No black box. Here's exactly what we score.
Roofbird's AI reads two things, then combines them into a single 0–100 buy-probability score per home. Every score comes with the signals behind it, click the card, see what the AI saw.
Two inputs
The roof tells us what's there. You tell us what you want.
Input 1 · Imagery
What the AI reads from satellite
- Roof material — asphalt, tile, slate, metal, TPO/EPDM commercial flat
- Visible condition — moss, granule loss, missing shingles, dark patches
- Age estimate — surface uniformity, weathering, fading pattern
- Damage signs — tarps, partial repairs, hail spatter patterns
- Complexity — number of facets, valleys, dormers, vents, skylights
- Roof footprint — square footage, pitch class
- Solar panels, tree overhang, satellite dishes
- Neighborhood signals — how many roofs around it are recently re-roofed
Input 2 · Your business
What we learn from your website
- Materials you install — residential asphalt? metal? tile? commercial?
- Sales angle — insurance retrofit, age-driven, storm response, premium upgrade
- Geographic focus — service area, urban vs suburban patterns
- Brand voice — pulled into the door-hanger PDF copy automatically
- Logo + brand color — pulled for the PDF and dashboard
- Contact phone — for the door-hanger CTA
- One-paragraph business summary — used to judge fit per roof
Same map, different roofers. An asphalt shop and a commercial flat specialist get completely different lead lists from the same polygon. The roof's score depends on your profile.
Sample score
Every score is broken down.
Click any lead in the dashboard to see exactly what the AI saw. Here's what that looks like for one home.
Lead · 1234 Ashbury Ln, Plano TX
Aging asphalt, replacement-ready
High likelihood
Signals
AI-generated door pitch
"Hi, I noticed three homes on Ashbury were replaced this year. Your roof is about the same age and we'd love to show you what yours might look like, free, just 10 minutes."
Roof condition
32 / 40
Business fit
28 / 30
Neighborhood signal
27 / 30
Business-fit examples
Same map. Different leads.
Three roofers running Roofbird on the exact same zip would see three very different lead lists. Here's why.
Residential asphalt shop
Promoted
Aging asphalt, hail-touched neighborhoods, 18+ year roofs
Demoted
Tile, slate, metal, commercial flat → auto-low
Commercial flat specialist
Promoted
TPO, EPDM, PVC membranes, ponding signs, parapet wear
Demoted
All residential pitched → auto-low
Tile + slate restorer
Promoted
Tile roofs with visible cracks, slate with missing pieces
Demoted
Asphalt, metal → auto-low (wrong material)
The keep-filter
Roofs the AI rates low don't count against your quota.
Every roof in your polygon gets scored. But only high and medium likelihood roofs land in your list. Low-likelihood roofs (recently replaced, wrong material, no visible wear) get filtered out and don't burn quota.
01
In polygon
3,200 homes
02
AI scores all
3,200
03
Low filtered out
2,750 (no charge)
04
Kept on your list
450
You only pay quota for leads worth knocking. The 2,750 filtered roofs are still scored and stored, click Get leads next month and the AI moves on to roofs it hasn't shown you yet.
Honest limits
What we don't claim.
We do NOT detect yesterday's storm damage from satellite.
Public satellite tiles are months old. Storm-chasers should use Roofbird for baseline condition + neighborhood signals, and pair with NOAA storm overlays we surface separately.
We do NOT guarantee every score is right.
The AI gets surprised by tarps, weird shadows, and freshly-painted-but-old asphalt. That's why every score is explainable, you decide whether to trust it.
We do NOT replace door-knocking instincts.
A great rep with a Roofbird list will out-close a mediocre rep every time. We sort the doors. You still have to knock.
See it on real homes
Score a real polygon in 60 seconds.
25 free leads, no card. Drop your website so the AI learns your business, sketch your area, click Get leads.