The automated accounts payable and invoicing platform Tradeshift has secured more than $200 million in funding and debt from a group of investors that included Koch Industries.
The San Francisco company announced the funding in an emailed news release Thursday (Dec. 9), saying it would use the capital to optimize its growth and balance sheet as it scaled its business.
“Tradeshift’s unique, open network model is transforming the way B2B buyers and suppliers find, connect and transact with one another,” the company said.
“The additional backing from experienced and committed investors secures the path for Tradeshift to accelerate product development and network growth, reinforcing the company’s standing as the leading B2B commerce platform with embedded FinTech services,” Tradeshift wrote.
One of those investors, Jeff Randsell of Fuel Venture Capital Partners, said Tradeshift’s combination of Software-as-a-Service (SaaS) offering and embedded financial services represent “the next wave of digital transformation” and “the future of B2B software.”
Tradeshift says it recently logged more than $1 million in transactions through its network, double the amount from two years ago.
Annual charge volumes through the company’s card program Tradeshift Go are projected to top $2.5 billion for the year, a 600% increase since last year.
“Embedding financial services directly into our product unclogs the flow of working capital across supply chains, eliminating a significant pressure point in the buyer-suppliers relationship,” said Christian Lanng, CEO and co-founder of Tradeshift.
“As one of the first companies to recognize the potential for embedded finance in SaaS, we have been betting on the convergence of FinTech and SaaS products for a while. We’ve built the technology and distribution channels to capitalize on what is now one of the defining trends in our industry,” Lanng said.
Read more: Tradeshift: AI Updates Demonstrate Value Of Automated AP Systems
In June, Tradeshift upgraded its artificial intelligence (AI) tools, including a new feature on its platform to help companies forecast whether tasks would be more efficient carried out by computers or humans.
“We don’t believe in building ‘black box’ technology,” Lloyd Humphreys, the company’s principal product manager for analytics and artificial intelligence, said at the time. “Trusting machine learning with something as important as ensuring your company’s suppliers get paid is not something that should be done behind a curtain.
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