Gulf PropTech Marketplace — PropTech + GenAI
Built a GenAI property assistant that helps investors compare deals, analyze market trends, and automate tenant inquiries.
The problem
- Investors were juggling 4+ portals (DLD data, broker listings, spreadsheets, WhatsApp groups) to evaluate a single deal.
- Agents spent ~60% of their time answering repetitive tenant questions about availability, fees, and documents.
- No single source of truth for unit status — double bookings and stale listings damaged conversion.
The solution
- GenAI deal analyst that ingests listings, transaction history, and rental yield data, then ranks opportunities against an investor's thesis.
- Tenant-facing WhatsApp + web chatbot with retrieval over property docs, contracts, and policies, escalating to a human agent on intent triggers.
- Unified back-office where agents, investors, and tenants share one timeline per unit — replacing scattered spreadsheets and chat threads.
Architecture highlights
React + TanStack Start, server-rendered listing pages for SEO, real-time updates via Supabase channels.
Postgres on Supabase with RLS; nightly ETL from public registry feeds + broker APIs; pgvector for semantic search over listings and documents.
RAG pipeline (chunked listings + policy docs) on OpenAI + