Concentric Comes out of Stealth to Stop the Threat of Unprotected and Overshared Business-Critical Data
Concentric Is the First to Utilize AI and Deep Learning to Uncover the Business Criticality and Risk to Millions of Documents Dispersed Across the Enterprise That Are Vulnerable to Abuse by Hundreds or Thousands of Employees
Concentric announced the availability of a new approach to the most significant security challenge facing the enterprise business-critical unstructured data, stored on-premises or in the cloud, that is impossible to identify and protect manually. Enterprise customers using Concentric have already found millions of unprotected or inappropriately shared documents accessible by thousands of employees, which could have led to data breaches and costly fines. To combat this significant threat, Concentric is the first company to leverage deep learning capabilities to identify and autonomously quantify risk by developing an accurate and detailed semantic understanding of all data. The company uses these insights to efficiently and effectively protect business-critical data and meet security, compliance and privacy mandates.
Concentric is also announcing that it has raised $7.5 million from Clear Ventures, Engineering Capital, Homebrew and Core Ventures.
The fact is, today’s organizations lack insight into risks associated with business-critical information like contracts, financial documents, payroll, M&A plans, product roadmaps and source code, to name a few. A report published today by the company, based on live data analyzed by Concentric’s Semantic Intelligence™ solution, reveals the composition and risks found in a typical organization’s unstructured data:
- An average business has nearly 10 million documents, with 1.2 million documents deemed business critical. Of those business-critical documents, over 15% are at risk because of improper sharing with users and groups or inadequate/incorrect data classification.
- On average, non-C-Suite employees had access to 90% of business-critical documents.
- Of these business-critical documents, approximately 200,000 files in an enterprise are overshared (translating to around 40 files per employee).
The Concentric Semantic Intelligence solution uses powerful deep learning technology to autonomously develop an unparalleled semantic understanding of each document to deliver the industry’s most complete, detailed and accurate risk-oriented view into business-critical information. When the solution finds at-risk files, Concentric’s native remediation capabilities proactively and automatically remediate the document’s risk factors to protect them effectively and efficiently.
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Existing approaches like static, predefined rules produce mediocre results at best, delivering documents that may or may not be business critical. And asking employees to categorize documents requires extensive training and constant vigilance to make sure everyone is doing their part to categorize accurately. Likewise, these methods also can’t fully evaluate a document’s true meaning, making it difficult to assess risk.
Semantic Intelligence not only uncovers, categorizes and classifies the documents, but it also allows IT and security teams to easily monitor data security with up-to-the-second information and powerful risk visualizations that drill down into the at-risk documents to explore in more granular detail. The solution also integrates with major third-party security and data stores to help customers leverage the security investments they already have in place.
“Concentric is an essential part of Cadence’s data security portfolio. We use it to identify all the business-critical data – product documentation, finance reports, contracts, etc.,” noted Sreeni Kancharla, CISO Cadence Design Systems. “Legacy solutions don’t work autonomously, and we’re forced to review flagged documents and fix security violations manually. Concentric gives us a critical layer of data security intelligence on top of the data protection solutions we already use.”
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The stakes are high for financial institutions to keep sensitive information protected, but at the same time, to allow the needed flexibility for companies to conduct ongoing business activities efficiently. One use case that can be extremely costly is enforcing information walls in financial services organizations that fall under oversight from the Securities and Exchange Commission (SEC). Firms rely on information walls to separate key conflicting areas of the business, for example, separating the investment banking department from the trading desk, to prevent the potential sharing of sensitive information with another department that could act on the insights for illegal purposes, such as insider trading. Improper sharing permissions on a highly confidential document can allow the document to fall into the wrong hands and the steep fines and substantial damage to the firm’s reputation can be crippling.
“Businesses understand the importance of protecting their critical assets, and yet, despite their best efforts, an extreme amount of data is left unsecured, unidentified, misclassified and at risk,” said Concentric CEO and Co-founder, Karthik Krishnan. “Unstructured data is currently copious and dispersed, and it includes an alarming amount of business-critical information. It’s a target for cybercriminals and can be a pitfall for regulatory compliance, but securing it is incredibly difficult. It’s the data challenge of our digital generation that we’re laser-focused on solving.”
“Unstructured data is now the industry’s primary threat surface because it’s highly dispersed and comes in all forms, and it’s tough to protect business-critical content,” said Chris Rust, founder and managing partner, Clear Ventures. “Concentric solves this problem with fundamentally new, autonomous capabilities that find, monitor, and secure an enterprise’s most valuable assets.”
Concentric was founded by Krishnan, CTO and vice president of engineering Shankar Subramaniam and Chief Data Scientist Madhu Shashanka. The founding team has an extensive background in networking and security at several successful companies such as Juniper Networks, PGP Corporation (acquired by Symantec), Symantec, HPE, Aruba Networks (IPO), Niara (acquired by HPE) and Andiamo Systems (acquired by Cisco).