Company’s Adaptive Manifold Compression Models Optimize Data Intensive Large Language Models to Accurately Discover All Sensitive Data Models with Context Quickly and Efficiently

Concentric AI, a leading vendor of intelligent AI-based solutions for autonomous data security posture management (DSPM), today announced the industry’s first DSPM solution with support for optimized large language models delivering unmatched data security and protection. As a result, Concentric AI’s Semantic Intelligence™ uniquely delivers semantic understanding of data and leverages context to offer precise accuracy in discovering sensitive data from intellectual property to financial data to business confidential information to PII/PCI/PHI, and more.

According to Gartner®, “Foundation models (which are mostly large language models) are designed to replace task-specific models”…“Foundation models represent a huge step change in the field of artificial intelligence, due to their massive pretraining and significant improvements in accuracy across a variety of tasks.” ¹

In the face of massive data volume growth, data sprawl across cloud and on-premises data repositories, and massive complexity in the nature of sensitive data, organizations have struggled with requiring large teams and massive operational costs to deal with voluminous data security risks, often burdening security teams with rule writing and pattern matching to discover sensitive data. This can result in organizations having limited visibility into where mission critical data is, and the inability to identify risks associated with wrong entitlements, inappropriate permissioning, risky sharing, and unauthorized access.

Unlike other solutions, Concentric AI uses optimized large language models to accurately discover data without needing inaccurate regex or pattern matching. While large language models are very data intensive, highly optimized data compression Adaptive Manifold Compression models achieve up to 10 times compression and orders of magnitude improvements in data discovery rates for optimal compute efficiency, storage and performance. With Concentric AI, organizations discover all sensitive data with context, accuracy and minimal false positives and negatives, all with unmatched speed and efficiency. Concentric AI’s differentiated AI-based technology uniquely performs computations on large language models without the compute burden or inefficiencies of other solutions.

“The popularity of models such as GPT-3 has attracted the attention of CIOs, CTOs, CISOs and data and analytics leaders, who are looking to exploit their potential for business use cases,” said Karthik Krishnan, Founder and CEO, Concentric AI. “Being the only company to leverage large language models gives Concentric AI the advantage in enabling organizations to protect their data with unmatched contextual understanding, all in an accurate and efficient manner needed to address today’s complex and ever-growing data environments and their associated security risks. These models allow enterprises to move past regex or pattern-based discovery of sensitive data to understand semantic meaning at unmatched efficiency while maintaining high accuracy and minimal false positives and false negatives.”

Concentric AI’s Semantic Intelligence™ is also the industry’s only solution that allows AI data fingerprinting to avoid rescanning of data to look for new patterns. As a result, organizations can discover patterns and specific things they are looking for without the burden of repetitive scanning. Once scanned, the data is fingerprinted for discovering characteristics important in the future.

According to recent industry research, the cost of a data breach averaged USD $4.35 million in 2022, reaching an all-time high. Breaches at organizations with fully deployed security AI and automation cost USD $3.05 million less than breaches at organizations with no security AI and automation deployed. Finally, the research showed that companies with fully deployed security AI and automation experienced on average a 74-day shorter time to identify and contain the breach, known as the breach lifecycle, than those without security AI and automation.

Concentric’s new capabilities expand the company’s leading AI technology to support highly differentiated, powerful capabilities for effective data security posture management. Zero training data models allow auto-categorization of data without customers having to provide training datasets. The solution comes with hundreds of out-of-the-box models to categorize data from tax filings to source code to contracts to trading data to PHI/PII/PCI and more, enabling customers to operationalize data security without large upfront or going work, or requiring large teams.

As a result, to date Concentric AI has protected more than 1 million users from breaches, scaled to petabytes of data per customer with unmatched accuracy, and remediated and protected up to 20 percent of business-critical data per customer that has been overshared through wrong entitlements, risky sharing, inappropriate permissions, or unauthorized access.

Concentric AI’s DSPM solution scans organizations’ data, detects sensitive or business critical content, identifies the most appropriate classification category, and automatically tags the data. Concentric AI uses artificial intelligence (AI) to improve discovery and classification accuracy and efficiency to avoid endless regex rules and inaccurate end user labeling. In addition, Concentric AI can monitor and autonomously identify risk to financial and other data from inappropriate permissioning, wrong entitlements, risky sharing, and unauthorized access. It can automatically remediate permissions and sharing issues or leverage other security solutions and cloud APIs to quickly and continuously protect exposed data.

Concentric AI’s Semantic Intelligence™ automates unstructured and structured data security using deep learning to categorize 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 of the same type to identify risk from oversharing, third-party access, wrong location, or misclassification. Organizations benefit from the expertise of content owners without intrusive classification mandates, with no rules, regex, or policy maintenance needed.

Availability and Pricing

Concentric AI’s latest version of Semantic Intelligence™ with optimized large language models is available today. For more information, see www.concentric.ai/product.

Note 1 – Gartner, Inc. “Innovation Insight for Artificial Intelligence Foundation Models,” by Arun Chandrasekaran, Magnus Revang, Arnold Gao. Oct. 27, 2022. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

About Concentric AI

With Concentric AI, organizations can finally address their unmet data security needs by discovering and protecting business-critical content. Concentric AI protects intellectual property, financial data, PII/PCI content, customer data, business confidential content and more, across on-premises and cloud-based data stores, as well as messaging and communication applications. The Concentric AI Semantic Intelligence™ Data Security Posture Management solution uses deep learning and Risk Distance™ analysis to accurately categorize data, assess risk, and remediate security issues – without relying on upfront rules or complex configuration. Concentric AI is venture-backed by leading Silicon Valley VCs and is headquartered in San Jose, Calif. For more information, see https://www.concentric.ai.

Concentric AI, Semantic Intelligence™, and Risk Distance™ are or may be registered trademarks of Concentric AI, Inc. All other marks and names mentioned herein may be trademarks of their respective companies.

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Concentric AI's adaptive manifold compression models optimize data intensive large language models to accurately discover all sensitive data models with context quickly and efficiently