Model data freshness and evidence instead of treating every CRM field as equally trustworthy.
PROJECT / 03 · Real estate / operator workflow
AI Real Estate CRM
The AI Real Estate CRM is a public systems layer for turning messy property, owner and lead data into explainable matching and safer next actions.
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Property CRMs become noisy quickly: duplicated people, stale property context, weak identity resolution and generic “AI” recommendations make it harder to decide who to call and why.
HOW I BUILT AROUND IT01 02 03 04
Use deterministic matching where the operator needs to understand why a contact or property matched.
Generate call angles from verified context instead of inventing buyer or seller intent.
Keep voice-agent handoff separate from identity and matching logic.
CAPABILITIESWhat it does,
What it does,
without the theatre.
01Evidence freshness02Contact/property identity logic03Deterministic matching04Safe call-angle generation05Voice-agent handoff data06Synthetic-first public fixtures
ARCHITECTURE
What the system is meant to preserve.
- 01Never fabricate intent
- 02Make data freshness visible
- 03Keep identity resolution auditable
- 04Design for a broker’s next action
Does the public project contain private CRM data?+
No. The public project is synthetic-first and demonstrates the systems logic without publishing private operational data.
How are matches explained?+
The public core emphasises deterministic matching and evidence freshness so a suggested relationship can be traced to known data.
Does the voice agent decide identity or intent?+
No. Voice-agent handoff is downstream; the CRM core first resolves identity, context and the safe call angle.