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Real-estate AI that ships on hostile data.

MLS feeds that never agree. Leads that vanish between handoffs. CRM records that quietly lie. We build AI that works on the data you actually have, not the clean version that only shows up in a demo. Normalized, deduplicated, production-real.

500+
MLS schemas we normalize
1-8%
Lead leakage we close
21×
Speed-to-lead decay we fight
8
Systems we build
$55K
Where projects start
Trusted by brokerages, proptech platforms & property teams
★ ★ ★ ★ ★ Clutch · 5.0 ★ ★ ★ ★ ★ G2 · 5.0 ★ ★ ★ ★ ★ GoodFirms · Top Dev Firm AWS Partner
Residential brokeragesPropTech platformsCommercial CREProperty managementMLS & listing portalsResidential brokeragesPropTech platformsCommercial CREProperty managementMLS & listing portals
Where we help

Three segments. One data problem, different shapes.

01

Residential

MLS fragmentation and lead-pipeline leakage across regional systems. We normalize the feeds and close the gaps where leads quietly disappear.

↳ MLS normalization
02

Commercial

Lease and document complexity. Clause extraction that gets validated against real documents, not the three clean PDFs everyone tests on.

↳ Lease document AI
03

Property management

Tenant records, maintenance histories, and operational data that never lived in one place. We integrate it so it can actually be reasoned over.

↳ Operational integration
What we build

Eight systems. Each built for dirty data.

01

Lead lifecycle integrity

Tracks every lead through every handoff and flags the leaks the moment they happen.

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02

Speed-to-lead automation

Responds while the lead is still warm, before the 21× decay does its damage.

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03

MLS normalization

Turns 500+ incompatible schemas into one you can actually build on.

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04

Lease-document AI

Clause extraction with validation you can trust on real, messy contracts.

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05

Attribution tracking

Credits the thing that actually drove the deal, not the last click before it.

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06

Identity resolution

Collapses the same property showing up as four listings into a single truth.

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07

CRM workflow automation

Holds up on messy input, so agents stop escaping back to their spreadsheets.

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08

Property AI tools

Search, valuation, and recommendation built for the data you have today.

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The through-line

Every one of these fails the same way if the data layer underneath doesn't hold. So that's what we build first.

Spotlight: where real-estate AI breaks

Real-estate AI, without the wishful thinking.

We don't demo on clean data and call it shipped.

Most teams validate against tidy sample data because it's easy to get and makes the demo look great. We validate against production-grade data, the kind full of nulls, typos, and contradictions, because that's what your system will actually see.

We run failure-mode analysis before we ship, so we know how the system behaves when the input is garbage. And we build structured validation in, so the AI says "I'm not sure" instead of confidently returning something wrong. In real estate, a confidently wrong answer is worse than no answer, because someone acts on it.

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Six places real-estate AI breaks: we design for all six
01 Hostile data incompatible schemas
02 Silent lead leakage unwatched handoffs
03 Speed-to-lead decay slow = dead lead
04 CRM on dirty data workflows choke
05 Attribution blindness last-touch lies
06 Identity & dedup one building, four rows
Built for the data real estate actually has MLS / RESOFree-text fieldsDuplicate listingsMulti-CRMLeaky pipelinesLegacy feeds
Talk to a real-estate engineer, not a sales rep

Ready to build real-estate AI that actually holds.

Bring us the MLS mess, the leaky pipeline, or the CRM nobody trusts. We'll pressure-test what's feasible, scope a fix against your real data, and send back a one-page plan within 48 hours. Senior engineers on the call, not sales reps.

Applied AI Engineering · Since 2011
Q2 2026 capacity open