SAN JOSE, Calif.--(BUSINESS WIRE)--Concentric Inc., a leading vendor of intelligent AI-based solutions for protecting business-critical data, today announced that Company Nurse, a leading provider of COVID-19 health screenings and workplace injury reporting and nurse triage services for employers, has selected Concentric’s Semantic Intelligence™ solution to protect private workers' compensation data on behalf of its customers and users. The solution autonomously discovers Company Nurse’s business-critical unstructured data, highlighting opportunities to mitigate data sprawl and reduce threat surfaces.
“Company Nurse eases the pain of workers’ comp by completing incident reports, providing appropriate care advice to injured workers, managing providers for referral, and more,” said Henry Svendblad, CTO for Company Nurse. “The information on the forms and reports adds up to significant quantities of unstructured data. With Concentric, we can secure this private information without extra staff or overhead. It’s a powerful addition to our cyber security strategy.”
Semantic Intelligence™ automates unstructured data security using deep learning to categorize data, uncover business criticality and reduce risk. The solution uses the baseline security practices observed for each data category to calculate a “risk distance” from the baseline to each individual form or file managed by Company Nurse. Risk distance reveals inappropriate sharing, risky storage locations and incorrect classifications – all without regex, rules or upfront policy configuration. Concentric works autonomously to reduce staff demands required to secure data, while providing continuous protection.
“Not long after we installed the solution, Semantic Intelligence found duplicate files we didn’t need to maintain and spotted opportunities to tighten up access permissions and improve least-privileges discipline,” continued Svendblad. “With Concentric we’ve solidified our cyber security leadership in the workers’ comp industry. Looking ahead, as customers adopt our new COVID-19 screening and triage program, protecting their private data will be one less thing for them to worry about.”
“We’re proud to be a part of the Company Nurse story,” said Shankar Subramaniam, co-founder and VP of Engineering at Concentric. “We look forward to a long and productive relationship. By helping them find duplicate files and oversharing incidents, we’re addressing tough-to-solve problems that are pervasive across the industry.”
About Company Nurse
Workplace injuries happen. Company Nurse provides COVID-19 health screenings and nurse triage for injured workers and makes the process of workers’ comp pain-free. As an industry pioneer, Company Nurse continues to grow so that businesses can take care of people and processes, make workplaces more productive, and businesses more profitable. For more information, contact Jackie Binsfeld at email@example.com or call 480-717-6843.
Concentric discovers and protects business critical content stored in unstructured data, which according to Gartner represents 80 percent of all corporate data. Concentric protects organizations’ most sensitive data, including intellectual property, financial documents, PII/PCI content in documents, business confidential data (strategy plans, product roadmaps, contracts, blueprints); and private data stored in Office365/Sharepoint, Windows file shares, Box, Google Drive, Dropbox, etc. The Concentric Semantic Intelligence™ solution uses deep learning to develop a semantic level understanding of the content in each document and leverages that data to discover business sensitive content, surface high risk data, and remediate issues without relying on upfront rules or complex configuration. Concentric is venture backed by leading Silicon Valley VCs and is headquartered in San Jose, Calif. For more information, see https://www.concentric.ai
Concentric and Semantic Intelligence™ are or may be registered trademarks of Concentric AI, Inc. All other marks and names mentioned herein may be trademarks of their respective companies.