Residenta — AI-Powered Property Management SaaS
Built Residenta — a full-stack AI-powered property management SaaS that replaces fragmented spreadsheets and email-based workflows with centralised lease management, AI maintenance ticket classification, predictive maintenance forecasting, financial tracking, a resident self-service portal, and real-time notifications. Designed to scale from 10 units to 10,000 with the same team size.
Client
Residenta
Project Value
$90,000+
Rating
The Challenge
Property managers and landlords were operating with a fragmented toolset — tenant communication scattered across emails and calls, maintenance requests tracked in spreadsheets, rent collection manual and without visibility, and zero predictive insight into upcoming issues. As portfolios grew from 10 to 100+ units, manual processes collapsed: maintenance requests were missed, lease renewals expired without action, rent reminders required individual follow-up per tenant, and there was no structured way for residents to self-serve. The market lacked an affordable, modern platform that could handle the full operational lifecycle for both small landlords and mid-market property companies without an enterprise-level contract.
The Goal
Design and ship a production-grade property management SaaS with multi-property and multi-unit management, full lease lifecycle (create, renew, bulk renew, expire), AI-powered maintenance ticket classification, predictive maintenance forecasting, financial tracking (payments, invoices, overdue management), a resident self-service portal, real-time in-app notifications, automated daily cron jobs for rent reminders and lease alerts, a document hub, and three-role RBAC (Admin, Manager, Resident) — with full dark mode and responsive design.
Solution & Implementation
1Analysis
Conducted discovery with property managers, independent landlords, and residents across residential and mixed-use portfolios to map the full property operations lifecycle. Identified seven critical workflow failures: no centralised maintenance request intake, manual lease renewal tracking with high miss rates, reactive maintenance costing 3–5x more than scheduled repairs, rent collection requiring individual follow-up, no resident self-service causing high support volume, zero document organisation, and no role separation meaning residents had access to admin data.
2Designing Solution
Selected React 18 with TypeScript, Vite, Tailwind CSS, and shadcn/ui for the frontend — delivering a responsive, dark-mode-capable SPA with Framer Motion animations. TanStack React Query manages all server state with intelligent cache invalidation. Recharts powers financial charts and occupancy visualisations. The entire backend runs on Supabase: PostgreSQL with RLS for data isolation, Auth, Storage for document uploads and avatars, Realtime for in-app notifications, and Edge Functions for AI operations and automated notification dispatch. A configurable AI provider (OpenAI-compatible) powers ticket classification, financial insights, the lease assistant chatbot, and maintenance predictions.
3Customizing Business Logic
The dashboard presents real-time KPI cards (Occupancy Rate, Monthly Revenue, Active Tickets, Total Properties) with animated counters, a collection progress tracker, and a portfolio-wide activity feed. Lease management covers the full lifecycle including bulk renewal — select multiple expiring leases and process in one action with custom terms. AI ticket classification automatically assigns category (plumbing, electrical, HVAC, structural, appliance, pest control, general) and priority (low, medium, high, urgent) to every incoming request without manager triage. The resident portal gives tenants self-service access: submit and track maintenance tickets, view lease and payment history, read announcements, and receive real-time notifications.
4Scale & Optimize
Three automated daily cron jobs (via pg_cron calling Edge Functions) handle: overdue invoice marking with tenant notification, expiring lease alerts for leases within 30 days (deduplicated weekly), and rent due reminders 3 days before payment dates. The AI Lease Assistant chatbot is context-aware — knowing tenant name, rent, deposit, and dates per lease to answer resident and manager questions accurately. Predictive Maintenance analyses ticket history per unit and surfaces upcoming issue predictions with confidence scores and predicted dates — enabling scheduled repairs before failures occur.
Results & Impact
Maintenance Resolution
Rent Collection Rate
Lease Renewal Misses
Resident Support Volume
Portfolio Scale
AI-powered maintenance ticket classification auto-assigns category and priority to every incoming request — eliminating manual triage and routing to the right technician instantly
Predictive maintenance AI analyses ticket history per unit and forecasts upcoming issues with confidence scores — enabling scheduled repairs before costly emergency breakdowns
Bulk lease renewal — select multiple expiring leases and process in one action with custom terms, preventing the miss rates that cause revenue loss
Three automated daily cron jobs handle overdue invoice marking, expiring lease alerts (30-day advance), and rent reminders (3-day advance) with full deduplication logic
Real-time in-app notifications via Supabase Realtime — residents receive overdue payment alerts, lease expiry notices, and ticket status updates instantly
Context-aware AI Lease Assistant chatbot knows tenant name, rent, deposit, and dates per lease — answering questions without manual data lookup
Resident self-service portal reduces inbound manager queries by 45% — tenants submit tickets, track status, and view payment history without calling the office
Three-role RBAC enforced at PostgreSQL RLS layer — residents access only their own unit data; managers never see another organisation's portfolio
Key Technologies
Project Gallery
"Residenta replaced everything we were doing manually. Maintenance requests get classified and assigned automatically, lease renewals never slip through, and our residents use the portal instead of calling us. We manage twice as many units with the same team."
Residenta
Residenta
Frequently Asked Questions
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