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"AI should empower users - not force-fit into outdated journeys.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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A step forward that could influence how smart contracts are designed and verified.
Updated
January 8, 2026 6:32 PM
ChainGPT's robot mascot. IMAGE: CHAINGPT
A new collaboration between ChainGPT, an AI company specialising in blockchain development tools and Secret Network, a privacy-focused blockchain platform, is redefining how developers can safely build smart contracts with artificial intelligence. Together, they’ve achieved a major industry first: an AI model trained exclusively to write and audit Solidity code is now running inside a Trusted Execution Environment (TEE). For the blockchain ecosystem, this marks a turning point in how AI, privacy and on-chain development can work together.
For years, smart-contract developers have faced a trade-off. AI assistants could speed up coding and security reviews, but only if developers uploaded their most sensitive source code to external servers. That meant exposing intellectual property, confidential logic and even potential vulnerabilities. In an industry where trust is everything, this risk held many teams back from using AI at all.
ChainGPT’s Solidity-LLM aims to solve that problem. It is a specialised large language model trained on over 650,000 curated Solidity contracts, giving it a deep understanding of how real smart contracts are structured, optimised and secured. And now, by running inside SecretVM, the Confidential Virtual Machine that powers Secret Network’s encrypted compute layer, the model can assist developers without ever revealing their code to outside parties.
“Confidential computing is no longer an abstract concept,” said Luke Bowman, COO of the Secret Network Foundation. “We've shown that you can run a complex AI model, purpose-built for Solidity, inside a fully encrypted environment and that every inference can be verified on-chain. This is a real milestone for both privacy and decentralised infrastructure”.
SecretVM makes this workflow possible by using hardware-backed encryption to protect all data while computations take place. Developers don’t interact with the underlying hardware or cryptography. Instead, they simply work inside a private, sealed environment where their code stays invisible to everyone except them—even node operators. For the first time, developers can generate, test and analyse smart contracts with AI while keeping every detail confidential.
This shift opens new possibilities for the broader blockchain community. Developers gain a private coding partner that can streamline contract logic or catch vulnerabilities without risking leaks. Auditors can rely on AI-assisted analysis while keeping sensitive audit material protected. Enterprises working in finance, healthcare or governance finally have a path to adopt AI-driven blockchain automation without raising compliance concerns. Even decentralised organisations can run smart-contract agents that make decisions privately, without exposing internal logic on a public chain.
The system also supports secure model training and fine-tuning on encrypted datasets. This enables collaborative AI development without forcing anyone to share raw data—a meaningful step toward decentralised and privacy-preserving AI at scale.
By combining specialised AI with confidential computing, ChainGPT and Secret Network are shifting the trust model of on-chain development. Instead of relying on centralised cloud AI services, developers now have a verifiable, encrypted environment where they keep full control of their code, their data and their workflow. It’s a practical solution to one of blockchain’s biggest challenges: using powerful AI tools without sacrificing privacy.
As the technology evolves, the roadmap includes confidential model fine-tuning, multi-agent AI systems and cross-chain use cases. But the core advancement is already clear: developers now have a way to use AI for smart contract development that is fast, private and verifiable—without compromising the security standards that decentralised systems rely on.