FoxyAI: Real Estate Frustration Leads to Valuation Innovation –

6 minutes, 17 seconds Read

In the real estate business, how a property looks has a big impact on how potential buyers make a decision.
With so much at stake, real estate professionals have turned to AI in the buying, selling, planning and visualization of real estate.


World’s Leading High-rise Marketplace

“I wouldn’t disagree with the perception that the real estate industry has been slower to adopt technology historically,” FoxyAI CEO Vin Vomero told PYMNTS. “But I think they have very quickly jumped on the AI train. AI has been transformational across many industries, and people in the real estate world have seen that and they realize what kind of benefits AI can have within their business.”

Vomero is a former real estate developer whose company is among those deploying AI to shatter that perception of paper contracts, paper checks and paper photos. FoxyAI’s mission is to transform the way consumers perceive, analyze and engage with property data through AI.

Founded in 2018, FoxyAI was born out of Vomero’s frustration with an appraisal coming in lower than expected, sparking a journey into the potential of AI and computer vision to revolutionize the valuation of real estate. His frustration led to the development of a platform that turns property photos into actionable data.

FoxyAI isn’t involved in actual real estate transactions. Instead, it focuses on creating efficiencies and improving margins for its clients through what it calls “Visual Property Intelligence.” It leverages AI-driven computer vision, machine learning and data science to turn property photos into usable data, catering to a diverse clientele that includes government entities, lending institutions, property preservation and asset management companies, insurance providers, appraisal and inspection firms, tech companies and real estate investors.

The company delivers its brand of AI through its proprietary FoxyAI Model Library, accessible through an API, that empowers users to assess property quality, condition, location, room, scene, object detection, occupancy, damage prediction, and renovation cost estimation.

In addition to the Model Library, FoxyAI provides users with a suite of solutions, from quality control to property valuations to a generative AI model that allows users to search real estate datasets flexibly, identify similar properties And estimate renovation costs. The pain points it solves for include providing solutions that facilitate better information flow and, consequently, smoother transactions in the process.

According to Vomero, the company’s impact extends beyond valuations. FoxyAI can assist real estate agents in becoming more effective through tools like virtual staging and advanced search capabilities for unique property features. FoxyAI GPT, for instance, enables comprehensive searches across real estate datasets, ranging from specific objects to abstract concepts such as open kitchens with natural lighting.

The company has also developed AI-enhanced automated valuation models (AVM), which uses a proprietary condition scoring method and quality score models. These innovations allow for instant consideration of a property’s condition alongside traditional metrics, yielding more accurate valuations.

“We help facilitate better information, which in turn facilitates a better selling process,” Vomero said. “So, for example, many of our customers use our condition score and quality score models to enhance their AVMs, and this allows any algorithm to factor in the condition and quality of the property instantly, alongside typical property level features like location and square footage, number of bedrooms and bathrooms, which results in a more accurate valuation.”

What does that look like in practice?

Take NCCI, a risk resolution outsourcing company which provides consumer outreach solutions for real estate and inspection services. The company’s property inspection services include reporting on a property’s occupancy status, evaluating the overall condition of the property, assessing the exterior condition of the home and detecting any incidents of vandalism. By utilizing property photos, it ensures that field reports are accurate and that the valuation process has been correctly followed.

However, the manual verification process is labor intensive and requires multiple full-time employees to oversee the quality control process. As a result of using FoxyAI’s models, Vomero said, it reduced the labor costs involved in quality control by 50%.

The company won its third straight HousingWire Tech 100 award in mid-February. While specific financial goals remain private, Vomero suggested a future marked by significant advancements in optimizing AI models and customer experience.

“We pride ourselves on hiring the best people for every role in our company, and particularly our engineers and AI folks,” Vomero said. “They’re the ones that drive the solutions that we offer our customers. But from a brand perspective, technology can only go so far. It’s how you use that technology to transform your customer experience that matters. That’s why we have a lot of team members that have backgrounds in real estate as well. I want to focus on continuing to deliver that expertise.”

This post was originally published on 3rd party site mentioned in the title of this site

Similar Posts