A Massachusetts startup advances scalable light-control tech for AR, AI and imaging markets
Updated
February 27, 2026 3:59 PM
Myrias Optics' Nanoimprinted All-inorganic Metaoptic. PHOTO: MYRIAS OPTICS
Myrias Optics, a Massachusetts-based optical technology startup, has raised US$2.1 million in a Seed 1 financing round to accelerate the commercialization of its advanced light-control technology. The round was led by MassVentures, with participation from existing investors Hoss Investment Inc., Maroon Venture Partners and Tenon Venture Partners, as well as new investors Mill Town Capital, TiE Boston Angels and Doug Crane. This new round follows a US$3.3 million seed financing completed in December 2023, led by Asia Optical, and a US$1.5 million Direct-to-Phase II award from the National Science Foundation. In total, Myrias has secured US$6.9 million to date, positioning it to move from development to scaled production.
The company builds ultra-thin, nano-patterned surfaces that precisely control how light moves through a device. These structures replace or enhance traditional lenses and optical parts inside products such as augmented reality headsets, AI data center hardware, consumer electronics, industrial systems and medical imaging devices. The goal is straightforward: to deliver high optical performance while making the parts easier and more cost-effective to manufacture in large quantities.
Across industries such as augmented reality and AI infrastructure, manufacturers face a common challenge. They need highly precise light-guiding components that can withstand heat and long-term use. At the same time, those components must be produced consistently and at scale. Traditional semiconductor-style fabrication can be costly, while polymer-based optical manufacturing can face limits in durability and thermal stability.
Myrias addresses this gap by using inorganic materials and a nanoimprint manufacturing process to create stable, repeatable optical layers on wafers. This approach is designed to combine performance with manufacturability. In augmented reality systems, for example, the company’s technology enables higher viewing angles while remaining suitable for volume production. In AI data centers, the same material and process advantages support improved light transfer and stronger performance under demanding thermal conditions. These benefits also extend to advanced imaging systems in consumer, industrial and medical markets.
The new Seed 1 funding is intended to expand manufacturing capacity and scale pilot production lines. The company will also continue executing active customer programs. Myrias is already working with strategic partners and Tier 1 supply chain participants to integrate its waveguide and light-shaping solutions into commercial AR platforms, AI photonics systems and advanced imaging products. The capital, therefore, supports a clear next step: moving from validated prototypes to a steady commercial supply.
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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.