StrataRisk.com

AI-powered due diligence that reveals hidden short-term rental risks in strata buildings before you buy

Score: 6.1/10BJMedium Build
Brand Colors

The Opportunity

Problem

Apartment buyers inherit costly, hard-to-fix problems from unregulated short-term letting when the body corporate lacks proper controls.

Solution

Prospective buyers upload body corporate documents, meeting minutes, and bylaws. Our RAG system analyzes them against known short-term letting red flags and public listing data to deliver an instant risk score, projected cost exposure, and plain-English report. Investors track buildings over time and receive alerts if new STR activity appears.

Target Audience

Prospective apartment buyers and investors in strata-titled buildings in short-term rental hotspots

Differentiator

The only tool combining document RAG analysis with real-time STR listing monitoring specifically for strata buyers — competitors are either generic home inspectors or host-focused AirDNA tools.

Brand Voice

professional

Features

Document Upload & Parsing

must-have35h

Secure upload of PDFs, meeting minutes, and bylaws with automatic OCR and chunking

RAG Risk Analysis

must-have65h

AI extracts STR rules, enforcement history, and risk indicators using embeddings

Risk Scoring Engine

must-have25h

Generates 1-100 risk score with weighted factors and cost projections

Professional PDF Reports

must-have30h

Branded, downloadable reports with executive summary and supporting evidence

Building Dashboard

must-have40h

Track multiple buildings with historical risk trends

STR Listing Monitor

must-have45h

Periodic scans for new short-term rental listings in the building

Email Alerts

nice-to-have20h

Notifications when risk profile changes or new listings appear

Comparable Buildings

nice-to-have30h

Benchmark against similar buildings in the same suburb

White-label Reports

nice-to-have25h

Buyer's agents can brand and send reports to clients

Predictive Levy Forecasting

future60h

Machine learning model predicting future special levies

Total Build Time: 375 hours

Database Schema

users

ColumnTypeNullable
iduuidNo
emailtextNo
roletextNo
created_attimestampNo

Relationships:

  • subscriptions.user_id references users.id
  • properties.user_id references users.id

properties

ColumnTypeNullable
iduuidNo
addresstextNo
suburbtextNo
risk_scoreintYes
user_iduuidNo
created_attimestampNo

Relationships:

  • reports.property_id references properties.id
  • properties.user_id references users.id

reports

ColumnTypeNullable
iduuidNo
property_iduuidNo
risk_scoreintNo
findingstextYes
pdf_urltextYes
created_attimestampNo

Relationships:

  • reports.property_id references properties.id

document_chunks

ColumnTypeNullable
iduuidNo
report_iduuidNo
contenttextNo
embeddingvectorYes
created_attimestampNo

Relationships:

  • document_chunks.report_id references reports.id

API Endpoints

POST
/api/properties

Create new property and trigger analysis

🔒 Auth Required
POST
/api/upload

Upload and chunk document for RAG

🔒 Auth Required
POST
/api/analyze

Trigger OpenAI RAG analysis

🔒 Auth Required
GET
/api/reports/[id]

Retrieve report with findings

🔒 Auth Required
GET
/api/alerts

Fetch user alerts and notifications

🔒 Auth Required
POST
/api/subscribe

Create Stripe subscription

🔒 Auth Required

Tech Stack

Frontend
Next.js 14 + Tailwind + shadcn/ui
Backend
Next.js API routes + LangChain.js
Database
PostgreSQL with pgvector (Neon)
Auth
Clerk
Payments
Stripe
Hosting
Vercel
Additional Tools
OpenAIResendpdf-lib

Build Timeline

Week 1: Foundation and auth

42h
  • Landing page
  • Clerk auth
  • Database schema
  • Basic dashboard

Week 2: Document processing pipeline

55h
  • Upload flow
  • PDF parsing
  • Chunking logic
  • pgvector setup

Week 3: RAG and AI core

48h
  • LangChain integration
  • Embedding pipeline
  • Risk scoring algorithm

Week 4: Report generation

38h
  • Interactive report UI
  • PDF export
  • Email delivery

Week 5: Monitoring and alerts

35h
  • Building watchlist
  • Listing scanner stub
  • Alert system

Week 6: Payments and polish

32h
  • Stripe integration
  • Pricing tiers
  • Onboarding flow

Week 7: Testing and data

28h
  • Seeded test buildings
  • End-to-end tests
  • SEO optimization

Week 8: Pre-launch

22h
  • Landing page A/B tests
  • First three customer onboarding system
  • Documentation
Total Timeline: 8 weeks • 337 hours

