Embedded payments platform Payabli has closed on a $28 million Series B funding round.
The new funding comes just nine months after Payabli raised its Series A led by QED Investors bringing the total capital in the company to date to $60,000,000. The Series B is led by Fika Ventures and QED Investors with participation from existing investors TTV Capital and Bling Capital.
California-based Payabli provides a single unified API to allow software developers to create any payment experience they need for acceptance and issuance of money, as well as operational tools to manage the tactical needs of a payments company. This includes vertical-specific capabilities that lend themselves to certain “Need-to-Pay” businesses, like property management, utilities, education, and government.
Over the past year, the company has posted a 7x year-over-year increase in revenue and surpassed 50,000 merchants on its platform.
Joseph Elias Phillips, co-founder and Co-CEO of Payabl, says the new funding will be directed to product development, with a focus on AI-driven features.
“We’re fortunate to be experiencing rapid growth at a time when AI is poised to revolutionize the financial services industry," he says. "When our investors approached us about doubling down on Payabli, we saw a clear opportunity to go on the offensive by accelerating AI enablement across our platform and organization to drive further growth and bring groundbreaking new products and capabilities to market faster.”
Payabli recently launched Amigo, its first AI-powered support agent, now available through the company’s technical documentation, web platform, and natively within Slack. Amigo delivers a wide range of functionality, from acting as a solution engineer that helps software companies integrate faster, to serving as a support representative that resolves tickets quickly, to functioning as a business analyst that assists software partners with reporting and analytics through a user-friendly, chat-based interface.
In parallel, Payabli is working with Nvidia to develop advanced risk and fraud detection models trained on proprietary customer data to deliver tailored risk assessments specific to each customer’s business and industry.