Xelix Raises $160 Million to Bring Agentic AI to Accounts Payable

Agentic artificial intelligence (AI) software firm Xelix has raised $160 million in new funding.

The company’s Series B round will help Xelix develop its platform and support more companies in adding AI to their finance operations, according to a Monday (July 21) news release.

“For too long, companies have relied on manual processes and basic systems to manage accounts payable and vendor risk,” Xelix said in a news release. “As a result, enterprises lose millions each year to overpayments, face increased fraud risks and suffer from bloated and burdensome manual workflows.”

With the need for better accounts payable (AP) controls in mind, Xelix says its platform integrates with companies’ systems to spot payment errors and fraud, automate supplier statement reconciliations and streamline AP helpdesk operations.

The release notes that companies including Astra Zeneca, GSK and Virgin Atlantic have used Xelix’s offerings to automate manual AP processes.

The company’s new funding round is happening as enterprises are increasingly using AI for their financial operations.

Research by PYMNTS Intelligence shows that a little more than a third of American chief financial officers (CFOs) at large enterprises were actively using AI in their AP programs. Another 43% are interested in integrating AI across AP but have yet to do so.

“Traditionally, the AP process has been reactive,” PYMNTS wrote in May. “An invoice arrives, it is reviewed, entered into an enterprise resource planning (ERP) system, matched with a purchase order, and scheduled for payment. It is a labor-intensive process prone to human error and delays.”

But as AI advances, AP is advancing with it, transforming from a “reactive cost center” to “a proactive, strategic force within the enterprise,” the report added.

At the same time, additional PYMNTS Intelligence research finds some reluctance among mid-market companies in adopting agentic AI. The reasons are both strategic and psychological, with 80% of high-automation enterprises pointing to data security and privacy as their top concern with agentic AI.

“While the technological potential is enormous, the readiness of systems (and humans) is far less clear,” LYMNTS wrote earlier this month.

“For AI to take action autonomously, executives must trust not just the output, but the entire decision-making process behind it. That trust is hard to earn — and easy to lose.”

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