Advanced Real Estate Voice Agent

We are building an end-to-end AI-powered real estate acquisition system designed for wholesaling, creative financing, fix-and-flip, and long-term rental investing.
This is not a simple chatbot project.

The system will:
Aggregate real estate data from multiple sources (property data, pre-foreclosure, auctions, rentals, listings)
Underwrite properties automatically using investor-grade financial models
Determine the optimal exit strategy (wholesale, cash flip, or long-term hold via creative financing)
Populate all data and calculations into a CRM
Power a human-sounding conversational voice AI agent that speaks with sellers, presents offers, sends LOIs, and schedules follow-ups
Operate within U.S. calling/SMS compliance constraints using human warm-transfer → AI
We are looking for a senior engineer or small expert team with experience in:
AI agents (LLMs + tool use)
Voice AI (ElevenLabs / Twilio / SIP / low-latency speech)
API integrations
CRM + workflow automation
Financial modeling logic
Production-grade systems

End Goal (What Success Looks Like)
A working system where:
Property leads enter the system (lists, auctions, pre-foreclosures, inbound calls)
AI pulls and normalizes property data automatically
The system underwrites the deal and selects the best strategy:
Wholesale
Fix-and-flip (cash)
Long-term hold (creative financing)
A human-sounding voice AI agent speaks to sellers after a warm transfer, adapts strategy in real time, and:
Explains seller options
Presents a preliminary offer
Sends SMS/email summaries
Generates and sends an LOI for signature
Schedules a human follow-up call
All activity, calculations, and conversations are logged in the CRM

System Architecture (High Level)
1. Data Ingestion Layer
The system must pull, normalize, and de-duplicate data from:
Property data (e.g., PropStream or equivalent)
Auction data (e.g., Auction.com or feeds)
Pre-foreclosure data (county public records / notices)
Listing data (e.g., Zillow or equivalent)
Rental market data (e.g., RentCast or equivalent)

Key requirements:
Address/APN matching
Source reliability scoring
Versioned data snapshots
Confidence scoring when data is incomplete

2. Underwriting & Decision Engine
The AI must calculate and store:
Core Inputs (some auto, some user-adjustable)
List price
Suggested offer price
Assignment fee (manual override)
Rehab cost (manual override)
ARV (comps-based)
Existing mortgage balance (if known)
Existing mortgage interest rate/payment (if known)
Property taxes
Insurance
HOA fees
Closing costs
Vacancy rate
CapEx & maintenance
Management fees
Creative financing terms (interest, amortization, down payment)
Strategy Logic
Wholesale / Fix-and-Flip
MAO = (ARV × 0.70) – Rehab – Assignment Fee

Long-Term Hold / Creative Financing
Must meet ALL criteria:
≥ $200/month cashflow per door
≥ 12% cash-on-cash return
< 20% total buyer cash-in
< 10% down payment (≤5% preferred)
The system must:
Calculate monthly & annual cashflow
Calculate cash-on-cash return
Calculate buyer entry %
Suggest optimized terms if deal is close but fails thresholds
3. Comps & Valuation Engine
Pull comparable sales and rentals
Filter by distance, recency, size, property type
Score comps for similarity
Output ARV + confidence band
Flag “Needs Human Review” if confidence is low
4. CRM (System of Record)

CRM must store:
Properties
Sellers / leads
Deals & deal stages
Underwriting versions
Offers & LOIs
Call logs, transcripts, recordings
SMS/email history
Tasks & follow-ups
Consent & compliance flags

CRM can be:
Custom-built
Or an existing platform with custom objects (e.g., GoHighLevel, Podio, HubSpot)

Voice AI Agent (Critical Component)
Requirements
Must sound 100% human
Natural pacing, interruptions, emotion, hesitation
No robotic cadence
Capable of 10–20 minute conversations
Technology Preference
ElevenLabs Conversational AI (or equivalent human-grade voice)
Telephony via SIP/Twilio/Retell/etc.
Tool-calling capability to read/write CRM, send SMS/email, generate LOIs, schedule calls
Conversation Capabilities

The agent must:
Classify seller type dynamically
Switch strategies mid-call if needed
Handle objections naturally
Use CRM underwriting data safely (never assert unverified facts)
Present offers clearly
Ask for micro-commitments (“Would you like me to send this in writing?”)
Seller Playbooks (Single Agent, Multiple Modes)
Pre-foreclosure options (informational → subject-to / wrap)
Distressed sellers (low-price cash offers)
Tired landlords (seller finance / income replacement)
Inherited / probate
Vacant / code enforcement
Auction deadline sellers
Retail / listing comparison

Document Automation
Generate LOIs / intent letters dynamically
Cash offers
Subject-to / owner-carry offers
Hybrid structures
Send via SMS/email
Collect e-signatures
Store executed documents in CRM

Workflow Summary
Lead enters system
Property data ingested & normalized
Underwriting engine runs
Strategy + offers generated
Human makes initial call → warm transfers to AI
AI qualifies, presents offer, sends summary + LOI
AI schedules human follow-up
Human finalizes contract
CRM updated automatically

Compliance & Safety
Human makes initial outbound call
AI only engages after warm transfer
Consent tracking for SMS/email
Opt-out handling
No legal advice
No fabrication of financial facts
Full audit trail

Tech Stack (Flexible, but preferred experience)
Backend: Python (FastAPI) or Node.js
Database: PostgreSQL
Queue/workflows: Celery / Temporal / BullMQ
Voice: ElevenLabs
Telephony: Twilio / SIP / Retell
LLMs: OpenAI / Anthropic (tool-calling)
CRM APIs
E-signature APIs
Webhooks & event-driven design

Who We’re Looking For
This is not an entry-level project.
We want:
Senior full-stack engineers
AI/agent architects
Voice AI specialists
Small, experienced teams
You should have experience with:
LLM tool orchestration
Real-time voice systems
Complex business logic
Production deployments
API integrations
Security & reliability

Deliverables
System architecture & documentation
Working ingestion + underwriting engine
CRM integration
Conversational voice AI agent
SMS/email + LOI automation
Deployment guidance
Clean, maintainable code

Budget & Engagement
Open to fixed-price or milestone-based
Long-term engagement possible
Budget flexible for the right expertise
Quality and correctness matter more than speed

To Apply (Important)
Please include:
Relevant past projects (especially voice AI or agent systems)
Your proposed architecture approach
What parts you would build vs integrate
Any questions or assumptions
Estimated timeline
Generic bids will be ignored.