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AI-Assisted Features ​

AI features powered by Claude to reduce friction for tenants and landlords.

Problem: Traditional filter-based search requires users to manually set multiple dropdowns and checkboxes. Many tenants think in natural language.

Solution: A search bar that accepts natural language queries and translates them into structured filters.

Examples:

  • "2 bedroom near Plateau under $1500 pet-friendly" → bedrooms=2, borough=Plateau, maxPrice=150000, isPetFriendly=true
  • "grand 4 1/2 proche du metro" → bedrooms=2, transit proximity filter
  • "furnished studio downtown available March" → propertyType=studio, borough=Ville-Marie, furnished amenity, availableDate

Approach:

  • User types into search bar
  • Backend sends query to Claude with structured output schema
  • Claude returns parsed filters
  • Frontend applies filters to existing listing search
  • Fallback to text search if AI parsing fails

Listing Description Generator ​

Problem: Landlords often write bare-minimum descriptions that don't help tenants make decisions.

Solution: Landlord enters bullet points or key features, AI generates a compelling, well-structured description.

  • Input: "3 bed, renovated kitchen, near Jean-Talon market, hardwood, balcony facing park"
  • Output: Full 2-3 paragraph description highlighting the property's best features
  • Landlord can edit the generated text before saving
  • Optional tone: professional, casual, luxurious

Auto-Translation (FR/EN) ​

Problem: Montreal is bilingual. Listings in only one language miss half the audience.

Solution: On-demand translation of listing descriptions.

  • Tenant clicks "Voir en francais" / "View in English"
  • Backend translates via Claude, caches the result
  • Translations stored in DB alongside original
  • Landlords can review and edit translations

Smart Amenity Tagging ​

Problem: Landlords forget to check amenity toggles even when the description mentions them.

Solution: After landlord writes description, AI suggests amenity tags.

  • Parses description for keywords ("dishwasher", "lave-vaisselle", "balcon", etc.)
  • Suggests tags with confidence indicators
  • Landlord confirms or dismisses suggestions

Neighborhood Summaries ​

Problem: New-to-Montreal tenants don't know neighborhoods.

Solution: AI-generated neighborhood profiles based on aggregated listing data.

  • Average rent by bedroom count
  • Common amenities in the area
  • Description of vibe and character
  • Updated periodically as listings change
  • Displayed on neighborhood filter pages and map