Getting to the Moon was the first chapter. Interlune and Astrolab are working on how to operate there.
Updated
March 6, 2026 1:32 AM
Apollo 17 Astronaut's Snapshot of Taurus-Littrow Valley. PHOTO: UNSPLASH
As plans for a long-term human presence on the Moon pick up pace, the focus is shifting from landing there to working there. It is one thing to reach the surface. It is another to build roads, prepare sites and extract materials in a way that can support real activity.
That is where Interlune and Astrolab come in. Interlune is a space resources company. Astrolab builds planetary rovers. The two are now working together to mount Interlune’s lunar digging system onto Astrolab’s Flexible Logistics and Exploration (FLEX) rover. They have completed a concept study and are planning hardware testing in Houston.
The aim is straightforward: combine a rover that can move reliably across the Moon with equipment that can dig, collect and handle lunar soil. Interlune is focused on harvesting natural resources from the Moon, starting with helium-3. To do that at scale, the system cannot sit in one place. It has to move across the surface, handle dust and operate in harsh conditions. "Reliable, autonomous mobility is crucial to the Interlune harvesting system and broader lunar infrastructure development", said Rob Meyerson, co-founder and CEO of Interlune. "Astrolab's FLEX is the right vehicle for the job".
By fitting its digging and collection hardware onto FLEX, Interlune is working toward a mobile system that can gather large amounts of lunar soil and support future construction needs. Beyond helium-3, the same setup could help prepare base sites, level ground, build protective barriers and lay the groundwork for other structures. In simple terms, it is about turning a rover into a working machine for the Moon.
The partnership also connects to Interlune’s work with Vermeer Corporation to develop equipment for continuous, high-volume digging adapted to lunar conditions. Taken together, the goal is to build systems that can support both commercial and government missions — whether that means resource extraction or preparing land for future bases.
For Astrolab, the collaboration strengthens the role of FLEX as more than just a transport vehicle.
"Working with Interlune further differentiates FLEX as the rover of choice for commercial and government Moon missions", said Jaret Matthews, Astrolab founder and CEO. "Interlune's expertise in developing and testing highly specialized regolith simulant will further enhance FLEX's ability to mitigate dust and operate in extreme environments".
Testing will be centered in Houston, which is becoming an important hub for commercial space development. Astrolab was the first company to lease space at the Texas A&M University Space Institute, currently under construction at NASA’s Johnson Space Center. Interlune operates the Houston-based Interlune Research Lab, where it creates and tests simulated versions of lunar soil.
That detail matters. Moon dust is fine, abrasive and difficult to manage. Before any hardware flies, it needs to prove it can survive and function in those conditions. By testing their systems in realistic soil simulants, the companies can refine how the rover moves and how the digging system performs.
The Houston lab is partially funded by the Texas Space Commission, reflecting the growing role of regional space initiatives in supporting private companies building beyond Earth. Overall, the collaboration is not about grand promises. It is about integrating hardware, running real tests and taking practical steps toward operating on the Moon.
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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.