Artificial Intelligence

From Security Scores to Dollar Risk: Quantara AI Pushes Continuous Cyber Risk Modeling

Quantara AI launches a continuous platform designed to estimate the financial impact of cyber risk as companies move beyond periodic assessments

Updated

February 20, 2026 6:43 PM

A person tightrope walking between two cliffs. PHOTO: UNSPLASH

Cyber risk is increasingly treated as a financial issue. Boards want to know how much a cyber incident could cost the company, how it could affect earnings, and whether current security spending is justified.

Yet many organizations still measure cyber risk through periodic reviews. These assessments are often conducted once or twice a year, supported by consultants and spreadsheet models. By the time the report reaches senior leadership, the company’s systems may have changed and new threats may have emerged. The way risk is measured does not always match how quickly it evolves.

This gap is where Quantara AI is positioning its new platform. Quantara AI, a Boise-based cybersecurity startup, has introduced what it describes as the industry’s first persistent AI-powered cyber risk solution. The system is designed to run continuously rather than rely on occasional assessments.

The company’s core argument is straightforward: not every security weakness carries the same financial consequence. Instead of ranking issues only by technical severity, the platform analyzes active threats, identifies which company systems are exposed, and estimates how much money a successful attack could cost. It uses statistical models, including Value at Risk (VaR), to calculate potential losses. It also estimates how specific security improvements could reduce that projected loss.

The timing aligns with a broader market shift. International Data Corporation (IDC) projects that by 2028, 40% of enterprises will adopt AI-based cyber risk quantification platforms. These tools convert security data into financial estimates that can guide budgeting and investment decisions. The forecast reflects growing pressure on security leaders to present risk in terms that boards and regulators understand.

Traditional compliance and risk management systems often focus on meeting regulatory standards. Vulnerability management programs typically score weaknesses based on technical characteristics. Consultant-led risk studies provide detailed analysis, but they are usually performed at set intervals. In fast-changing threat environments, that model can leave decision-makers working with outdated information.

Quantara’s platform attempts to replace that periodic process with continuous measurement. It brings together threat data, internal system information and financial modeling in one system. The goal is to show, at any given time, which specific weaknesses could lead to the largest financial losses.

Cyber risk quantification as a concept is not new. What is changing is the expectation that these calculations be updated regularly and tied directly to financial decision-making. As cyber incidents carry clearer monetary consequences, companies are looking for ways to measure exposure with greater precision.

The broader question is whether enterprises will shift fully toward continuous, AI-driven risk analysis or continue relying on periodic external assessments. What is clear is that cybersecurity discussions are moving closer to financial reporting — and tools that estimate potential loss in dollar terms are becoming central to that shift.

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Deep Tech

How a South Korean University Team Is Turning Industrial Air Into Power

A turbine-inspired generator shows how overlooked industrial airflow could quietly become a new source of usable power

Updated

February 12, 2026 4:43 PM

Campus building of Chung-Ang University. PHOTO: CHUNG-ANG UNIVERSITY

Compressed air is used across factories, data centers and industrial plants to move materials, cool systems and power tools. Once it has done that job, the air is usually released — and its remaining energy goes unused.

That everyday waste is what caught the attention of a research team at Chung-Ang University in South Korea. They are investigating how this overlooked airflow can be harnessed to generate electricity instead of disappearing into the background.

Most of the world’s power today comes from systems like turbines, which turn moving fluids into energy or solar cells, which convert sunlight into electricity. The Chung-Ang team has built a device that uses compressed air to generate electricity without relying on traditional blades or sunlight.

At the center of the work is a simple question: what happens when high-pressure air spins through a specially shaped device at very high speed?  The answer lies in the air itself. The researchers found that tiny particles naturally present in the air carry an electric charge. When that air moves rapidly across certain surfaces, it can transfer charge without physical contact. This creates electricity through a process known as the “particulate static effect.”

To use that effect, the team designed a generator based on a Tesla turbine. Unlike conventional turbines with blades, a Tesla turbine uses smooth rotating disks and relies on the viscosity of air to create motion. Compressed air enters the device, spins the disks at high speed and triggers charge buildup on specially layered surfaces inside.

What makes this approach different is that the system does not depend on friction between parts rubbing together. Instead, the charge comes from particles in the air interacting with the surfaces as they move past. This reduces wear and allows the generator to operate at very high speeds. And those speeds translate into real output.

In lab tests, the device produced strong electrical power. The researchers also showed that this energy could be used in practical ways. It ran small electronic devices, helped pull moisture from the air and removed dust particles from its surroundings.

The problem this research is addressing is straightforward.
Compressed air is already everywhere in industry, but its leftover energy is usually ignored. This system is designed to capture part of that unused motion and convert it into electricity without adding complex equipment or major safety risks.

Earlier methods of harvesting static electricity from particles showed promise, but they came with dangers. Uncontrolled discharge could cause sparks or even ignition. By using a sealed, turbine-based structure, the Chung-Ang University team offers a safer and more stable way to apply the same physical effect.

As a result, the technology is still in the research stage, but its direction is easy to see. It points toward a future where energy is not only generated in power plants or stored in batteries, but also recovered from everyday industrial processes.