Introducing

burbia

"Find where you belong."

AI-powered town and neighborhood discovery for families moving to the suburbs, before they ever look at a listing.

Confidential · 2026
01 / 10
Burbia

The Problem

Six months on Zillow.
Still no idea which town, or which part of it.

Families leaving NYC know they want the suburbs. They don't know where to start. And picking a town is only half the problem.

340K

households leave NYC metro annually

4-6

towns considered before deciding. Then weeks more researching neighborhoods within each.

The process today: months of Reddit threads, Facebook group arguments, conflicting realtor advice, and weekend drives through 8 towns. Then more weeks trying to figure out which part of the right town to actually look in. The only structured alternative requires booking a human consultant and waiting weeks for a recommendation. Most families stay paralyzed.

We’re building for the family that spends six months researching before a single showing. They exist in every metro. They’re underserved everywhere.

02 / 10
Problem

The Market Shift

Real estate AI launched in 2025.
It skipped the first two steps.

Homes.com and Redfin built conversational AI for listing search. They help you find a house once you already know the town and neighborhood. Nobody built what comes before.

01Which town fits our family?Burbia
02Which neighborhood within that town?Burbia
03Which listing matches our criteria?Zillow / Redfin AI
04Make an offerRealtor

Burbia owns Steps 01 and 02: the highest-leverage, completely uncontested layer in the entire real estate stack. The buyer arrives at a realtor already knowing their town and their neighborhood.

03 / 10
Opportunity

The Solution

An AI advisor that finds your town,
then your neighborhood, before your house.

01

Tell us about your family

Where you're coming from. Kids' ages. What matters most: schools, commute, walkability, community vibe.

02

We surface the trade-offs

Everyone compromises. We name the conflicts honestly: schools vs. commute vs. price. Then help you decide which ones you can live with.

03

We match you to your town

Ranked town recommendations with real data: school ratings, commute times, median prices, tax rates, and vibe. In plain language.

04

We narrow to your neighborhood

Within your matched town, we identify which neighborhoods fit how you actually want to live: walkable downtown, near the train, quiet cul-de-sac, close to parks.

The output: A structured buyer profile: matched town, specific neighborhoods, priorities, trade-offs accepted, budget, timeline, and a verbatim quote from the conversation. A realtor receives a buyer who already knows exactly where they want to look.

04 / 10
Solution

The Product

Live. Working. Differentiated.

A conversational AI that knows NJ suburbs cold, town by town and neighborhood by neighborhood, and shows its work on a live map.

  • Single conversation flow: town discovery → neighborhood match → buyer brief output
  • Inline suggestion chips guide without constraining. Feels like an advisor, not a survey.
  • Live map updates as preferences are captured. Pins narrow from towns to neighborhoods.
  • Neighborhood profiles: walkability, school zones, commute access, character, price band
  • Town + neighborhood detail drawer surfaces hyperlocal data: restaurants, parks, events, hidden gems
Burbia · NJ Suburb Advisor
Let's figure out where your family belongs. Are you coming from the city?
ManhattanBrooklynHoboken/JC
Manhattan. Two kids, 6 and 9.
Schools matter a lot with a 6-year-old. That points to Summit or Westfield. Once we narrow it down: do you want walkable to a downtown, or quieter streets near a park?
05 / 10
Product

Market Size

A $28,000 transaction.
An uncontested entry point.

340KNYC metro households relocate annually
85KNJ suburb moves per yearCensus, 2024
$1.1MMedian NJ suburb purchase priceTarget market
$28.5KAvg. realtor commission per NJ saleAt 2.5% buyer-side

Closest analog: Suburban Jungle

10

metros served (human-based)

~40

families per consultant per year (capacity ceiling)

Profitable

single founder, no tech

Suburban Jungle is a good business built entirely on human consultants: one per family, one at a time, capacity capped by headcount. Burbia does the same job with AI. 20 metros, no headcount ceiling. That’s the multiplier.

06 / 10
Market

Business Model

Three revenue streams.
One flywheel.

Core
Realtor Lead Packages

Pre-profiled buyers who know their town AND their target neighborhoods, with budget, timeline, priorities, and a conversation transcript attached. High intent vs. unqualified portal clicks.

Per lead
Consumer
Premium Tier

Saved profiles, listing alerts scoped to matched towns, realtor matchmaking. Converts the engaged user into recurring revenue.

Monthly
Year 2
Mortgage Referral

Refer buyers to preferred lenders at the point of realtor match. Natural placement, high intent.

Per close

As metro coverage grows, data quality compounds. More buyer conversations → sharper scoring → stronger realtor trust → more distribution. First-mover advantage is structural, not just a head start.

07 / 10
Model

Why This Wins

Data flywheel.
Local trust. Hard to replicate.

◎

Hyperlocal data no one else has assembled

Multiple verified data sources combined in a way no single provider offers. The depth, the combination, and the weighting are ours.

⟳

Preference data competitors can't buy

Every conversation produces structured intent data. It compounds. The more families we see, the sharper every future match becomes. That loop doesn't exist anywhere else in the market.

◈

Network effect: buyers + realtors

More buyers → better matching data → more realtors trust the leads → more realtors promote Burbia to buyers → more buyers.

⬡

Founder-market fit

Justin built intent-scoring systems at AOL/Millennial Media for 100M+ users. This product is audience segmentation applied to real estate. He's lived in Westfield for years and has moved families through this process personally.

08 / 10
Advantage

Founder

Built to build this.

Justin Silberman

Founder & CEO

  • PM Director, Epic Games: product leadership at global scale
  • VP Product, AOL / Millennial Media: built programmatic SSP/DSP audience targeting systems serving 100M+ users
  • Background in intent scoring, audience segmentation, lead quality systems, the exact architecture Burbia is built on
  • Westfield, NJ resident. Has personally navigated the NYC-to-suburb decision and watched friends struggle through it for years.

“I've spent 15 years building systems that match intent to outcomes. This is the same problem, applied to the most important decision a family makes.”

09 / 10
Team

Traction & Ask

Live product.
Looking for five realtors.

What exists today

  • Working AI advisor, live demo available
  • 2,300+ towns profiled across 20 US metros with verified data
  • Full discovery flow: from preferences to matched towns to neighborhoods
  • Live map that updates in real time as the conversation narrows
  • Structured buyer brief output, ready for realtor handoff

The ask

A founding pilot cohort

We'll supply complimentary buyer briefs to start. In return: honest feedback on lead quality, and a commitment to route future Burbia buyers their way.

  • Westfield · Summit · Montclair
  • Ridgewood · Chatham · Maplewood

Interested? Contact Justin Silberman to get on the pilot list.

Questions? Contact Justin Silberman to get on the pilot list.

10 / 10
Ask