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Homa's AI Platform Modernizes Home Buying Process




“Many home buyers we interviewed struggled to understand the necessity of working with a buyer’s agent,” says Arman Javaherian, CEO and Co-Founder of Homa. “They understood the role of a seller’s agent on the listing side, but questioned the need for a buyer’s agent.”
This observation, gained during Javaherian’s six-year tenure at Zillow and Trulia, combined with the landmark NAR settlement that now requires buyer’s agents to disclose their commissions directly to clients, sparked the creation of Homa, an AI-powered platform designed to guide homebuyers through the purchasing process without necessarily requiring a traditional buyer’s agent.
The NAR Settlement: A Catalyst for Change
When the NAR settlement was announced last year, Javaherian recognized a pivotal moment in the industry. For the first time, because homebuyers now have to sign a contract with buyer’s agents, this cost is going to be visible to them. “It’s going to be right in their face,” he notes. “This visibility is something that never existed before.”
The settlement created transparency around buyer’s agent commissions—often 2-3% of a home’s purchase price—making consumers more aware of costs they previously didn’t see. “I thought, if I was a homebuyer, I’d take a step back and ask: What other paths are there that don’t require spending $20,000 to $40,000 on a buyer’s agent?” Javaherian explains.
From Zillow Insider to Disruptor
Javaherian’s journey to founding Homa was shaped by his extensive experience in real estate technology. During his time at Trulia and later Zillow (following their acquisition), he led the team responsible for the Zillow Premier Agent app, growing it to approximately 50,000 daily users.
“At Zillow, we operated at the intersection connecting hundreds of thousands of Premier agents with tens of millions of home buyers every month,” Javaherian explains. This vantage point gave him unique insights into the challenges homebuyers face.
This realization prompted him to leave his position at Shortcut, a project management startup, in May 2023 to develop Homa. After creating a proof of concept in late 2024 that attracted investor interest, Javaherian and his team built and launched the current version of Homa in early 2025.
An AI-First Approach to Home Buying
Homa distinguishes itself as an AI-first company, leveraging artificial intelligence to guide users through every step of the home buying process. Javaherian’s co-founder, who holds a PhD in computer science with a focus on AI, has helped build a platform that uses machine learning to analyze properties, suggest offer prices, and interpret complex disclosure documents.
Rather than attempting to replace property search platforms like Zillow or Redfin, Homa focuses on the next steps after a buyer identifies a property of interest. Most people are satisfied with their current property discovery tools, Javaherian explains. If they’re using Zillow, they don’t want to leave Zillow.
Instead, Homa’s workflow begins when a user inputs a property they’re interested in and guides them through:
- Property Analysis: The platform uses AI to assess the property’s value, analyze comparable sales, and determine the buyer’s bargaining power.
- Tour Scheduling: Users can request tours directly from listing agents or use Homa’s partnership with Showami, a showing service that charges approximately $50 per showing.
- Offer Price Determination: Homa’s algorithm pulls comparable properties and suggests offer prices based on market conditions, price changes, and property-specific factors.
- Disclosure Review: The platform can analyze disclosure documents—even handwritten ones—to identify potential issues and extract key information.
- Offer Generation: A TurboTax-style interface walks users through creating an offer in 10-15 minutes, generating official contracts ready for signing.
- Escrow Management: Task-based guidance helps buyers navigate the escrow process.
Throughout this journey, users can interact with Homa’s AI assistant, which provides personalized responses based on the specific property and stage of the process.
Listing Agent Friendly
While Homa aims to reduce reliance on buyer’s agents, Javaherian emphasizes that the platform is very listing agent friendly.
“Unlike Zillow and other sites that hide the listing agent information, we actually encourage our buyers to interact with the listing agent,” he explains. “We want them to approach the listing agent because we know that’s the best way, and often, they can get that deal done.”
This approach recognizes that while some listing agents may be cautious about working with unrepresented buyers, many see it as an opportunity.
Real Estate Investors: Early Adopters
The platform has found particular traction with real estate investors, who appreciate its data-driven approach. “Unlike regular home buyers who can get very emotional about properties, real estate investors are not emotional,” Javaherian observes. “They simply want a platform that helps them analyze the numbers.”
Some investors have added dozens of properties to Homa to analyze them efficiently, and the company plans to add more features specifically for this community. “Real estate investors are very conscious about 2-3% here and there,” Javaherian notes. “Being able to save on the buyer’s agent commission can really differentiate one investment property from another.”
Addressing Affordability Challenges
Beyond convenience and cost savings, Homa aims to address a fundamental challenge in the housing market: affordability.
“A significant portion of the population currently cannot access homeownership because they struggle with the down payment,” Javaherian explains. “The average down payment for many buyers is about 6%, so a 3% buyer’s agent fee represents half of their down payment.”
By potentially eliminating this fee, Homa hopes to help more people enter the housing market.
The Future of Real Estate Professionals
When asked about the evolving role of real estate agents, Javaherian sees a clear distinction between the buy and sell sides of transactions.
“Realtors provide the most value on the sell side,” he argues. “When you’re selling a home, it requires someone with taste to help market that property properly—someone who knows you need certain types of photos, staging, and the right furniture. There are numerous elements to effectively presenting that home.”
He also notes the liability considerations for sellers, who need to ensure disclosures are complete and accurate.
On the buy side, however, Javaherian believes technology can empower home buyers willing to advocate for themselves and take control of the process.
Trust and Transparency
Addressing the common realtor argument that homebuyers need professional guidance for such a significant purchase, Javaherian acknowledges that it all comes down to trust.
“Unfortunately, many homebuyers’ interactions with realtors diminish their trust,” he contends. “The system creates inherent conflicts. Agents are incentivized to close homes quickly and have buyers pay as much as possible.”
While he doesn’t blame agents for following their incentives, Javaherian believes many homebuyers, especially repeat buyers, recognize these potential conflicts of interest.
“Our users seek a platform that ensures they aren’t pressured and provides unbiased guidance,” he explains. Homa serves that purpose by offering trustworthy, unbiased, data-centric guidance to homebuyers.
Looking Ahead
As Homa continues to evolve, Javaherian hints at plans to expand into property search, but with an AI-first approach that differentiates it from existing platforms.
“We’re investing significant effort to help ensure our homebuyers can find the right home,” he says. “Adding comprehensive property search functionality with a creative, AI-first approach is our strategy.”
For now, Homa represents an innovative approach to reimagining the home buying process for a post-NAR settlement world, one where technology and artificial intelligence may increasingly supplement or replace traditional buyer agent services for a significant segment of the market.
This article was sourced from a live expert interview.
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