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Lightbeam’s answer makes use of AI and Pure Language Understanding (NLU) to determine segments of Personally Identifiable Data (PII) and tie it to a buyer’s identification.
For instance, the platform can determine the context of a nine-digit quantity to find out if that’s a random string of characters, a social safety quantity, checking account quantity or medical file after which decide who that information belongs to.
This method permits enterprises to extend visibility of knowledge saved all through the atmosphere, what information they should shield and who it belongs to.
Utilizing automation to maintain up with regulatory sprawl
The corporate is rising from stealth towards a backdrop from which organizations are more and more making an attempt to maintain up with ever mounting privateness laws — with the U.S. asserting a brand new data privacy pact and Utah turning into the fourth state to cross its personal privateness invoice.
As native and worldwide privateness laws multiply, there may be mounting strain for organizations to implement optimum information administration practices to keep up compliance.
“Whereas client consciousness for data privacy is growing, the business is hamstrung with legacy (guide) approaches to information privateness administration in mild of present and evolving privateness laws.,” stated LightBeam’s cofounder and product chief, Priyadarshi Prasad. “Privateness officers and data safety officers are having to cope with an exponentially rising quantity and number of information, making the guide ‘checkbox’ method to privateness untenable.”
“On the identical time, prospects are beset with quite a few instruments, all making an attempt to unravel one or different facet of privateness governance. Siloed options are inherently extra pricey to accumulate and keep and improve the chance of knowledge publicity due to extra transferring components.” he stated.
Lightbeam’s reply to the restrictions of regulatory complexity and the restrictions of legacy instruments is to assist organizations heart their information safety technique round individuals and their identities, fairly than random information.
As a substitute of merely scanning and cataloging information that appears necessary, Lightbeam’s AI makes an attempt to determine which explicit buyer or identification the data belongs to so safety groups can automate the safety of that information extra successfully.
The info privateness automation market
Lightbeam isn’t the one supplier trying to automate the problem of knowledge privateness, with the worldwide data privacy software market projected to develop from $2.36 billion in 2020 to $25.85 billion by 2029 as extra organizations try and sustain with native and Worldwide information safety legal guidelines.
The group is competing with a excessive variety of suppliers out there, together with information discovery supplier, BigID, which may determine, classify and catalog structured and unstructured information and supply customers with information intelligence insights.
BigID at present holds a valuation of $1.25 billion following a $100 million prolonged collection D funding spherical final 12 months.
One other key competitor is Collibra, a knowledge intelligence platform that may catalog information in enterprise environments and automate information governance workflows, which final 12 months raised $250 million in funding and achieved a valuation of $5.25 billion.
Though, Prasad argues that Lightbeam’s AI and its capacity to inform what buyer a chunk of knowledge belongs to provide it a bonus over current options.
“Whereas different instruments get excited (and begin throwing alerts left and proper) after they detect a nine-digit quantity, LightBeam makes use of its AI/ML-stack to determine the identification to whom such a nine-digit quantity belongs. The identity-centric method helps organizations perceive and shield towards the actual threat of delicate information publicity and automate their information safety privateness insurance policies based mostly on identities,” Prasad stated.
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