Company’s Risk Distance Analysis Technology Recognised for Innovative Use of AI and Deep Learning to Autonomously Discover and Protect Business-Critical Data
Concentric Inc., a vendor of intelligent AI-based solutions for protecting business-critical data, announced it has won a 2021 Artificial Intelligence Excellence Award for its Risk Distance natural language processing analysis technology in the Business Intelligence Group’s Artificial Intelligence Excellence Awards program.
Concentric’s Semantic Intelligence automates unstructured and structured data security using deep learning to categorise data, uncover business criticality and reduce risk. Its Risk Distance analysis technology uses the baseline security practices observed for each data category to spot security anomalies in individual files. It compares documents with peers in the same category to identify risk from oversharing, third party access, and wrong location or misclassification. Organisations benefit from the expertise of content owners without intrusive classification mandates, with no rules, regex or policy maintenance needed.
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‘We are so proud to name Concentric as a winner in our inaugural Artificial Intelligence Excellence Awards program’, said Maria Jimenez, chief nominations officer for Business Intelligence Group. ‘It was clear to our judges that Concentric’s Risk Distance technology is using AI to improve the lives of their customers and employees. Congratulations to the entire team!’
Customers use Semantic Intelligence to discover and manage risks to privacy-sensitive and regulated data, such as customer data or personal health information. They also rely on the solution for their zero-trust data access governance programs, where the solution autonomously evaluates access based on document contents and meaning, not file folder locations, end-user markup or other unreliable access control alternatives. Semantic Intelligence protects all types of data, ranging from intellectual property to financial information to sensitive human resources files – continuously and autonomously.
