Khoury News
There’s a new leasing agent in the crowded Boston rental market … only this one’s an AI
Leasing agents spend much of their time asking and answering the same renter questions over and over. So a team of Northeastern students built an AI agent called HouseFly to do it for them.
Milo Margolis wants to make his mark on the Boston rental market, and he’s hoping his newly launched AI-powered leasing agent is bringing him closer to doing just that.
Margolis, a fourth-year computer science major at Khoury College, was inspired to create HouseFly following a 2024 Dialogue of Civilizations in Belgium in which he and his cohort were instructed by their professors, Mark Fontenot and Eric Gerber, to build an app — “something from scratch that has a database and a front and a back end and actually worked,” Margolis says. “And that sparked an interest in wanting to build stuff on my own.”
READ: Pastries and projects: Khoury undergrads study data and software in Belgium
Initially, he and several other Northeastern students built HouseFly as a free matchmaking app to help first-time renters find housing and roommates in Boston by interviewing tenants and weeding out real estate agents who treated their clients poorly.
But within a few months, he realized the limits of the app’s utility and profitability.
“We would be following up with hundreds of people, basically answering the same questions and trying to extract the same information from every roommate group,” he explains. “And the problem was that 95% of them did not close a lease, which is normal for real estate agents in the student rental market. They're working with 10 other agents; they change their plans all the time.”
That inefficiency, coupled with a desire to transition to “something more focused on AI,” compelled Margolis to ask some of his agent contacts about their workday pain points. The one that stood out: Boston real estate agents spend 60–70% of their working hours answering would-be renters’ questions, qualifying their information, and following up with them — a tedious and time-consuming process of asking and answering the same questions.
“If we can replace that piece and free up another 20 or 30 hours during the agent’s week to get new leads or close deals, we’d be solving an actual problem,” Margolis says.
Margolis says the tech behind the newest iteration of HouseFly — an SMS assistant to handle that legwork — was fairly simple to implement. To start, HouseFly purchases a 10-digit phone number capable of application-to-person messaging for the real estate agent to use as their SMS assistant. Once the number is registered and legally cleared for commercial text messaging, HouseFly uses LLMs to generate natural questions and responses; a Supabase database to store users, responses, and prompts; and AWS-Lambda to deploy the software.
For the AI component, HouseFly uses OpenAI's API to generate standardized screening questions for renters based on their initial inquiries about preferences and requirements.
"We just integrate with MLS, the Multi Listing Services API, to get access to what houses are available and in what areas," Margolis explains. This integration allows the system to cross-reference renter preferences with available properties in real time, pulling listing data including price, location, amenities, and availability.
A real estate agent would start the process by creating a group chat that includes the AI assistant and the prospective renter. The assistant automatically initiates a structured interview process, asking standard qualifying questions —"How many bedrooms?" "What's your price range?" "Preferred neighborhoods?" — that would typically require agent time. The AI parses the responses, structures them into standardized data fields, and auto-populates them into a Google Sheet.
Margolis notes that many agents might not be ready to use AI for workday solutions quite yet. But he’s hopeful that the simplicity of essentially creating a group chat — and tech doing the rest of the work — will entice more agents to get on board.
Anthony Contreras, a real estate agent at Cornerstone Real Estate, first connected with Margolis when Margolis was looking for an apartment. Contreras said he had a positive experience with the original matchmaking app and with Margolis — “he's very outgoing, very eager, very knowledgeable and smart” — and is eager to explore the capabilities of the AI assistant during the upcoming fall lease-signing season.
“We rent about 300, 400 apartments every season, so the questions are going to accumulate,” he says. “To have a system in place ... that has all the answers will free up a lot of our time and make things easier.”
HouseFly is monetized as a subscription service for now, but Margolis stresses that his primary goal is to improve utility for a variety of brokerages.
“I'm more just trying to figure out if we can make something that's useful for people and then we can figure out how they how much they'd be willing to pay,” he says.
Margolis credits both the structure and leaders of his Belgium Dialogue as instrumental in giving him the confidence and chops to get HouseFly to where it is.
The experience “definitely built us up not only as programmers, but just as people confident to try things and build things.”
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