Concentric AI announces support for optimised large language models delivering unmatched DSPM - The EE

Concentric AI announces support for optimised large language models delivering unmatched DSPM

San Jose, United States – Concentric AI, a vendor of intelligent AI-based solutions for autonomous data security posture management (DSPM), announced the DSPM solution with support for optimised large language models delivering unmatched data security and protection.

As a result, Concentric AI’s Semantic Intelligence 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.

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, organisations 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 organisations having limited visibility into where data is, and the inability to identify risks associated with wrong entitlements, inappropriate permissioning, risky sharing, and unauthorised access.

Unlike other solutions, Concentric AI uses optimised large language models to accurately discover data without needing inaccurate regex or pattern matching. While large language models are very data intensive, highly optimised 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, organisations 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 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,” says Karthik Krishnan, founder and CEO, Concentric AI. “Being the only company to leverage large language models gives Concentric AI the advantage in enabling organisations 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 solution that allows AI data fingerprinting to avoid rescanning of data to look for new patterns. As a result, organisations 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 [$4.35 million (€4.07 million)] in 2022, reaching an all-time high. Breaches at organisations with fully deployed security AI and automation cost [$3.05 million (€2.85 million)] less than breaches at organisations 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 AI technology to support differentiated, capabilities for effective data security posture management. Zero training data models allow auto-categorisation of data without customers having to provide training datasets. The solution comes with hundreds of out-of-the-box models to categorise data from tax filings to source code to contracts to trading data to PHI/PII/PCI and more, enabling customers to operationalise 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% of business-critical data per customer that has been overshared through wrong entitlements, risky sharing, inappropriate permissions, or unauthorised access.

Concentric AI’s DSPM solution scans organisations’ 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 unauthorised access. It can automatically remediate permissions and sharing issues or leverage other security solutions and cloud APIs to continuously protect exposed data.

Concentric AI’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 of the same type to identify risk from oversharing, third-party access, wrong location, or misclassification. Organisations benefit from the expertise of content owners without intrusive classification mandates, with no rules, regex, or policy maintenance needed.

Follow us and Comment on Twitter @TheEE_io

By continuing to use the site, you agree to the use of cookies. more information

The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.