Proptech Startup PredictAP Raises $8M Series A for Expansion
Real estate accounts payable software company to grow in U.S. and internationally
Accounts payable is not the most exciting part of business, but PredictAP, a machine learning-enabled software startup that automates the function for real estate companies, has attracted investor excitement. On Wednesday, the company announced it closed an $8 million Series A financing round.
Boston-based PredictAP was developed as a fintech solution to automate the ingestion and coding of invoices for real estate accounting departments, said company CEO David Stifter, who founded PredictAP in 2020 with Russell Franks.
“My background was at a company called Colony Capital as a managing director leading business technology,” said Stifter. “This was a real-world problem around the payable process that as a big company kind of brought us to our knees. We realized that there wasn’t really a good solution in the market. PredictAP came out of that.”
PredictAP will use the new funding to develop additional software resources, he said.
Starting with the co-founders’ personal investments, as well as those of friends and family, PredictAP quickly realized that to solve the hurdles of early ingestion and the cutting of invoices for real estate, they would need more funding to create the artificial intelligence and machine learning to meet customer demand.
“The nice thing about AI is that it definitely is a great tool to achieve things, but the negative is it takes a lot of very talented people to make this stuff happen,” Stifter said. “So the primary use of this money is for engineers to help us get better at solving our core problem — engineering, customer support, and customer success.”
The fresh funding will be put to ready use.
“As we proved out our product market fit, we got customers up from five to 10, finishing last year with about 50 customers,” said Stifter. “The demands of keeping 50 customers happy, all the work you have to do around customer support, and also continuing to expand, you need to have capital, which is the lifeblood of any startup.”
That realization led PredictAP to seek its Series A funding, which was difficult during a lending drought, particularly in proptech, Stifter said.
“We have been doing some fundraising here and there, but the market has become dramatically different from two years ago versus a year ago versus now,” he said. “The path is much, much more narrow, and the amount of diligence and the amount of vetting you have to do is a whole lot more. So it’s been interesting seeing how at the start we had to turn people away with money, to now where you really have to prove yourself to raise funds in today’s market.”
Large real estate companies receive thousands of invoices a month, each of which has to be coded through a minutes-long process that requires manual data entry. PredictAP developed an AI-based software that leverages historical invoice data to code new invoices, after which the company says an accounting professional can confirm the information in seconds.
Since its launch, PredictAP has grown its user base, with the company now supporting companies that jointly process more than 2 million invoices per year, including real estate customers such as Bridge Investment Group, Garden Homes, The RMR Group, Starwood and CA Ventures.
“PredictAP’s powerful technology is one of the most successful uses of artificial intelligence that we’ve seen in the real estate sector, and the impact it is already having is immediately apparent to its users,” RET Ventures partner John Helm said in a statement. “The company was an exceptional investment opportunity because of its accelerated sales cycle. The firm goes through the sales process, closing, and technology deployment as quickly as any company we’ve seen. With approximately a billion invoices being processed globally each year, PredictAP is still in the early stages of its growth trajectory, and we’re excited to support the company as it scales in the years ahead.”
Philip Russo can be reached at firstname.lastname@example.org.