How ECOPEACE uses autonomous robots and data to monitor and maintain urban water bodies.
Updated
January 23, 2026 10:41 AM
A school of fish swimming among debris and waste. PHOTO: UNSPLASH
South Korea–based water technology company ECOPEACE is working on a practical challenge many cities face today: keeping urban water bodies clean as pollution and algae growth become more frequent. Rather than relying on periodic cleanup drives, the company focuses on systems that can monitor and manage water conditions on an ongoing basis.
At the core of ECOPEACE’s work are autonomous water-cleanup robots known as ECOBOT. These machines operate directly on lakes, reservoirs and rivers, removing algae and surface waste while also collecting information about water quality. The idea is to combine cleaning with constant observation so changes in water conditions do not go unnoticed.
Alongside the robots, ECOPEACE uses a filtration and treatment system designed to process polluted water continuously. This system filters out contaminants using fine metal filters and treats the water using electrical processes. It also cleans itself automatically, which allows it to run for long periods without frequent manual maintenance.
The role of AI in this setup is largely about decision-making rather than direct control. Sensors placed across the water body collect data such as pollution levels and water quality indicators. The software then analyses this data to spot early signs of issues like algae growth. Based on these patterns, the system adjusts how the robots and filtration units operate, such as changing treatment intensity or water flow. In simple terms, the technology helps the system respond sooner instead of waiting for visible problems to appear.
ECOPEACE has already deployed these systems across several reservoirs, rivers and urban waterways in South Korea. Those projects have helped refine how the robots, sensors and software work together in real environments rather than controlled test sites.
Building on that experience, the company has begun expanding beyond Korea. It is currently running pilot and proof-of-concept projects in Singapore and the United Arab Emirates. These deployments are testing how the technology performs in dense urban settings where waterways are closely linked to public health, infrastructure and daily city life.
Both regions have invested heavily in smart city initiatives and water management, making them suitable test beds for automated monitoring and cleanup systems. The pilots focus on algae control, surface cleaning and real-time tracking of water quality rather than large-scale rollout.
As cities continue to grow and climate-related pressures on water systems increase, managing waterways is becoming less about occasional intervention and more about continuous oversight. ECOPEACE’s approach reflects that shift by using automation and data to address problems early and reduce the need for reactive cleanup later.
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Backed by Menlo Ventures, BrainGrid tackles planning gaps as AI makes software building accessible to more founders.
Updated
April 1, 2026 8:37 AM
A phone screen with app icons. PHOTO: UNPSLASH
As artificial intelligence makes it easier to write code, a different problem is starting to surface. Building software is no longer limited by technical skill alone. Increasingly, the challenge lies in deciding what to build, how to structure it, and how to turn an idea into something that actually works.
That shift sits at the centre of BrainGrid, a startup that has raised $1 million in pre-seed funding led by Menlo Ventures, with participation from Next Tier Ventures and Brainstorm Ventures. The company is building what it describes as an AI-powered planning layer for people who want to create software but may not have a technical background.
The timing reflects a broader change in how products are being built. Tools like Claude Code and Cursor have made it possible to generate working code through simple prompts. For many first-time founders, this has lowered the barrier to entry. But writing code is only one part of the process. Turning that code into a reliable product requires structure, sequencing and clarity—areas where many projects begin to fall apart.
In traditional teams, this responsibility sits with product managers who define what needs to be built and in what order. Without that layer, even well-written code can lead to products that feel disjointed or incomplete. Features may not work together, integrations can break and the final product often does not match the original idea.
BrainGrid is designed to address that gap. Instead of focusing on generating code, it helps users map out the structure of a product before development begins. The aim is to give builders a clearer starting point so that the tools they use—whether human or AI—can produce more consistent results.
The company says more than 500 builders have already used it to create software products across areas like fitness, healthcare and productivity. These range from first-time founders experimenting with new ideas to experienced developers working independently. In many cases, the products are already live and generating revenue, suggesting that the demand is not just for experimentation but for building something that can scale.
For investors, the appeal lies in the evolving role of software development. As AI takes on more of the technical work, the value shifts toward defining the problem and structuring the solution. In that sense, planning becomes less of a background task and more of a core capability.
The US$1 million raise is relatively modest, but it points to a larger trend. As more people gain access to AI tools, the number of potential builders expands. What remains limited is the ability to organise ideas into products that work in the real world. If that shift continues, the next wave of software may not be defined by who can code, but by who can plan.