Quantara AI has announced the general availability of its AI-powered Cyber Risk Intelligence platform, designed to help enterprises continuously identify and measure the small percentage of cyber exposures responsible for the majority of financial risk. As cyber threats grow more dynamic and financially impactful, organizations are increasingly looking for solutions that connect security metrics directly to business risk. Therefore, Quantara AI developed this platform to move enterprises away from outdated, snapshot-based risk assessments toward continuous, real-time cyber risk intelligence.
Unlike traditional cyber risk evaluations that rely on periodic assessments, the new platform delivers a persistent and always-on Cyber Risk Quantification (CRQ) model. Additionally, it combines threat intelligence, business context, and financial exposure into a single system of record. As a result, CISOs, executive teams, and board members can make faster, data-backed security investment decisions with clear financial justification.
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Industry research also supports this transition toward automated cyber risk intelligence. According to IDC, enterprises are shifting toward predictive, AI-driven risk models. By 2028, IDC estimates that 40% of organizations will adopt AI-powered CRQ platforms that convert technical security metrics into measurable financial exposure. Consequently, enterprises can align cybersecurity budgets with actual business risk and improve strategic planning.
Currently, many organizations remain stuck using manual risk modeling processes that fail to keep pace with modern threat environments. For instance, companies often rely on consultant-driven assessments and spreadsheet-based risk tracking that become outdated immediately after completion. Furthermore, traditional GRC frameworks frequently operate without integrating real-time threat data or business telemetry. At the same time, legacy vulnerability management programs typically focus on technical severity rather than financial materiality. Because of these limitations, security leaders often struggle to determine which risks truly require urgent attention.
To solve these challenges, Quantara AI built a platform that continuously merges threat intelligence, historical industry loss data, business environment context, and financial risk modeling into a single operational system. Moreover, the platform correlates near real-time threat activity with specific business applications, sensitive data assets, and operational processes. By analyzing adversary behavior and attack paths, it helps organizations focus on the top 1% of exposures most likely to cause significant financial damage.
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In addition, the platform uses probabilistic modeling to convert cyber exposures into financial loss forecasts and Value at Risk (VaR) metrics. It also measures Risk Reduction Impact (RRI), allowing security teams to understand how each investment reduces financial risk. As a result, enterprises can prioritize cybersecurity spending more effectively and demonstrate measurable ROI.
The platform also delivers executive-ready insights through AI-generated natural-language reporting. Furthermore, it automatically maps cyber risks to regulatory and disclosure frameworks, helping organizations simplify compliance and board-level reporting processes.
“In reality, only a small fraction of cyber exposures account for the majority of potential financial loss,” said Harish Barnela, Founder and CEO of Quantara AI. “Quantara AI was built to continuously quantify the 1% that matters so leaders can cut through the noise and make confident, financially grounded decisions as conditions change.”
By enabling real-time risk visibility and persistent monitoring, the platform helps enterprises accelerate decision-making across security and risk functions. Ultimately, Quantara AI aims to eliminate outdated manual workflows, including consultant-led CRQ modeling, legacy GRC systems without live threat integration, static vulnerability management programs lacking business context, and manual board reporting processes that consume weeks of effort.
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