The Hong Kong startup combines 3D-printed reef tiles, biodiversity monitoring and long-term data to help companies manage their impact on marine ecosystems.
Updated
August 10, 2026 5:56 PM

Young corals growing on Archireef's 3D-printed terracotta reef tiles beneath the sea. IMAGE: ARCHIREFF
Anyone who has snorkeled over a coral reef has probably admired its vibrant colours and the marine life swimming between its branches. What is less visible is how easily these ecosystems can be damaged. Rising ocean temperatures and pollution continue to put reefs under pressure, while coastal development creates another threat. Construction can stir up sediment that settles on corals, blocking the sunlight they need and making it harder for damaged reefs to recover.
Protecting marine ecosystems is becoming a shared responsibility. Alongside scientists, governments and conservation groups, businesses whose operations affect the ocean are increasingly expected to understand, manage and reduce their environmental impact. They must also show regulators, banks and investors that they are meeting their environmental commitments.
Archireef helps businesses meet those demands. Founded by Vriko Yu, the Hong Kong-rooted B2B startup specializes in marine ecosystem restoration and ocean nature risk management. Drawing on years of research at the University of Hong Kong, Yu built the company to help organisations understand, measure and reduce their impact on marine ecosystems.
Yu describes Archireef as an “end-to-end ocean nature risk management company”.
“What we offer them is a credible way to meet those obligations and stand behind the results,” she says.
One of the company’s main tools for restoring damaged marine ecosystems is its flagship 3D-printed terracotta reef tile. The tiles provide a stable foundation where young corals can attach, grow and survive over time.
Archireef chose terracotta instead of concrete and other conventional materials because it is pH-neutral and does not release harmful chemicals into the water. Its surface also gives corals a suitable place to attach naturally.
Before placing a single tile in the ocean, the team studies the proposed restoration site to determine whether recovery is possible. It assesses the water quality, biodiversity and general health of the ecosystem. As Yu explains, restoration should begin only where nature has a realistic chance to recover.
“Restoration isn’t about replacing nature or engineering a reef into existence. It is about removing the barriers and giving a degraded system the conditions it needs to begin recovering on its own”, she says.
Once the team selects a site, divers carefully place the tiles on the seabed. Their curves, ridges and crevices imitate the structure of a natural coral reef, creating sheltered spaces for marine species. The design also helps limit sediment build-up, which can block sunlight and smother young corals.
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Archireef adjusts the shape of its reef tiles for each project.
“There’s no universal reef, so there’s no universal tile”, Yu says.
Instead of producing one standard model, the company adapts each design to the coral species, water conditions and surrounding marine environment. A coral restoration project in Hong Kong may therefore require a different tile from one in Saudi Arabia, even when the same manufacturing process is used.
“The biggest adaptation from site to site is usually the match between design, species and environment, not the manufacturing itself ”, Yu explains.

Although the reef tile is Archireef’s most recognizable innovation, Yu sees it as one part of a much broader service.
“The reef tile gets the attention because it’s tangible,” she says. “But the real product is the proof — defensible, audit-ready evidence of nature recovery that an organization can put in a disclosure and stand behind under scrutiny”.
Producing that evidence requires years of biodiversity monitoring. Long after the reef tiles have been installed, Archireef continues to track coral survival and the health of the surrounding marine ecosystem. Its monitoring methods include ecological surveys, AI-assisted species recognition, photogrammetry and environmental DNA testing.

Photogrammetry uses photographs to produce detailed 3D models of the reef. These models allow the team to measure changes in coral growth and reef structure over time.
Environmental DNA, commonly known as eDNA, offers another way to monitor marine biodiversity. Traditional ecological surveys often depend on divers recording the species they can see. eDNA testing instead examines traces of genetic material left in the water by marine organisms, including skin cells, mucus and waste.
By analyzing these traces, Archireef can detect species that may be hidden, difficult to identify or absent during a dive. This gives the company a more complete picture of the ecosystem and how it is changing.
For Archireef, the success of a coral reef restoration project is determined by what happens several years after installation.
“The indicators that matter aren’t the ones that look good on deployment day”, Yu says. “They’re the ones that show, two, three and five years on, whether a genuine ecosystem is establishing and sustaining itself”.
At the company’s first restoration site in Hoi Ha Wan, Hong Kong, around 90% of the transplanted corals remained alive four years after deployment. The long-term survival rate suggests that the ecosystem is recovering rather than simply appearing healthy during the early stages of the project.
Results like these have helped Archireef move beyond academic research and secure collaborations across the public and private sectors. In Hong Kong, the company has worked with government departments and public organisations responsible for coastal infrastructure and marine conservation.
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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.