Predict and prevent special levies caused by unregulated short-term rentals
Apartment buyers inherit costly, hard-to-fix problems from unregulated short-term letting when the body corporate lacks proper controls.
LevyGuard uses building characteristics, body corporate rules, and historical levy data to simulate potential future costs from short-term rental damage and poor regulation. Investors receive actionable recommendations to either avoid the building or push for better controls before purchasing.
Prospective apartment buyers and investors in strata-titled buildings in short-term rental hotspots
The only simulation platform that quantifies dollar impact of missing strata controls — turns vague risk into concrete financial forecasts.
supportive
What-if engine that models different STR policy scenarios
Projects probability and size of future special levies
Structured intake form covering bylaws, facilities, and history
Specific actions to mitigate risk (e.g. push for 90-day minimum stay rule)
Aggregate view of all watched buildings with total exposure
Crowdsourced and public data on past strata levies by building type
Ready-to-use motions for body corporate meetings
Share simulation results with buyer's agents and solicitors
Connect users with insurers who understand strata STR risk
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| text | No | |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| name | text | No |
| suburb | text | No |
| units | int | Yes |
| has_str_rules | bool | Yes |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| building_id | uuid | No |
| projected_levy_5yr | int | No |
| risk_level | text | No |
| created_at | timestamp | No |
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| building_id | uuid | No |
| amount | int | No |
| reason | text | No |
| year | int | No |
Relationships:
/api/simulateRun new levy simulation
/api/buildingsSearch historical building data
/api/portfolioGet user's portfolio risk overview
/api/recommendationsGet tailored risk mitigation steps
1 building
10 buildings
Unlimited
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 110 | 17% | $470 | $5,640 |
| Month 6 | 980 | 23% | $5,635 | $67,620 |
Our simulator predicts special levies caused by short-term rental damage and weak rules.
Run free workshops for property investment clubs in Brisbane and Sydney demonstrating the simulator live. Offer the first 15 users lifetime Investor access for detailed feedback and testimonials. Partner with strata lawyers who can refer clients before purchases are finalized.
Traditional strata management
No predictive analytics or simulation
Quantitative forward-looking risk modeling
Broad building inspections
Ignore regulatory and STR dynamics
STR-specific financial simulation
Proprietary historical levy database combined with simulation model that becomes more accurate with every user contribution.
Rising construction costs and increasing STR density have caused a surge in special levies across Australia in the past 24 months, creating urgent demand for prediction tools.
Inaccurate levy predictions damage reputation
Clear disclaimers that outputs are estimates, not guarantees. Use ranges instead of single numbers.
Investors prefer human advice over algorithms
Position as decision support tool for professionals, not replacement
Solo dev bandwidth for data collection
Start with public data and community contributions, expand gradually
Success: 75% report unexpected costs or fear of them
Success: 25 paid conversions from beta users
Success: Organic traffic >800 visitors/month with 8% conversion
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