Discover and classify business-critical data autonomously and accurately.
Modern cloud solutions and pervasive network connectivity have democratized sharing and collaboration, with enterprises managing millions of documents and dozens of databases every day. Many contain personally identifiable information (PII), financial information, intellectual property and other sensitive data that’s hard to find and protect.
Risks from compromised accounts, careless employees, and malicious insiders must be managed. But it’s not easy to identify at-risk data, classify it correctly, and limit access to appropriate personnel. Not only that, the harsh reality is that it’s even harder to find IT staff that possess the content expertise to write effective automation rules.
According to Gartner, with the pent up demand for higher levels of data security, 30% of enterprises will have adopted data security platforms by 2024 – a significant increase from the 5% reported in 2019.
For any organization, managing data risk is no longer a nice-to-have; it plays a crucial role in doing business.
Know where your data resides and autonomously understand all your sensitive data with semantic context
Classify your sensitive data without rules or relying on end-users
Turbocharge our existing security investments with standards-based classification for accurate policy enforcement
When it comes to data discovery, organizations must be confident they know where their business-critical data is, what types of data they have, and if that data has been properly classified. The Concentric Semantic Intelligence solution uses sophisticated machine learning technologies to autonomously scan and categorize data — from financial data to PII/PHI/PCI to intellectual property to business confidential information – wherever it is stored.
As organizations increasingly embrace cloud transformation, every piece of data can easily be shared with anyone, anywhere. But just as easily, that data can be copied, duplicated, modified and shared. Data classification for enterprises has been a difficult exercise with security teams stuck between 2 difficult choices: either writing rules to identify and label data — a complex and error prone exercise riddled with false positives and false negatives —or relying on end-users to self classify.
With Concentric Semantic Intelligence, security teams can identify their sensitive data with semantic context and label data centrally without complex rule writing or relying on end-users.
For optimal data classification, it’s pivotal to integrate with other elements of an IT tech stack. Defense-in-depth, a pillar of modern data security planning, is substantially more effective when paired with solutions capable of integrating with other data security products and frameworks. Concentric Semantic Intelligence seamlessly integrates with all the leading frameworks including Microsoft’s Information Protection (MIP) solution for data classification and management.
We organize data into thematic categories for analysis and display using powerful deep learning technologies for language analysis. This eliminates hard-to-maintain rules and pattern matching.
Our natural language processing (NLP) capabilities far exceed the pattern or keyword-based techniques of other automated approaches and solutions. Concentric’s NLP can, for example, interpret the meaning of the same word used in different contexts or interpret the meaning of an entire sentence or paragraph to accurately understand the semantic context of data.
The Concentric MIND service catalogs and curates deep learning models to ensure you always have the latest and best-fitting solution for your data. Sophisticated peer file analysis maximizes classification accuracy.
Yes. Concentric Semantic Intelligence can compare semantically similar data for classification mismatches, end-user errors or malicious insiders, identify anomalies and easily remediate these issues.
As we discussed in the benefits above, Concentric seamlessly integrates with a variety of classification frameworks, such as Microsoft Information Protection (AIP/MIP) to leverage their classification schema to apply the appropriate metadata labels.
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