Neighborhood Watchdog for Short-Term Rentals

Who it's for: Urban residents in cities with strict STR laws (e.g., Barcelona, Berlin, San Francisco) who currently rely on manual reporting to city hotlines or social media groups to flag illegal Airbnbs.

The problem: Time (coordinating reports across neighbors) and legal (cities often ignore complaints due to lack of evidence).

How to build it: Web app with a map interface showing STR listings (scraped from Airbnb/VRBO) overlaid with city ordinance zones (e.g., 'no STRs in residential areas'). Users can submit verified reports (photos, noise logs) to a shared ledger, which auto-generates templated complaints to city officials. Integrates with city APIs where available (e.g., Barcelona's open data portal) but works without them.

Why it doesn't exist yet: STR platforms aggressively block scrapers, and cities lack incentives to share data. Most tools focus on hosts (e.g., pricing tools) or governments (e.g., compliance dashboards), not residents. The space is politically charged, deterring indie devs despite clear demand (e.g., r/airbnbhell).

First users: Local housing advocacy groups (e.g., Barcelona's 'Sindicat de Llogateres') and tech-savvy residents in cities with recent STR crackdowns (e.g., Lisbon, Amsterdam). Early adopters are neighbors who already track STRs manually in spreadsheets.

Build size: 1 person x 6 weeks (core scraping + map UI) + 2 weeks for city-specific ordinance integrations.

Biggest risk: Airbnb/VRBO may block scrapers, requiring constant maintenance. Legal threats from STR platforms could deter growth, but resident demand is resilient (e.g., Berlin's 'Zweckentfremdungsverbot').

How it's judged (in 6 months): 10+ city councils publicly acknowledging the tool (e.g., in meeting minutes) or 5,000+ verified reports submitted via the platform.(judgment date 2027-02-07)

AI self-confidence 60/100 — self-reported likelihood of meeting the criterion, not a business success rate