It’s long been a complaint of homebuyers. They can find home listings, compare prices and research neighborhoods on their own. Yet a sale often still results in tens of thousands of dollars in commissions to an agent who came in to help close a deal.
On a $1 million home, for example, a 6% fee split between the buyer’s and seller’s agents amounts to $60,000.
For Arman Javaherian, who spent six years at Zillow, that disconnect became the reason to start a company.
“The way most people buy a home has not changed in forty years despite the tremendous growth of technology, and I watched that up close at Zillow,” he told This Week in Fintech in an interview.
As a senior director of product, Javaherian’s team built Zillow’s Premier Agent service, connecting homebuyers with agents who paid to reach potential customers. In conversations with hundreds of buyers, he relates that he repeatedly heard the same frustration. They found homes and did much of the research themselves, while agents collected sizable commissions. Some buyers didn't even realize how much their agents would get paid until closing.
“You tour on someone else’s schedule, you take advice from someone paid more when you spend more,” Javaherian said, “and then you hand over tens of thousands of dollars at the closing table for work you largely did yourself.”
Now, his startup, Homa, has raised $5 million in seed funding for a service that uses AI and licensed agents to help people buy homes, then returns part of the buyer’s agent commission at closing, it shared with This Week in Fintech exclusively.
Quiet Capital led the round, joined by Restive Ventures and Cambrian Ventures. Homa already operates in Florida, California and Texas, and the money will help fund its geographic expansion and the launch of a new mortgage business.
The startup began generating revenue in April, and revenue grew sixfold over its first six months, according to Javaherian. Homes purchased through the company have ranged from $150,000 to $2.4 million.
The company has returned nearly $1.5 million to buyers to date, Javaherian said. The average credit is about $10,560, he added.
Image credit: Homa; Co-founders Arman Javaherian (CEO) and Federico Campeotto (CTO)
Changing the model
Javaherian, whose career also included roles at Crunchbase and the software startup Shortcut, began developing the idea for Homa after the National Association of Realtors’ 2024 settlement over broker commissions.
That settlement requires participating agents to sign written agreements with buyers before touring homes together. Those agreements spell out the agent’s services and pay. Commissions have always been negotiable. To be clear, the settlement did not establish or abolish a fixed 6% rate.
Javaherian believed that discussing fees earlier would make more buyers question what they were paying for.
So in 2024, he teamed up with Federico Campeotto, Homa’s chief technology officer, to build out an offering that would give homebuyers a way to purchase homes without paying as much out in commissions. Campeotto has a doctorate in computer science specializing in AI and previously worked at AppFolio, where he helped develop AI systems for communication between property managers and renters, noted Javaherian.
Homa’s first version used AI to help people buy homes without their own real estate agent. But that approach ran into resistance from agents representing sellers.
Some refused to work with buyers without an agent, citing liability concerns, Javaherian said. Others sought to keep the commission that otherwise would have gone to the buyer’s agent. He said some sellers’ contracts allowed their agents to keep both portions if the buyer had no agent.
At that point, Homa obtained a brokerage license and began representing buyers itself.
The company charges 1% of the home’s purchase price, subject to a minimum fee, and returns the rest of the buyer’s agent commission to the customer as a credit at closing. How much a buyer receives depends on the commission the seller agrees to pay.
On a $1 million home with a 3% buyer’s agent commission, for example, Homa would receive $30,000. It keeps $10,000 and gives the buyer a $20,000 credit.
From showing to closing
Rather than have one agent handle every aspect of a real estate transaction, Homa divides the work. There are agents who show homes, agents who negotiate purchases and staff who handle the paperwork and deadlines needed to complete a sale.
Buyers wanting to see a property pick a desired date and time. Homa sends that request to its network of real estate agents. Whichever agent accepts the request first arranges the visit and meets the buyer at the property. The agents receive a set payment for each showing. Some work for other brokerages and take Homa assignments on the side. They receive no commission if the buyer makes an offer and purchases a home.
The approach gives buyers the opportunity to see several homes in a day without being dependent on one agent’s schedule.
“You can see six different homes on Saturday with six different agents,” Javaherian said.
To help buyers assess how much a home might be worth, Homa uses AI to compare a home with similar properties. It then suggests an offer price and determines how much room a buyer may have to negotiate. Buyers can also upload inspection reports, seller disclosures and condominium rules for analysis.
Once a buyer is ready to make an offer, a licensed Homa agent prepares it and handles negotiations. These agents are independent contractors and are paid a flat fee when a purchase closes, regardless of the home’s price.
That sort of payment structure removes the incentive to push a buyer toward a more expensive home, noted Javaherian. It also lets agents handle more purchases because they do not spend time driving to showings or looking for customers.
“Those in-house agents each have a minimum of 10 years of experience and a minimum of 200 closed transactions. They don’t have to do the showings. They don’t have to run around,” he said. “They don’t have to go and look for leads and look for new buyers…all they do is negotiate all day long.”
One Florida agent handled 18 transactions last month, according to Javaherian.
“A typical licensed agent basically does an average of five and a half transactions per year,” Javaherian said. “Our agents are able to do 250 transactions a year each.”
About half of Homa’s customers come through paid advertising and half through sources such as news coverage and referrals, he said. Referrals account for a growing share of buyers in Florida, where Homa has operated the longest.
Adding mortgages
For some buyers, the credit can help cover an expense they didn't fully anticipate, like closing costs, Javaherian said. Applying the credit to those costs can help them move forward.
Buyers can also use their Homa credit to pay upfront for a lower mortgage interest rate. That option could reduce a borrower’s rate by as much as three-quarters of a percentage point in some cases, depending on the loan and its terms, Javaherian said.
The company’s planned mortgage business will arrange loans through outside lenders and earn money from those loans. By offering mortgages to existing homebuyers, Homa can avoid some advertising and other expenses associated with finding borrowers, Javaherian said.
The startup plans to show mortgage rates alongside home listings, including what the rate would be if a buyer applied the credit toward lowering it.
The new funding will also support a mobile app planned for later this year. Beyond its California launch, Homa intends to expand into more states after raising a Series A, which Javaherian hopes to pursue in the first half of next year.
Michael Bloch, partner at Quiet Capital and an early investor in OpenAI and Reddit, told This Week in Fintech via email that real estate is a massive market but yet “the basic transaction model hasn’t meaningfully changed in decades.”
“That creates a huge opening for a company like Homa, which is rethinking not just the cost structure, but the entire homebuying experience,” he said.
The startup, in Bloch’s view, gives a clear picture of what homebuying will look like in the future.
“Buyers won’t need to depend on one agent for every step of the process. They’ll have technology doing the heavy lifting and on-demand human help when they need it, leading to a much faster path from search to close,” he said.
