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Today, LightBeam.ai emerged from stealth with $4.5 million in seed funding to announce the general availability of its AI-powered, identity-centric data privacy automation platform. 

Lightbeam’s solution uses AI and Natural Language Understanding (NLU) to identify segments of Personally Identifiable Information (PII) and tie it to a customer’s identity. 

For example, the platform can identify the context of a nine-digit number to determine if that’s a random string of characters, a social security number, bank account number or medical record and then determine who that data belongs to. 

This approach enables enterprises to increase visibility of data stored throughout the environment, what data they need to protect and who it belongs to. 


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Using automation to keep up with regulatory sprawl 

The company is emerging from stealth against a backdrop from which organizations are increasingly attempting to keep up with ever mounting privacy regulations — with the U.S. announcing a new data privacy pact and Utah becoming the fourth state to pass its own privacy bill. 

As local and international privacy regulations multiply, there is mounting pressure for organizations to implement optimal data management practices to maintain compliance. 

“While consumer awareness for data privacy is increasing, the industry is hamstrung with legacy (manual) approaches to data privacy management in light of current and evolving privacy regulations.,” said LightBeam’s cofounder and product chief, Priyadarshi Prasad. “Privacy officers and information security officers are having to deal with an exponentially growing volume and variety of data, making the manual ‘checkbox’ approach to privacy untenable.”

“At the same time, customers are beset with numerous tools, all trying to solve one or other aspect of privacy governance. Siloed solutions are inherently more costly to acquire and maintain and increase the risk of data exposure because of more moving parts.” he said. 

Lightbeam’s answer to the limitations of regulatory complexity and the limitations of legacy tools is to help organizations center their data protection strategy around people and their identities, rather than random data. 

Instead of simply scanning and cataloging data that looks important, Lightbeam’s AI attempts to identify which particular customer or identity the information belongs to so security teams can automate the protection of that data more effectively. 

The data privacy automation market 

Lightbeam isn’t the only provider looking to automate the challenge of data privacy, with the global data privacy software market projected to grow from $2.36 billion in 2020 to $25.85 billion by 2029 as more organizations attempt to keep up with local and International data protection laws. 

The organization is competing with a high number of providers in the market, including data discovery provider, BigID, which can identify, classify and catalog structured and unstructured data and provide users with data intelligence insights. 

BigID currently holds a valuation of $1.25 billion following a $100 million extended series D funding round last year. 

Another key competitor is Collibra, a data intelligence platform that can catalog data in enterprise environments and automate data governance workflows, which last year raised $250 million in funding and achieved a valuation of $5.25 billion.

Although, Prasad argues that Lightbeam’s AI and its ability to tell what customer a piece of data belongs to give it an advantage over existing solutions. 

“While other tools get excited (and start throwing alerts left and right) when they detect a nine-digit number, LightBeam uses its AI/ML-stack to figure out the identity to whom such a nine-digit number belongs. The identity-centric approach helps organizations understand and protect against the real risk of sensitive data exposure and automate their data security privacy policies based on identities,” Prasad said. 

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