Baltimore startup Atana is building a network that keeps data private - Technical.ly Baltimore

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Sep. 19, 2018 6:59 pm

Baltimore startup Atana is building a network that keeps data private

Founded by Hopkins grads David Shi and Kevin Joo, the company recently closed a $300,000 seed round.
Atana team members Kevin Joo, David Shi and Nam Nguyen.

Atana team members Kevin Joo, David Shi and Nam Nguyen.

(Courtesy photo)

When Kevin Joo looks at available data in the world, he recognizes the growing volume that’s available, and how that’s helped society. Yet most of that data is owned by the few companies that provide it, which leads to compromises on privacy and other issues. Additionally, the data that might be necessary to build an effective computational tool may not be available.

Along with fellow Johns Hopkins grad David Shi, Joo founded a startup creating a decentralized network to address those tradeoffs.

“We built Atana to allow everyone to harness power of data without compromising their basic privacy rights,” Joo said.

According to Joo, Atana’s technology includes encryption and blockchain-based infrastructure. It is designed to provide searchable data that is available to be analyzed, but does not reveal the contents or identities. The system also has built-in consent, “preventing a system where you don’t have control over where your information is going,” Joo said.

With tools that allow info to be transferred across databases, Atana’s team hopes to spur more collaboration when it comes to creating algorithms and other tools. The idea is that people and companies will be able to share data that can be used to create algorithms, yet keep the contents hidden.

Ultimately, the company aims to create a network where people can share data and search for what they need, with exchanges made via cryptocurrency.

One area where Atana has found interest is life sciences and healthcare, where data privacy is crucial for patients and intellectual property is key for companies, Joo said. In this realm, researchers would benefit from more access to data in building statistical models. Joo also envisions patients being able to find models that predict the likelihood of specific diseases.

Early on, the company got funding through Hopkins’ O’Connor award for undergraduate startups, and various hackathons. Shortly after the cofounders graduated, they closed on a $300,000 seed round from angel investors. The team also opened an office in Baltimore inside Woodberry’s Clipper Mill.

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