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Concentric was established by Karthik Krishnan (CEO), Madhu Shashanka (chief data scientist), and Shankar Subramaniam (CTO and VP, engineering) on the premise that new deep learning technologies may avoid data loss and breaches.
They believe AI-powered automation is the solution to today’s data security and governance issues. Risk Distance Analysis for autonomous risk assessment and Concentric MIND for an AI-assisted deep learning model and policy management/curation are among the patented capabilities of their groundbreaking Semantic Intelligence system.
The continuous growth of internet interconnectivity has resulted in an increase in cyberattack occurrences, many of which have had disastrous and terrible repercussions. Concentric AI says it secures the future of work by autonomously securing business-critical data concealed in today’s distributed workforce’s millions of files and databases.
With the rise of remote work and poor security mechanisms around it, users commonly transfer data through anonymous links, personal email accounts and the cloud. This has resulted in an avalanche of sensitive information being stored in unsafe areas, files being shared with the wrong people, and documents being categorized wrongly. Human error is responsible for 95% of cybersecurity breaches, according to statistics.
This is why Concentric relies on natural language processing (NLP) to identify and categorize sensitive information, assess risk, and resolve security issues – all while avoiding the overhead of rules and regulations. This allows enterprises to identify outlier files that aren’t being managed in the same way as their peers, whether in the cloud or on-premises, averting data loss and breaches.
Data security trends
Today’s data management requires precise, low-overhead automation that can handle many storage sites and large data volumes. Concentric responds to this trend with a solution that eliminates the need for elaborate, difficult-to-maintain rule sets or end-user engagement.
The current rules-based security paradigm is unsustainable, especially in an environment where consistency is not maintained. Security techniques, for example, do not adapt automatically to changing business situations such as rapid expansion or new API interactions with third parties. Configuring security rules on data loss prevention products, firewalls, intrusion detection systems, user accounts and other security technologies becomes inaccurate, inefficient and incomplete as a result of this. A rule-based security methodology may be overly lenient or uncomplicated in some cases. Hackers can easily take advantage of such a setup.
Security professionals are also rarely experts in the data they protect. According to a panel of 34 experts on securing sensitive data, most security professionals have no idea where their sensitive data is since they don’t develop policies to categorize it effectively and regularly. To understand data sensitivity and proper access, security experts must seek continuing assistance and insight from content owners. Organizations frequently don’t realize this until they’ve spent months categorizing data and attempting to assess risk, only to learn that governance is a time-consuming and continuing effort.
Concentric responds to this trend by reducing the expertise required for effective data security. Traditional rules-based data security systems need substantial content expertise on the part of IT teams in order to develop proper data discovery rules and policies. Infosec pros can effectively safeguard data with Concentric without needing content knowledge. Concentric’s Semantic Intelligence solution, which includes Risk Distance Analysis, an AI-assisted risk assessment tool, was designed to use the collective wisdom of content owners to build security baselines for similar files.
Finding risk no longer needs complicated rules, procedures, and time-consuming end-user consulting using Risk Distance. It’s now just a matter of computing the distance between each file and the risk baseline. Customers of Concentric utilize the product to prevent data breaches, comply with privacy requirements, avoid unauthorized data sharing and automate risk-mitigation processes.
Funding, customers and competitors
Ballistic Ventures, a new VC firm dedicated to advising and supporting early-stage cybersecurity firms, led the funding round. The $19 billion market for data protection, access governance, and loss prevention is the goal of the investment. Citi Ventures also participated in the round as a strategic investment, as did current investors Core Ventures Group, Engineering Capital, Homebrew, and Clear Ventures.
With these investments, the firm plans to expand its current company customer base through increased sales and marketing activities, as well as expand its solution to safeguard a growing list of content, locations and use cases.
“Our mission is simple: we are remaking the multibillion dollar data security market with an autonomous solution capable of discovering, evaluating and protecting structured and unstructured content across the entire cloud and on-premises landscape,” said Krishnan.
There are several companies that are usually in competitive situations with Concentric AI, including Varonis, Netwrix/Stealthbits, Spirion, Symantec, McAfee and Digital Guardian, amongst others. However, Concentric claims to be unique in that it uses deep learning to identify sensitive customer information, intellectual property, business papers, personally identifiable information, PHI, and other data without the need of rules.
It also boasts a curated catalog of AI models for high accuracy, a SaaS solution with no ongoing administrative burden, and simple, seamless integration with third-party security investments.
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