PredictAP, a machine-learning enabled invoice capture solution for real estate accounts payable (AP), announced the close of its successful preferred funding round. The $3.4 million raised from real estate industry veterans includes conversion of a $600,000 note raised in August 2020 to kick off development work and file provisional patents related to novel use of machine learning to solve invoice coding, and now to bring PredictAP to market in Q2 2021.
PredictAP is the first and only invoice capture solution designed for real estate AP. Powered by machine learning, PredictAP leverages historical invoice data to rapidly and accurately code new invoices, resulting in improved AP efficiency, faster payment cycle times and reduced AP related costs.
“The real estate industry processes millions of invoices each year,” says PredictAP co-founder David Stifter. “The staggering amount of manual work required to do this is a massive drain on resources. The backing of so many industry veterans reinforces the fact we are solving a real and pressing problem.”
Real estate-specific AP automation platforms like Yardi Payscan and Nexussytems have seen increasing adoption by the industry, but generally focus on managing review and approval workflows once an invoice has been captured.
Traditionally invoice capture and coding is still done manually by a company’s in-house AP team even after they have implemented an AP automation platform. PredictAP has been built from the ground up as a state-of-the-art SaaS solution designed to complement the AP automation platforms that are already transforming the AP process across the real estate industry.
President and co-founder Russell Franks outlines PredictAP’s future plans. “As we prepare to go to market in Q2 2021, we wanted to launch with a scalable solution that was truly cloud-first and felt ready to deliver on our promise to our customers,” he says. “We will be expanding our team, bolstering our infrastructure, and taking the leading position in the invoice capture space.”