Divya Aathresh On Using Ai To Solve Brokerage Back Office Problems

Editor in Chief Sarah Wheeler sat down with Divya Aathresh, founder and CEO of MaxHome.AI, to talk about the startup’s goals and how using artificial intelligence to solve real estate’s back-office problems will free up agents to do what they love best.

Sarah Wheeler: You founded MaxHome.AI in January. What stage is the company in right now?

Divya Aathresh: We are still very early, in the pre-seed stage. In terms of options, we’re very fortunate to have some of the top brokers in the country working with us on a product suite we will soon take to market. Processing is a big piece of what brokerages care about, so we have a copilot that we’re getting feedback on and plan to have six or seven copilots that will launch next year.

SW: How did you decide what part of the process you wanted to improve?

DA: When we started out, I thought AI would be most helpful in marketing, getting people in the funnel. But as I spoke to more people, the true pain point is how the transaction is getting managed, which shows up in how customers or workers are seeing the company, so we started looking at the downstream part of the transaction.

A copilot is a broad term, but at a high level, the idea we’re chasing is that no agent needs to go back late at night and open up their laptop to do more work. We’re very focused on assisting in the back office, streamlining the 10-15 different parties that are involved in the coordination of the transaction.

There’s a lot AI can do here to reduce complexity, because it can understand language and we can train the model in a very real estate-specific way. The goal is very practical solutions to address what’s hidden in the backroom of the back office.

SW: What differentiates your tech?

DA: When you look at how an agent spends their time, half of it is spent on things that don’t make them money — entering data, gathering documents, calling people. A lot of what happens is very inefficient, but it’s hard to build tech for that. We are using tech to understand the transaction, to look at all the documents and emails, and once you map it out, it opens up a whole suite of experiences for all people involved.

We’re working with our customers and breaking down the minutiae. We’ve trained our AI models to be extremely specific to help agents, brokerages and end customers as well.

SW: Tell me more about your background.

DA: In the early part of my career I was intentionally a generalist. I wrote software, then spent time in fintech, risk in particular, and did strategy work at McKinsey. Then Better brought me to this industry. I joined the strategy team there and saw how complex, how big the challenge is, but also the types of solutions provided.

I spent four years at Better and shadowed our own in-house agents. I looked at details — why is this email going out? How are they using tech? That aspect opened up a lot of learning for me: part product discovery and part were my connections in the industry.

In the last few years, the opening point for me was seeing the potential of how working hard and working smart with tech options could unlock opportunities for our customers.

SW: What do you see as the risks of AI?

DA: I think there is a potential perception risk, with a question around if AI is helpful or harmful. In our case, we already see how it is adding value and helping customers. I’ve had customers tell me that it’s changing their life because they don’t have to work until midnight now.

From the standpoint of a startup founder, I’m hyper-focused on the team I’m bringing together. Very early on, I brought on people from Better who understood the industry. Our head of sales is a life-long Realtor, one of the first people I hired when I was at Better. Our head of machine learning — they understand the industry, the pain points of the customer.

SW: What keeps you up at night?

DA:  Having an unhappy customer. That’s the only focus — if we get that right, all the other things will work out.