Digital real estate platform developer Wahi embracing AI in big way

ChatGPT applications are springing up everywhere, including at Wahi, a Toronto firm that specializes in real estate data and analytics. It has already received approval from OpenAI  for its plugin for the generative artificial intelligence (GenAI) chatbot.

According to Benjy Katchen, the founder and chief executive officer (CEO) of Wahi, which has developed its own real estate platform, the organization began development of the plugin soon after the release of ChatGPT-4, which occurred last November.

Officially launched in May, he said the firm’s offering is designed to “give more control to homeowners. (It) makes the homebuying journey more convenient than ever.

“The plugin can turn the property search into a conversation that can take place in any language in a very natural way for consumers.”

A release issued by Wahi said that ChatGPT users who enable it can find property listings that meet their specific criteria: “For example, ask ChatGPT, ‘can you help me find condos for under $800,000 in Toronto’s Entertainment District or Liberty Village?’ and the plugin will pull listings curated to meet your criteria. You can get even more specific by requesting listings for properties near TTC stations or with parking spaces, too.”

Plugins such as this, the company stated, improve the ChatGPT experience by “connecting with the OpenAI chatbot and feeding it the latest information from trusted third-party sources. The Wahi plugin is available to anyone who has a ChatGPT Plus subscription and currently features listings from across Ontario.”

In addition to that offering, late last month the company launched the AI-powered realtor recommendation system, which it said is designed “to put consumers in the know by arming them with the information and data they need to find the right realtor for them.”

Homebuyers and sellers across Ontario, it said, can use the system to compare “fees, services, realtor profiles, statistics, and personal introductions to find the right fit.”

A set of questions submitted by Wahi in a first-time homebuyers survey sponsored by residential mortgage insurer Sagen and conducted by Environics Research revealed that upwards of 45 per cent of recent buyers, or those intending to buy a home, rely on referrals from family, friends, or colleagues to find their realtor.

“While relying on family and friends to recommend a realtor isn’t necessarily a bad thing, it also doesn’t always lead to the most suitable match or the best outcomes,” said Katchen. “For example, just because a realtor is a good generalist or good in one specific area doesn’t mean that they are the best suited for a completely different part of the city or different type of home.

“Realtors lend expertise to the real estate experience with their local knowledge, connections, and experience in the neighbourhoods in which they work. The ability to get matched with the top 10 per cent of realtors in your area through our system is unique to Canada and will help to create a better overall real estate experience for Canadians.”

The system was co-developed with The Vector Institute, an organization launched in 2017 that assists public and private sector organizations of all sizes adopt and embrace AI advances.

Wahi signed on with Vector’s Fastlane initiative, which is designed to assist small and medium sized companies in Canada who “have clear plans for AI, but limited resources to carry them out.”

Tony Gaffney, Vector’s president and chief executive officer (CEO), said the “Wahi team was able to tap into (our) network of AI experts and turn their idea into reality.”

The whole intent, the release stated, is to “provide a way for consumers to choose a realtor that will get the best results for them.

“The matching tool uses extensive data and AI to analyze hundreds of real estate agents in every micro zone in Ontario. Homebuyers can be matched based on their desired price range, property type, and other personalized criteria. The proprietary algorithm provides personalized introductions to the top 10 per cent of agents based on the specific preferences and needs of each consumer.”

Factors used to match the most suitable realtors with consumers include property search location, property type and price, and agent experience and expertise, as well as their sales history and proven results.

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