Circles is using AI to turn telecom support from a cost centre into a faster, more personalised growth engine
Updated
May 1, 2026 2:04 PM
A woman holding a phone while using a laptop. PHOTO: ADOBE STOCK
Circles, a Singapore startup that builds software for digital telecom operators, has launched an AI concierge as part of its partnership with OpenAI. The release marks a new step in the company’s effort to modernise how telecom providers serve and retain customers. The move reflects a wider shift in the telecom sector. Many operators still rely on older support systems that can be slow, fragmented and costly to run. AI is now being tested as a way to improve service while creating new revenue opportunities.
Circles said the concierge is built on OpenAI’s API platform and sits within what it calls an AI-native telecom stack. In practical terms, the system is designed to handle customer support, account changes and personalised offers through automated interactions.
One part of the platform is called CareX. According to the company, it can deal with billing issues, service requests and network-related problems. Circles said CareX currently resolves 85% of customer queries globally without human intervention and reaches a 95% resolution rate on end-to-end tasks. That matters because customer support remains one of the larger operating costs for telecom providers. Faster automated handling could lower pressure on service teams while reducing wait times for users.
The second part of the platform is Xplore IQ, which focuses on revenue growth. The tool is designed to predict what a customer may need, recommend a suitable plan or offer and complete upgrades or downgrades automatically. Circles said the early rollout has led to a 22% rise in average revenue per user for Circles.Life Singapore. It also said personalised offers helped reduce customer churn by 9%.
"AI should empower users - not force-fit into outdated journeys. OpenAI's role has been critical in enabling Circles to scale this vision globally. With the AI concierge, we are moving beyond providing simple answers to delivering real-world outcomes, along with balancing cost and latency to maximize value for operators and customers alike", said Awais Malik, Global Chief Growth Officer at Circles.
"Circles is demonstrating how advanced AI can modernize essential industries like telecommunications at scale. By combining frontier models with multi-agent systems, they are enabling telecom operators globally to deliver faster, smarter and more personalized customer experiences. This milestone is a strong example of how AI can deliver tangible value for businesses and customers they serve", Oliver Jay, Managing Director, International for OpenAI, added.
Together, the tools are intended to connect customer service, operations and sales into one system. Rather than treating support and monetisation as separate functions, the company is combining them into a single digital layer.
Circles said the partnership will continue over the next two years as both companies work toward a more autonomous telecom model. Whether that vision is achieved remains to be seen, but the direction is clear: telecom operators are increasingly treating AI as core infrastructure rather than an optional add-on.
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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.