Antom, a merchant payment and digitisation services provider under Ant International, today announced major upgrades to Antom Copilot, its AI agent designed for merchant payment and operations management.

Integrated into the Antom Merchant Portal, Antom Copilot now provides enhanced automation and tailored assistance based on learnings from real-world cases, to help merchants handle payment complexity more efficiently.

Main features include:

• Agentic support for entire payment lifecycle, from onboarding and integration, to dispute handling, risk control and payment success rate operation;
• Domain-trained intelligence functions like a virtual team of payment experts to manage traditionally resource-intensive processes with shorter processing time and less costs;
• Better resolution performance in real, multi-step operational scenarios, supported by improved multi-turn dialogue and memory capabilities;
• Closer monitoring of operational signals enables the pre-emptive capture of risks and opportunities, rather than waiting for merchants to raise issues.

As a result, Antom Copilot is able to learn each merchant’s business rhythm and deliver proactive and nuanced advice across their payment-related operations.

“Managing payments doesn’t have to be a passive and low ROI process of solving problems for merchants,” said Gary Liu, CEO of Antom, Ant International. “Today, our goal is to put advanced AI efficiency tools at the fingertip of every merchant in daily operations at lower cost, turning what large enterprises achieve through dedicated teams into accessible tools for all.”

Recently, Antom also launched EPOS360, an AI-powered app bringing together point-of-sale (POS) system, payments, banking, lending, and growth support together to help SMEs move from setup to scale efficiently.

“Ant International is focusing on building domain-specific agentic AI that solves global payment complexity for merchants,” said Jiangming Yang, Chief Innovation Officer, Ant International. “We train and tune AI agents using deep industry know-how and a large set of anonymized complex cases, and evolve new agent protocols to ensure agents solve tasks in efficient orchestration.”