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Proscia Announces Massive Dataset Migration Service to Accelerate Transfer of Large-Scale Digital Pathology Image Data to the Cloud

By Author Proscia | October 24, 2016

Addresses the challenge of securely and rapidly moving large amounts of image data to the cloud.


Proscia Inc., the provider of the leading cloud-based platform for digital pathology, announced today a new service to enable rapid migration of large pathology data sets to the Proscia Pathology Cloud platform. The inefficiency in data upload has remained one of the factors limiting adoption of digital pathology. Proscia’s free massive dataset migrator makes the secure, HIPAA-compliant upload of data time, cost, and resource efficient.

Proscia and its customers often deal with very large images or datasets in digital pathology, where upload and migration can be major challenges. Pathology departments looking to adopt digital pathology software often have existing databases of images and corresponding patient data many gigabytes in size. Proscia has become a leader in managing high-volume digital pathology customers with best-in-class upload and migration solutions, as well as a focus on accessibility and security of customer data as a foundational principle. This new product offering enables clients to upload as much as 1 petabyte per week without using client bandwidth, and is provided free-of-charge to existing customers.

“Our team recognizes that some organizations may have doubts about their ability to migrate their existing images and data away from legacy, on-premises storage,” said Coleman Stavish, CTO at Proscia, “The dataset migrator has helped us eliminate that problem for our customers.”

The Proscia Pathology Cloud already implements two other data migration solutions working with its partners at Amazon Web Services and other cloud providers to serve hundreds of users from top institutions with a secure and compliant cloud-based platform for hosting, managing, and analyzing images of tissue and related data, and has recently announced an expansion towards tissue analytics.

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