Insights on how to use AI in real estate for property managers, investors, and brokers.
The data science team at HelloData.ai recently launched a new rent comp analysis algorithm that combines the power of computer vision and AI to generate an incredibly robust multifamily market analysis in seconds. In this post, we’ll delve into some of the techniques we're using to identify and analyze comparable properties with greater precision than ever before.
On average, insurance costs have increased by about 27% from 2020 through the end of 2022. The Midwest saw the lowest increases from 2020 – 2022 at only 21%, while the South experienced a 39.3% increase in insurance costs over the same time period.
Whether you’re a property manager looking to monitor competitor rents, a broker generating an opinion of value, or an appraiser looking for the perfect floorplan comps – doing an accurate rent survey is time consuming. Fortunately, we built RentSource to eliminate this manual work.
The process of developing internal products comes with a minefield of potential pitfalls unique from those of external customer-facing products. This nuanced landscape demands a different approach to product development – one that borrows from the agility of startups, but scales to fit within the organizational dynamics of larger companies.
The world of online real estate listings is plagued by a major issue - inappropriate use of images with logos or watermarks. Our proprietary technology at HelloData.ai effectively identifies, tags, and flags images with non-conforming watermarks and logos. Using the latest breakthroughs in computer vision, our unique watermark model spots images and videos containing artificially added watermarks, logos, and text overlays.
If we can generate a commercial lease abstract in minutes vs hours, capture comparable sales data from appraisals without an underwriter ever opening the document, and help acquisitions analysts deal with the continual onslaught of offering memos flooding their inboxes each week, I think we’re going to make life a whole lot better for real estate professionals.
Most real estate companies generate a ton of data through listings, purchase & sale agreements, market studies, site inspections, etc… the list goes on. Large volumes of data can be very powerful for analysis, but in real estate, this data tends to be locked in emails, PDF documents, and Excel models. It’s essentially unusable, unless the data can be extracted in a consistent way. With recent advancements in artificial intelligence (AI), however, it is becoming significantly easier for real estate companies to unlock the value of their data.
Last week, we put together data on the Atlanta rental market as part of a proof of concept with a potential client. The data included rent, availability, concessions, amenities, and many other attributes for about 16k units listed on a single day in May. It also analyzed the listing photos for each property, and included the QualityScore we generated as a variable.
The Quality Score mode objectively evaluates a property's quality condition and features/amenities from interior and exterior photos. It then converts this data to a consistent, easy-to-understand score for AVMs and comparable property detection algorithms.
