Astrada Raises $3.8 Million to Expand Autonomous Finance Offering

Autonomous finance data layer Astrada has raised $3.8 million in new funding.

The company’s seed round, announced Wednesday (May 6), was led by Bain Capital Ventures, QED Investors and Nyca Partners, with participation from Visa and Mastercard. The company says the funding will help boost product development and expand partnerships in the FinTech and enterprise finance worlds.

“As businesses increasingly adopt AI agents to manage financial workflows, the need for a unified, real-time data layer has become critical,” the company said in a news release. “Astrada sits at the center of this shift, giving finance platforms the infrastructure to support both human-driven and agent-driven spending at scale.”

Launched in 2024, Astrada says it has processed more than $750 million in card spend and 3 million-plus transactions across all three major card networks via a single API. Customers include Workday, Zoho, Payhawk and Miter.

“Finance is moving from manual to autonomous — and the infrastructure hasn’t kept up,” Astrada founder and CEO Salman Syed said. “We built Astrada to be the real-time data layer that finance platforms need as they evolve to support AI agents alongside human users.”

In other agentic AI news, PYMNTS wrote last week about the “possibilities of fully autonomous financial workflows” as invoices and contracts become machine-readable.

AI agents, that report said, can negotiate terms within predefined parameters, carry out transactions based on real-time conditions and enforce agreements with no human involvement.

“For CFOs, this represents an opportunity to reduce cycle times, improve cash flow visibility and minimize disputes,” PYMNTS added. “But it also requires a willingness to rethink long-standing processes and invest in data infrastructure.”

If AI agents are going to be executing contracts, those agreements must be designed for machine readability, the report said, with key elements like pricing models, payment schedules, service-level agreements and termination conditions explicitly defined in standardized formats.

“Ambiguity, while sometimes useful in human negotiations, becomes a liability when machines are tasked with execution,” PYMNTS said.

A similar transformation is happening with invoices, as these documents become “real-time signals within a continuous financial workflow” in an AI-focused environment.

The report also cites PYMNTS Intelligence research showing that “as agentic AI systems mature, descriptions optimized for human persuasion, like rich imagery, narrative copy and lifestyle framing, must be complemented by precise, unambiguous metadata, like specifications, dimensions, compatibility, warranties, return policies and availability in consistent formats.”