Today, Mave, an artificial intelligence (AI) assistant for the real estate industry, announced it has raised $2 million in pre-seed funding and launched its beta program for agents and brokers.
The investment was raised and closed in a few weeks and was led by Relay Ventures and N49P with participation from Alate Partners, Clarim Ventures, Gambit Partners, along with several angel and strategic investors including a past president of the Toronto Real Estate Board.
Mave’s journey to today
After Mave founder and CEO Raz Zohar worked as an executive assistant for agents across the Greater Toronto Area (GTA) and gained experience with the demands on agents’ time, he discovered a gap: brokerages try to support agents, but with their commission split per deal getting smaller, many lack the resources for dedicated backend assistance.
So, Mave began as a result of this opportunity, along with the rapid improvements in AI and large language models (LLM).
“Not much has changed in recent years about the way the real estate industry operates. To modernize their brokerages, many look to existing tools for help. But these can be overwhelming for agents … Mave is the first solution we’ve seen that really solves the core problems the industry faces in a way that is easy enough for any agent to adopt,” says Alex Baker, managing partner at Relay Ventures.
Its current state
Mave currently has a team of 10. While the product has been operating in stealth mode, it has attracted interest from over 6,000 real estate agents across more than 90 brokerages in the GTA. From these prospective users, Mave has selected 1,000 to initially onboard as part of its beta program.
The team has worked to secure access to extensive market data and related property information through partnerships with real estate boards and other data providers. As the Mave AI assistant is trained using this information, it enables agents to harness market and neighbourhood insights to respond instantly to client requests and deliver a greater level of customer service.
”While our initial focus is on handling marketing tasks, with the funding in place we’re expanding our development to establish Mave as a full-time assistant,” says Zohar. “Mave will handle key back-end administrative tasks, from coordinating an open house to finalizing contracts better and faster than ever before.”
Baker adds, “We believe in Raz and his team and are confident that this is the right approach for the industry.”
How Mave works
Agents text questions to Mave such as “What is the price per square foot of homes in “X” postal code?” Then, in seconds, Mave can automate backend tasks, such as creating social media posts, marketing materials, emails and presentations.
The product fits into existing workflows, enabling agents to interact with the AI assistant via text messages just as they would their real assistants to get tasks done.
Use cases
The number of reported daily wins and use cases shared by agents testing the platform have exceeded Mave’s expectations. For example, for one agent participating in the beta program, the ability to immediately respond to a client’s questions and very quickly price the property enabled them to secure a listing within 24 hours.
Another agent that used Mave to optimize a listing saw showings go from zero to 11 in one week. A third used Mave to create the concept, script, post and caption for an Instagram campaign that led to a sale for $100,000 over-asking price.
Among the first Mave beta customers is PSR Brokerage, a luxury boutique real estate firm with over 150 agents in Southern Ontario. The brokerage specializes in resale and pre-construction sales, supported by high-end marketing services for its clients. Within the first week of signing up for the Mave beta program, 60 per cent of agents are actively using the AI assistant at least six times per week.
“Clients have high expectations of realtors to know every detail about thousands of listings,” notes Joshua Chisvin, VP of resale, partner at PSR Brokerage. “With Mave, we finally found the perfect solution to enable our teams to meet this demand effortlessly.”
