Modern Treasury Debuts AI Platform for B2B Payments

Modern Treasury has introduced what it calls the first artificial intelligence (AI) platform purpose-built for enterprise payments.

Modern Treasury AI, announced by the payments operation platform Thursday (May 1), features an artificial intelligence (AI) agent designed to meet the needs of payment operations.

The agent, unlike generic large language models or probabilistic AI tools, “is auditable by design” and delivers results based on “existing connectivity and a deep understanding” of how enterprise payment systems and workflows operate, the company said in a news release.

“AI is only as good as the data, and Modern Treasury is uniquely positioned to deliver the first AI capabilities with relevant payments context,” said Sam Aarons, Modern Treasury’s co-founder and chief technology officer.

“We see the full payment lifecycle,” he added. “We see the metadata, the reconciliation logic, the exceptions, and the outcomes. No one else has a contextualized dataset of trillions of datapoints on enterprise payments or the expertise in navigating them. Modern Treasury has the deepest, real-world understanding of how payments work, and that data foundation allows us to offer a powerful new experience for users.”

PYMNTS explored the use of agentic AI in payments — and how the technology could be harnessed — last month in a conversation with TerraPay Co-founder and Chief Operating Officer Ram Sundaram.

“In financial services, you can’t take chances on technology like this, which has the freedom to go wrong,” he said. “You have to be careful about making sure that it’s 100% reliable before we can let things run entirely by automation.”

Agentic AI also remains costly. For example, OpenAI charges $20,000 a month for its specialized agents. But Sundaram argued the industry will quickly become commoditized, which will bring down prices. In addition, some open-source offerings are capable, he added.

“There’s a fire hose of news about breakthroughs and new ideas and new ways of doing things that are coming out on a daily basis,” Sundaram said.

Data is at the center of it all, and Sundaram told PYMNTS that no matter what the application, the information presented the models needs to be clean. Most organizations have an array of data in different intra-company silos, and those silos have to be torn down.

In addition, the data should be accessible and able to be synthesized by the models. Many companies subscribe to more than 1,000 software-as-a-service (SaaS) resources without accurately tracking or monitoring them.

“Every database is separated, each one sitting somewhere else,” he said.