The AI prepares the work · The agent stays in control
Supervised AI operations
for Australian real estate agencies
Aussie Real Estate AI helps agents clear the admin work around enquiries, follow-up, call notes, CRM updates, calendar booking, vendor reporting, and prospecting.
Raising $50,000 to convert a working system into a repeatable implementation business.
Live agent + CRM stack
First 10 customers target
Setup fees + retainers
02 / 14
The Problem
Real estate agents lose time in the work between the tools
Agents are not short on software. They are short on clean operational execution across inbox, phone, SMS, calendar, CRM, property documents, buyer feedback, and vendor communication.
Inbox
Phone
SMS
Calendar
AGENT · manual glue
CRM
Documents
Buyer feedback
Vendor comms
Where time leaks
- Enquiries arrive across multiple channels and need fast follow-up.
- Call notes, tasks, reminders, and next actions often never reach the CRM.
- Appraisal nurture and vendor reporting require consistent preparation.
Why it costs money
- Buyer matching, prospecting, and open-home follow-up are repetitive but revenue-sensitive.
- Admin hiring is expensive, but missed follow-up costs listings and relationships.
Investor takeawayThe pain is daily, operational, and close to revenue.
03 / 14
Why Now
AI adoption is happening, but trust is the blocker
Real estate is already being touched by AI through listing copy, consumer search, agent workflows, and marketing automation. The opportunity is not convincing agents that AI exists — it is giving them a safe operating layer they can trust with customer-facing work.
Adoption
AI is already entering the workflow
Listing copy, consumer search, marketing automation — agents are already exposed to AI.
Trust
Approval-first is required
Brand, compliance, and relationships mean agents need systems that keep them in control.
Workflow gap
Fragmented tools, no operator
Work is split across many tools. The first trusted operator can expand workflow by workflow.
Investor takeawayThe category is moving from AI novelty to controlled execution.
04 / 14
The Solution
A supervised AI agent that prepares, updates, and follows up
01 · CAPTURE
Bring the work in
Website forms, calls, SMS, email, CRM records, calendars, and lead lists.
02 · UNDERSTAND
Classify it
Person, role, intent, urgency, and the next action.
03 · PREPARE
Draft the output
Replies, notes, tasks, reports, follow-up sequences, appointment options.
04 · ACT W/ CONTROL
Execute on approval
Book meetings, update CRM, send approved messages, log every action.
05 · IMPROVE
Turn runs into playbooks
Convert each run into a repeatable implementation playbook.
Approval queue · Tuesday 7:42 am
# draft · SMS Sarah M — asked about the contract for 14 Banksia St
"Hi Sarah, the contract is on its way to your email now…"
approve · edit · reject
# draft · email Ben T — price question after Saturday's open home
"Hi Ben, great to meet you at 22 Coral Ave…"
approve · edit · reject
# CRM note Call summary ready — vendor update, 8 Palm Ct → to CRM
Approval-first
Not another CRM
Operations layer around existing tools
PositioningNot another CRM. A supervised AI operations layer around the real estate systems agencies already use.
05 / 14
Live Proof
The product is already real enough to demo
Website lead
→
KAREN · OpenClaw agent
→
Twenty CRM note + task
→
Google Calendar + Meet
● Live now
- Karen / OpenClaw real estate agent is running.
- Twenty CRM dashboard is live.
- Karen creates CRM people, companies, notes, tasks, and calendar events.
- Karen books Google Calendar events with Google Meet links.
- Karen shows upcoming meetings from Google Calendar.
- Public booking page writes into CRM.
- Website call submission flow exists.
- Notes schema includes spoken status and lead temperature.
- Daily lead discovery job exists.
- Sydney 100-principal target list exists.
- Outreach message generation exists.
- Website and brand assets exist.
○ Roadmap / pending credentials
- Agent Box production integration.
- WhatsApp production sending.
- Plaud Note ingestion.
- Zoom meeting creation.
- ID4ME automation.
- Social auto-posting.
RoadmapPending credentials
Investor takeawayThis is not a slideware idea. The first operating stack exists; funding buys repeatability, reliability, and customer delivery.
06 / 14
The First Customer Workflow
Turn inbound and outbound conversations into booked sales opportunities
Website / outbound lead
→
Confirm role
→
Capture details
→
Explain use case
→
Book founder call
→
$500 audit deposit
What Karen does
- Confirms they are a real estate agent, principal, or relevant agency operator.
- Captures name, role, agency, location, and the most time-consuming workflow.
- Explains the relevant Aussie Real Estate AI use case.
- If qualified, books a founder call. If high intent, sends a $500 AI-readiness audit deposit link.
- Updates the CRM with status, notes, lead temperature, and next action.
Outcome
Fewer missed follow-ups
Cleaner CRM, faster booking, and a better founder sales handoff.
Approval-first deposit link
Writes to Twenty CRM
07 / 14
Product Wedge
Start with the AI-readiness audit, expand into agency operations
AI WORKFLOW AUDIT
→
Enquiry follow-up
→
Call summaries → CRM
→
Appraisal nurture
→
Supervised ops agent
What the audit does
- Maps the agency's admin-heavy workflows.
- Identifies where AI can safely assist.
- Checks CRM, calendar, inbox, call, and data readiness.
- Defines approval rules and escalation points.
- Produces the first implementation plan.
Expansion workflows
- Email classification and draft replies.
- Call summaries into CRM notes and tasks.
- Vendor report drafts and appraisal drip nurture.
- Prospecting and principal outreach.
- Full supervised operations agent.
Investor takeawayThe audit is both a paid qualification product and a discovery engine for repeatable implementation.
08 / 14
Pilot Blueprint
The full product surface comes from a real agency blueprint
The first deep implementation blueprint is a 13-module supervised operations system around the tools real agents already use.
