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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Where smarter storage meets smarter logistics.
Updated
January 8, 2026 6:32 PM
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Kioxia's flagship building at Yokohama Technology Campus. PHOTO: KIOXIA
E-commerce keeps growing and with it, the number of products moving through warehouses every day. Items vary more than ever — different shapes, seasonal packaging, limited editions and constantly updated designs. At the same time, many logistics centers are dealing with labour shortages and rising pressure to automate.
But today’s image-recognition AI isn’t built for this level of change. Most systems rely on deep-learning models that need to be adjusted or retrained whenever new products appear. Every update — whether it’s a new item or a packaging change — adds extra time, energy use and operational cost. And for warehouses handling huge product catalogs, these retraining cycles can slow everything down.
KIOXIA, a company known for its memory and storage technologies, is working on a different approach. In a new collaboration with Tsubakimoto Chain and EAGLYS, the team has developed an AI-based image recognition system that is designed to adapt more easily as product lines grow and shift. The idea is to help logistics sites automatically identify items moving through their workflows without constantly reworking the core AI model.
At the center of the system is KIOXIA’s AiSAQ software paired with its Memory-Centric AI technology. Instead of retraining the model each time new products appear, the system stores new product data — images, labels and feature information — directly in high-capacity storage. This allows warehouses to add new items quickly without altering the original AI model.
Because storing more data can lead to longer search times, the system also indexes the stored product information and transfers the index into SSD storage. This makes it easier for the AI to retrieve relevant features fast, using a Retrieval-Augmented Generation–style method adapted for image recognition.
The collaboration will be showcased at the 2025 International Robot Exhibition in Tokyo. Visitors will see the system classify items in real time as they move along a conveyor, drawing on stored product features to identify them instantly. The demonstration aims to illustrate how logistics sites can handle continuously changing inventories with greater accuracy and reduced friction.
Overall, as logistics networks become increasingly busy and product lines evolve faster than ever, this memory-driven approach provides a practical way to keep automation adaptable and less fragile.