Real Estate Company Raises $290 Million with Temy’s AI-Powered Price Predictor Tool
$290M+
total funding raised
8
AI tools
$100M+
saved by home buyers & sellers
THE CHALLENGE
Launch new AI features right before the investment round
Reali, a U.S. based real estate startup founded in Israel in 2015, disrupted the market with a flat-fee model instead of traditional commission fees, making home buying and selling more affordable than ever.
At the time, Temy was already working with Reali on home systems, but we saw an opportunity to facilitate the home buying process: an
AI-powered tool that could take the guesswork out of home pricing.
Setting the right price is a gamble. Buyers and sellers rely on rough estimates, and bidding wars often send final prices skyrocketing. To fix this, we proposed Reali build an AI model that could predict the actual selling price, helping buyers bid smartly and sellers price their homes right. With an investment round approaching, Reali needed a feature to impress investors. They gave us 1 month to build a Proof of Concept and prove the idea was feasible.
Obstacles
How Temy made it happen
Messy, inconsistent data
U.S. real estate data is publicly available, but it comes in different formats that constantly change, making data preparation tough.
Tight deadlines
We had only 1 month to develop a PoC and give Reali the possibility to raise funding for the development of a full-scale price predictor.
High accuracy needed
The model had to accurately predict home sale prices, avoid any hallucinations, and provide users with clear explanations of its estimates.
THE SOLUTION
AI price predictor for buying and selling homes
We started the project by testing the idea on housing datasets. Temy’s Data Scientist conducted in-depth research and built a model that delivered accurate results on sample datasets. From there, we moved fast, developing and launching the first version of the price predictor in just 6 months. But that was just the beginning. Over 5 years, we kept refining the tool and building new AI models, making home buying and selling smoother than ever.
Proof of Concept in 1 month
Our Data Scientist researched real estate pricing trends using 30K property listings, developed an algorithm, and built the first model in just four weeks, proving the idea was feasible.
Price predictor launched in 6 months
PoC was a success, so we rapidly moved into full development. Our dedicated team of data engineers and ML specialists refined the model, ensuring it was ready for release.
New features and data cleaning
We prepared housing data for instant calculations, integrated it into Reali’s mobile app, and built an explanation model so users could understand the logic behind AI-driven pricing.
More AI models for Reali
Over five years, Temy developed 8 AI models for Reali, each offering new features, from suggesting sellers price-boosting improvements to segmenting the real estate market for better analysis.
Key project outcomes
$20M series
B funding
Reali secured $20 million in Series B funding, using the price predictor to secure funds and fuel further AI development.
Company growth
In 2020 alone, Reali saw:
- 7x year-over-year growth
- 2x customer base expansion
- 3x increase in average revenue per user (ARPU)
95%
accuracy
The AI model delivered instant price estimates with a 95% accuracy rate, setting a new standard for predictive pricing in real estate.
THE PROCESS
How we built an AI-powered home price predictor
Predicting home prices with AI sounds simple – just feed it the right data, right? Not quite. The real challenge is in the data preparation itself.
First, we needed enough data, so we pulled in lots of datasets. But size wasn’t the only problem, as data quality was inconsistent. We had over 20 data sources, each with different formats that kept changing. If the AI couldn’t read the data properly, the entire prediction tool would fail.
Then came the next challenge – accuracy. A model that predicts prices is useless if it can’t tell good predictions from bad ones. We had to teach it to evaluate itself, filter out unreliable results, and explain its pricing logic so users could trust it.
Here’s how we tackled each step:
Temy lies the foundation of the price predictor
Reali estimated home prices manually by checking real estate websites and calculating averages. We set out to automate this. Our Data Scientist tested different AI models, picked the best one, and trained it using over a million property listings.
Our Data Scientist creates filtering systems to clean data
We had to deal with a million listings of unfiltered data – some sources used numbers, others text, and some empty fields. While humans can easily make sense of this, an AI model requires a unified formatting. So, we built smart filtering systems to clean and organize the data, making it ready for model processing.
The team teaches the model to self-evaluate
Some home price predictions were spot-on, but in areas with too little data, accuracy dropped. Instead of letting bad predictions slip through, we built a model that could evaluate its own judgments. If the model wasn’t sure, it simply removed those results, allowing us to achieve 95% accuracy.
We made predictions understandable with an explanation model
As the AI model started generating home price predictions, one issue became clear – users needed to understand why a house was priced a certain way. Instead of leaving them with a “black box” algorithm, we built an explanation model that broke down the most important pricing factors.
Our team continues to add new features to the platform
Temy didn’t stop at the price predictor. In sum, we built 8 AI models solving different problems for Reali:
- Finding similar homes to help users explore options
- Breaking down homes into components and predicting their prices
- Suggesting ways to boost home prices with smart recommendations
- Segmenting the market for better targeting
Our team kept pushing forward, powering the Reali platform with new AI features.
The augmented teams are professional and always deliver on time. Temy provides personable service and successfully recruits top-notch resources. Customers can expect competitive prices.
Tal YanivVP R&D at Reali
The result
AI price predictor instantly analyzes millions of listings, giving buyers a clear understanding of the most probable future price and helping sellers set the optimal price for their homes. This AI feature helped Reali secure multiple investments and attract more than twice as many customers.
Before
Pricing a home was a guessing game or a slow, manual process
No exciting features to grab investors’ attention
Limited functionality for users
Too costly home buying or disadvantageous selling
After
AI calculates the perfect price in seconds with 95% accuracy
8 cutting-edge AI tools that helped secure $290M+ in funding
A game-changing tool that makes buying and selling easier, avoiding bidding wars
The price predictor already helped users trade hundreds of millions in homes
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