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| Tom Martin |
Depositron was launched on Independence Day by Tom Martin, the CEO of automation company LawDroid, and Sateesh Nori, a senior legal innovation strategist at legal tech company Just-Tech Inc. The two hope the app will help tenants who may not have the necessary legal acumen to get their deposits back.
"There's growing commercial interest in this direct-to-consumer market, and I really think that people should take it seriously," Martin told Law360. "It's not just charity. It actually is something that raises all boats."
The founders hope Depositron will help address a multimillion-dollar issue that looms large in New York City. According to Martin and Nori's research, nearly 5,000 New York City tenants have filed complaints over illegally withheld security deposits with the New York attorney general since 2023. The attorney general's office has recovered $2.1 million for tenants through mediation, but with approximately half a billion dollars tied up in security deposits at any given time in the city, according to its comptroller, Depositron's founders believe more can be done.
Legislation passed in 2019 mandates the return of security deposits within 14 days of a tenant's moving out, with deductions allowed only for unpaid rent, damages beyond wear and tear, and specified charges. Tenants, however, need to know how to assert their rights, and the time and money needed to hire a lawyer often makes the fight feel hard to justify, Martin noted.
Depositron steps in by taking information and apartment photos from tenants and using artificial intelligence to generate demand letters. The app is being offered free to the first 1,000 users.
Here, Martin discusses the launch and how AI can be used to help New York City's many renters. This interview has been edited for length and clarity.
How has everything gone with the launch?
It's gone pretty well. We've gotten a few hundred users so far, last time I checked. People have activated Depositron and engaged with it, and I'm excited about the potential.
Can you explain how Depositron uses generative artificial intelligence?
Like a few projects that I've worked on, it's a great way to unlock domain expertise and get it out there to the world.
What I mean by that is that we have connected it to reliable sources of information — in this case, about security deposits in New York City — and then when people ask questions about that subject, generative AI finds the right bits of information to serve up and then uses it to synthesize an answer. So every single person that interacts with it gets a custom legal answer every single time.
How did this issue first come to your attention?
I have to give the credit to Sateesh. Sateesh has been working in housing advocacy as an attorney for 20-plus years, and he's even written a book about it. So he's the expert, and he knows his stuff, and [he] identified that this is not just a legal problem, but one that has a lot of numbers behind it.
A lot of people are affected by this, and it's a sizable financial problem, too, when you put together everyone in New York City that's experiencing difficulties with landlords holding onto their deposits.
Why do you think there are still issues with this, despite the legislation that was passed in 2019?
Like with a lot of things, I think it's that the information is unequally distributed. Not everybody knows. And then some landlords — not all landlords, but some landlords — like to take advantage of that information inequality to keep the money.
They're counting on the fact that most renters don't know about that — that they're not educated about the security deposit laws in New York City, and that even if they were to learn about it, what are they going to do about it? Landlords typically have financial resources or connections to lawyers, and most renters don't. And so there's a power imbalance there that exists, and we're hoping to address that imbalance through technology.
What other access to justice issues do you think technology like this could address at some point?
There's definitely room for expansion. There are, within housing itself, many additional issues.
It could be housing discrimination. It could be wrongful evictions themselves, and defending against those. When there's problems with your apartment — say, a leak, or some issue that's not being addressed that affects health and safety. All of those are ripe for expansion.
But I do want to emphasize that from our standpoint, we want to start with something that's a single issue that we can focus on, do well and help people, and then, based upon the success of that, expand to other issues.
Do you think generative AI overall has the potential to be a game changer in closing access to justice gaps?
I absolutely do believe that. And the reason why is I've been in this space engineering access to justice solutions for almost 10 years now, so way before generative AI.
So I knew the before and after picture. And the before picture was that we could engineer solutions that use logic-based, conditional logic chatbots, and they worked pretty well. But what would happen is, when people would ask questions it wasn't anticipating or they have edge cases, it would tend to break. It was somewhat fragile.
Generative AI fills that gap so that it can go with the flow of what people are asking about and then direct down the right path. And that ability to have a much more human conversation and provide flexible information and guidance is exactly what people need. And so now it's possible to scale help to millions of people that need it at very low costs.
And so based upon my over 25 years of experience as a lawyer [and] my over 10 years of experience engineering AI solutions for the access to justice space, I believe that generative AI can fill the gap, and that's the project that I'm working on with Sateesh and many more to come.
--Editing by Robert Rudinger.
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