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 7, 2026 4:10 AM
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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A new AI model replaces months of simulation with near-instant predictions, changing how spacecraft operations are prepared
Updated
April 24, 2026 10:53 AM
Northrop Grumman Stargaze serves as the mother ship for the Pegasus, an air-launched orbital rocket. PHOTO: UNSPLASH
Flexcompute, a startup that builds software to simulate real-world physics, is working with Northrop Grumman to change how space missions are prepared. Together, they have developed an AI-based system that can predict how spacecraft respond during critical manoeuvres such as docking—when one spacecraft moves in and connects with another in orbit. These steps have traditionally taken months of preparation.
At the centre of this work is a long-standing problem in space operations. When a spacecraft fires its thrusters, the exhaust plume interacts with nearby surfaces. These interactions can affect movement, temperature and stability. Because these effects are difficult to test in real conditions, engineers have relied on large volumes of computer simulations to estimate outcomes before a mission. That process is slow and resource-intensive.
The new system replaces much of that workflow with a trained AI model. Instead of running millions of simulations, the model learns patterns from physics-based data and can make predictions in seconds. It also provides a measure of uncertainty, which helps engineers understand how reliable those predictions are when making decisions.
"At Northrop Grumman, we're pioneering physics AI to accelerate design and solve complex simulation and modelling problems like plume impingement—critical for station keeping, rendezvous and space robotics. Simply put: we're pushing the boundaries of advanced space operations", said Fahad Khan, Director of AI Foundations at Northrop Grumman. "Partnering with Flexcompute and NVIDIA, we're accelerating innovation and mission timelines to deliver superior space capabilities for customers at the speed they need".
The system is built using technology from NVIDIA, which provides the computing framework behind the model. Flexcompute has adapted it to handle the specific challenges of spaceflight, including how gases expand and interact in a vacuum. The result is a tool that can simulate complex scenarios much faster while maintaining the level of accuracy needed for mission planning.
By shortening preparation time, the model changes how engineers approach spacecraft design and operations. Faster predictions mean teams can test more scenarios and adjust plans more quickly. It also helps improve fuel use and extend the lifespan of spacecraft.
"Northrop Grumman's confidence reflects what sets Flexcompute apart", said Vera Yang, President and Co-Founder of Flexcompute. "We are able to take the most accurate and scalable physics foundations and evolve them into highly trained, customized Physics AI solutions that engineers can rely on. This work shows how we are transforming the role of simulation, not just speeding it up, but expanding what engineers can confidently solve and how quickly they can act".
The collaboration points to a broader shift in how engineering problems are being handled. Instead of relying only on detailed simulations that take time to run, companies are beginning to use AI systems that can approximate those results quickly while still reflecting the underlying physics.
"The industry's most ambitious space missions now demand a level of speed and precision that traditional engineering cycles can no longer sustain", said Tim Costa, vice president and general manager of computational engineering at NVIDIA. "By integrating NVIDIA PhysicsNeMo, Northrop Grumman and Flexcompute are transforming complex simulations like plume impingement from days of compute into seconds of insight, drastically accelerating the path from mission concept to orbit".
What emerges from this work is a shift in how missions are prepared. When prediction cycles move from months to seconds, testing and decision-making can happen faster. For space operations, where timing and precision are closely linked, that change could reshape how systems are built and run.