Pricing Tiers

Starter

$0/mo

Limited to 1 building

  • 1 report per month
  • Basic risk score
  • Community data only

Pro

$25/mo

Up to 10 buildings

  • Unlimited reports
  • Full RAG analysis
  • Monitoring alerts
  • PDF reports
  • Email support

Investor

$49/mo

Unlimited buildings

  • Everything in Pro
  • Portfolio dashboard
  • White-label reports
  • Priority support
  • API access

Revenue Projections

MonthUsersConversionMRRARR
Month 118012%$540$6,480
Month 61,45019%$6,885$82,620

Unit Economics

$42
CAC
$840
LTV
4.5%
Churn
83%
Margin
LTV:CAC Ratio: 20.0xExcellent!

Landing Page Copy

Don't inherit someone else's Airbnb nightmare

Upload your strata docs and get an AI-powered risk report in minutes. Know exactly what you're buying.

Feature Highlights

Instant STR risk scoring
Projected repair costs
Regulatory red flags
Real-time listing monitoring

Social Proof (Placeholders)

"Saved me from a $47k special levy on a property I almost bought. This is gold. - Michael Chen, Melbourne"
"As a buyer's agent I now require every client to run a StrataRisk report. - Sarah Patel"

First Three Customers

Offer 50 free comprehensive reports to buyer's agents in Sydney and Melbourne via LinkedIn outreach in exchange for video testimonials and referrals. Post case studies in Australian Property Investors Facebook groups (targeting strata owners). Partner with 2-3 active real estate agencies in short-term rental hotspots like Byron Bay who can white-label the reports.

Launch Channels

Product HuntIndie Hackersr/AusPropertyr/strataLinkedIn Property Investment groupsTwitter/X threads on Australian real estate

SEO Keywords

strata short term rental riskcheck airbnb issues before buying apartmentbody corporate airbnb problemsstrata title due diligenceavoid special levies airbnb

Competitive Analysis

AirDNA

airdna.co
Subscription $200+/mo
Strength

Excellent market data for hosts

Weakness

Not built for buyers or strata documents

Our Advantage

Buyer-first focus with document intelligence

strata Community Forums

flat-chat.com.au
Free
Strength

Local knowledge

Weakness

Unstructured, anecdotal, time-consuming

Our Advantage

Structured, instant, AI-analyzed

🏰 Moat Strategy

Data moat — every uploaded document improves the embedding database and risk model. Network effects as more users contribute building intelligence.

⏰ Why Now?

Multiple Australian states have introduced or tightened STR regulations in 2023-2024, dramatically increasing financial risk for buyers who inherit poorly governed buildings.

Risks & Mitigation

legalhigh severity

Liability if report misses major issue leading to buyer loss

Mitigation

Prominent disclaimers, insurance, and 'for information only' positioning

technicalmedium severity

AI hallucinations in document analysis

Mitigation

Human review option for paid tier + rigorous prompt engineering

marketmedium severity

Buyers unwilling to pay $25/mo

Mitigation

Strong free tier with clear upgrade triggers during purchase process

Validation Roadmap

pre-build14 days

Interview 25 prospective apartment buyers and buyer's agents

Success: At least 18 confirm they would pay for this report

mvp21 days

Launch waitlist and collect 100 email signups with survey

Success: 30% of respondents say they are 'very likely' to purchase

launch45 days

Acquire first 30 paying users through targeted outreach

Success: Achieve $750 MRR and 4.5+ NPS

Pivot Options

  • Pivot to full-service strata management SaaS for body corporates
  • Focus exclusively on buyer's agents as white-label customers
  • Expand into vacation home due diligence in the US market

Quick Stats

Build Time
337h
Target MRR (6 mo)
$7,500
Market Size
$28.0M
Features
10
Database Tables
4
API Endpoints
6