Rentberry, a website which runs rental auctions, will begin using machine learning to analyse local rental market data within the coming weeks as it expands in the US.
The website lets landlords set a preferred rent which prospective tenants then bid on to try and get a lower figure.
The site claims it will use technology to help landlords set more reasonable prices and also rate would-be tenants based on their information within the system.
“People say we create competition, but competition already exists,” Rentberry chief executive Alex Lubinsky told the BBC.
He claims that of the 4,000 New York properties listed on the site many will go within four to five days in the current “hot market” and that properties tend to go for less than the landlord asking price.
“We compared the data on the rental platforms in US for the largest cities (including New York and Miami) and at this moment the final rental price on Rentberry is 4.3% lower than on other sites,” he said.
The platform currently has around 100,000 properties and more than 50,000 users and allows landlords to see both the bids and information on the bidders, including their credit score.
Rentberry claims the system is better for tenants as it encourages a more transparent renting process.