Front office
- Email management and reply drafting.
- Document sending workflows.
- Inspection booking.
- SMS reply and prospecting response handling.
Admin layer
- Calendar and task creation.
- Call transcription and notes.
- CRM update and admin support.
- Appraisal drip nurture.
Growth layer
- Buyer feedback and vendor report drafts.
- Social content support.
- Competitor tracking.
- Buyer-to-listing matching.
- Listing description drafting.
Paid setup + monthly support retainer
Investor takeawayWe start narrow, but the account expansion map is already visible.
09 / 14
Business Model
Setup revenue funds implementation. Retainers compound support revenue.
| Package | Setup | Monthly | Best fit |
|---|
| Lead Machine | $2,500 | $197 | Solo agents starting outbound and follow-up |
| Pipeline Dominator | $5,000 | $397 | Agents with active pipeline and CRM pain |
| Full Stack Agent | $10,000 | $797 | High-output agents needing broader automation |
| Agency System | $30,000 | $2,500 | Offices or teams with multiple workflows |
| Pilot Blueprint | $12,000 | $1,200 | First deep implementation reference case |
Investor takeawayThis is not a free-trial SaaS motion at the start. It is founder-led implementation with cash up front and recurring support revenue.
10 / 14
Go To Market
Founder-led sales into a narrow, reachable real estate ICP
Initial ICP
- Australian residential real estate agents.
- Principals or high-performing agents with admin bottlenecks.
- Agencies already using CRM, calendar, phone, email, and listing workflows.
- Customers willing to pay for implementation, not just software access.
Channels
- Founder network and warm introductions.
- One cold caller qualifying real estate agents.
- Website call funnel handled by Karen.
- Targeted principal lists.
- AI Workflow Audit as the conversion offer.
- First 10 pilot agents as implementation proof.
Sales motion
- Qualify pain.
- Audit workflow.
- Book founder call.
- Close setup + retainer.
11 / 14
Use Of Funds
$50,000 funds the first repeatable operating base
Operations hub / warehouse lease
$18,000
Server & AI infrastructure
$12,000
Sales & lead generation
$8,000
Implementation & integrations
$7,000
Legal, compliance, insurance
$3,000
Investor takeawayThe raise is not for research. It funds customer acquisition, customer delivery, and proof.
12 / 14
90-Day Milestones
The next milestone is proof of repeatability
Targets within 90 days of funding
- Close 10 paying real estate customers.
- Deliver the first deep agency pilot.
- Convert the AI Workflow Audit into a repeatable offer.
- Build implementation playbooks for the first 5 workflows.
- Target setup revenue of $120,000–$300,000 depending on package mix.
- Target MRR of $12,000–$25,000.
Target
Proof investors should expect
- Signed customers.
- Live workflow usage.
- CRM / calendar / call logs.
- Retainer conversion.
- Repeatable delivery checklist.
Investor takeawayThe next round should be raised on customer proof, not theory.
13 / 14
Team
Product, sales, workflow, and creative in one fast loop
Built by operators working with the latest agentic AI. Sales conversations show what agents care about, audits show where follow-up breaks, and product work turns those learnings into repeatable systems.
T
Founder · Product, Growth & Operations
Tom
Leads product direction, workflow design, sales strategy, customer discovery, and daily execution — turning messy real estate work into practical AI-assisted systems: call summaries, CRM-ready notes, buyer follow-up, approval queues, and agent dashboards.
D
Co-Founder · AI Systems, Operations & Delivery
Deandre
Brisbane-based developer and AI specialist with six years building real systems for real businesses — AI agents, workflow automation, custom dev tools, and infrastructure. Owns AI systems, delivery, and customer workflow scoping.
X
Real Estate Sales & Growth
Xavier
Brings real estate sales experience into outreach, agent conversations, discovery, and pipeline — getting the product in front of agents, principals, and agency operators dealing with missed leads and messy follow-up.
◆
Performance Creative · Paid Ads
Creative Lead
Direct-response creative around real agent pain — missed enquiries, slow speed-to-lead, open-home follow-up, CRM cleanup, and call notes — across Facebook, Instagram, TikTok, Reels, and Messenger.
Why the team worksFounder-led real estate sales, AI delivery, and performance distribution under one roof — a fast learning loop that keeps the product close to real workflows instead of AI hype.
14 / 14
The Ask
We are raising $50,000 to turn a working system into a fundable company
What exists
Working agent, CRM, calendar booking, lead capture, outreach workflows, and the first product blueprint.
What capital unlocks
Reliable infrastructure, a focused sales motion, implementation capacity, and the first 10 paying customers.
Why us · product
Already built, not slideware
A working agent, live CRM, calendar booking, and lead capture exist today — capital buys reliability and delivery, not invention.
Why us · trust
Approval-first by design
Built for an industry where brand and relationships matter. Agents stay in control, which is the wedge competitors built on full automation can't easily copy.
Why us · distribution
Founder-led real estate access
Real estate sales, AI delivery, and performance creative under one roof — a direct line to the exact ICP we're selling.
CloseAussie Real Estate AI is building the operating layer real estate agents will trust before they trust full automation.
Appendix
Claim discipline, safety model, demo script
A · Claim discipline
Live, roadmap, and target claims are visually separated throughout this deck.
LiveTargetRoadmap
B · Safety model
AI drafts. Agent approves. System logs.
Approval-first for: SMS, email, vendor reports, social posts, property documents, outbound calls, public publishing.
Approval-first
C · Demo script
- Website lead submission enters CRM.
- Karen qualifies the lead.
- Karen creates CRM note and task.
- Karen books Google Calendar event with Meet link.
- Dashboard shows status and next action.
Confidential · Not for distribution without signed NDA · Targets and projections are not guarantees