Law · Social Impact
Sateesh Nori wanted a chatbot for tenants. The team picked the one topic where being wrong wouldn't get anyone evicted.
Sateesh Nori, Jenny Laurie, Sam Flynn · New York City, USA
New York's right to a lawyer stops at eviction, and the nonprofit hotline that picks up the rest cannot reach everyone who needs it. So a team of about five volunteers spent 13 months teaching a bot one corner of tenant law.
The person and the place
Sateesh Nori spent years doing legal services work in New York City and now teaches at NYU School of Law. The arithmetic was familiar from the inside. "One of the biggest challenges of working as a legal services lawyer or a nonprofit lawyer is that you don't have enough time, or resources, to help everybody who seeks your help," Nori said.
The problem Sateesh cared about
New York City gives tenants a right to a lawyer when they are facing eviction. That right stops there. A tenant with no heat, no hot water, a dead elevator, or mold on the wall calls Housing Court Answers. By Nori's account it is a nonprofit with a staff of 15 and a budget of about a million dollars, its hotline takes about 200 calls a day, and the wait to reach a person runs 45 minutes to an hour. The other option Nori describes is a trip to a courthouse or a legal services office, sometimes three to four hours on a bench, and then usually being turned away for not facing eviction.
The agency moment
Nori had wanted to point AI at tenants' problems since 2023, and the first decision was which problem. Eviction and rent were the obvious candidates, and the team ruled them out on purpose. "We thought about eviction and rent issues, but we decided against that, because if a chatbot makes a mistake, we didn't want to risk somebody getting evicted," Nori told Law360. They took repairs instead, and trained the bot to answer "I don't know" the moment a question left that subject.
What changed, with evidence
Nori matched Josef Legal with Housing Court Answers, making three organizations with NYU Law School, and a team of about five people spent 13 months feeding it every statute, guide, and training document they could find about repairs in New York City. Nobody funded it and everybody had another job. Sam Flynn, who co-founded Josef, says Housing Court Answers, Josef, and Nori spent about six months testing it and checking its answers. Roxanne launched in January 2025, usable from a phone, drawing on Housing Court Answers' own guidance instead of the open internet. Brick Underground asked it how to get a landlord to fix the heat and got the real sequence back: make a record, tell the landlord, call 311, talk to the other tenants, and file an HP Action in housing court if the repairs still are not made. The same test found it will occasionally answer something outside its subject. Jenny Laurie, who runs Housing Court Answers, states the rest plainly: "This is a machine. It's not a live lawyer, so you're not getting legal advice that's custom made for your situation." Over three to four weeks Nori counted at least 1,000 uses. A lot of them were about heat. It was a cold January.
The move worth copying
The team did not start with the biggest problem. They started with the one where a wrong answer was survivable, and then trained the thing to refuse everything else. If you are pointing AI at something that matters, that is the first call to make: find the corner where being wrong costs the least, and begin there.
"For us, it's not even about the AI, it's about the results." — Sateesh Nori, to Law360
Sources
Here is where this story came from. Go read the originals.
Curated by Good in Progress from the public record.
Sources last verified .
- Brick Underground, Celia Young ↗
- Law360, Marco Poggio ↗
- LawNext, Bob Ambrogi, January 2025 ↗
- Thomson Reuters Institute, Natalie Runyon ↗
- Housing Court Answers, the tool's own page ↗
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