The AI That Knows Who Wants to Sell Before They Do

Most real estate agents prospect by volume. Work the phones, knock the doors, send the emails, and eventually something converts. It is a numbers game, and everyone knows it. The problem is that the math gets worse every year. More agents chasing the same leads, more homeowners with caller ID and the instinct to ignore it.

Addy Kim and Chris Dimitriou built Homiere around a different idea: that data already contains the answer. With the right models pulling from the right sources, an AI platform can identify which homeowners are most likely to sell before they ever raise their hand, before they search for an agent, before they call anyone. The agent who reaches them first wins the listing.

On Episode 6 of AI Agent Advantage, JMan sat down with both co-founders to break down exactly how this works, who it is built for, and what a real estate agent can do with it starting today.

From Cold Calling Everyone to Calling the Right Five

The core of what Homiere does is predictive lead scoring. The platform pulls enriched data on properties across a market and runs it through models that look for patterns tied to historical sales activity. Equity levels, property condition, financial distress signals, interest rate sensitivity, length of ownership, permit history: these signals get combined into a prediction about which homeowners are most likely to sell in the near future.

The result is not a list of thousands of names to dial through. It is a short list of properties and owners that score high on the likelihood-to-sell model. An agent who would normally spend a week cold calling 300 people can instead focus on 10 or 15 who actually fit the profile.

"We are cutting down a lot of the brunt manual aspects of combing through who is likely to sell and list with you. That leaves you with a handful of properties or clients to reach out to, as opposed to hundreds or thousands of leads you have to cold-reach."

— Addy Kim, CEO, Homiere

For door knockers, the same logic applies. Rather than working every house on a street, an agent can go directly to the doors where the data suggests timing and motivation are aligned. JMan, who started his own career door-knocking, described it as going from knocking on 100 doors to showing up at the five that matter.

Off-Market Property Search That Works Like a Conversation

The second major capability in Homiere is off-market property search using natural language. This feature was built to solve a problem Addy and her team ran into in their own real estate investment business: finding specific types of properties to flip or develop when inventory was tight.

Instead of clicking through filter menus and downloading comps, an agent or investor can describe what they are looking for the same way they would describe it to a colleague. Homiere takes that description, runs it against enriched property data that includes orientation, pool presence, permit history, room details, and satellite-assessed condition, and returns a set of matching properties, including ones that are not listed anywhere publicly.

The example JMan raised in the episode shows how specific this can get: an agent whose client wants a home with morning light in the kitchen can search by door orientation and which direction the property faces. Homiere can return results that match. For high-net-worth buyers with detailed preferences, that kind of precision changes what it means to serve a client well.

"Anybody can come in and use plain language to search for what they are looking for. It will pinpoint, here are the properties that match exactly or close enough to the criteria you described."

— Chris Dimitriou, CTO, Homiere

Why Agents Need to Think About AEO, Not Just SEO

The third piece of what Homiere offers is AI-optimized websites. This might seem like a separate product, but Chris explained why it fits the same logic as everything else on the platform: the way consumers find agents is changing fast.

A growing number of people are skipping Google entirely and asking AI assistants directly. Who are some good realtors in this neighborhood? Which agent specializes in off-market deals in this city? The answers those AI tools return are shaped by how well an agent's online presence has been structured for that kind of retrieval, not just for traditional search engine indexing.

This shift from SEO to AEO, answer engine optimization, is something most agents have not started thinking about yet. Homiere builds websites with that in mind, working with each agent to understand what they want their site to accomplish and then configuring it to be discoverable on both traditional search and AI-driven search platforms.

What the First 30 Days Actually Look Like

When someone signs up for Homiere, the first step is a consultation call. Not a tutorial video. Not a login and a quick-start guide. A conversation with Addy or Chris directly to understand what the agent is trying to accomplish, what their current bottleneck is, and which combination of Homiere's tools will actually move the needle for them.

From there, the team configures a solution based on that specific need. Agents who want better leads get a lead feed built around their target seller profile. Agents who want off-market deal flow get a deal feed customized to the property criteria their buyers are looking for. Agents who want to show up more online get a website built for discoverability.

The onboarding process is designed to keep the learning curve flat. But Addy was clear that this is not a passive tool. The agents who get the best results are the ones who stay engaged, treat it like a campaign rather than a switch they flip once, and give the system time to work.

One Tip From Each Co-Founder for Getting Started with AI

JMan closes every episode of AI Agent Advantage with the same question: what is your single best tip for someone who is just getting started with AI?

Addy's answer: start with the thing you hate most. Every agent has a task they avoid, a part of the job that drains them. Find an AI solution for that one thing first. Once it works, the motivation to apply AI elsewhere follows naturally.

Chris's answer: slow down before you start clicking around. Spend real time thinking about how you spend your day and where the friction lives. The right application of AI becomes obvious once you understand your own workflow clearly.

Both answers point to the same principle: AI works best when it is applied to a specific, understood problem, not adopted randomly because the technology seems interesting.

About Addy Kim & Chris Dimitriou

Addy Kim is the CEO and co-founder of Homiere. Chris Dimitriou is the CTO and co-founder. Both previously worked at JP Morgan before launching Homiere to bring financial-grade data modeling to real estate. Homiere combines predictive seller intelligence, off-market property search, and AI-optimized agent websites into a single platform for modern real estate professionals.

• Website: homiere.com