal. In turn, this allows admins to restrict data access to individual users based on their roles, corporate policies and industry regulations, Immuta said.

“We’ve added auditing tools to allow for data usage accountability, which is crucial to those impacted by GDPR,” Carrol said. “Other solutions just mask or filter out personal data. Data scientists often need that data, but they need to provide the purpose and justify their use of that data.”

Immuta is also adding a new Policy Building in Plain English feature, which makes it “click-simple to add personalized permissions to dataset access,” Carrol said. Lastly, the company has introduced something called Purpose-Based Data Restrictions, which places limits on how data can be used to ensure regulatory compliance is maintained.

Information technology industry analyst David Floyer of Wikibon, owned by the same company as SiliconANGLE, said Immuta was trying to position itself as a kind of “arbitrator” that ensures the compliance of any data organizations use. He added that it’s a pretty unique offering and that Immuta has very few competitors in the space at present.

“Others with tools to help in this area include Catalogic, but Immuta is a bit more than that, putting in not only the catalog but all the rules as well,” Floyer said. “[However], Immuta is early in their cycle, and we’re still in the early days of solving this problem.”

Immuta said its newly updated platform is available now.

Image: Immuta

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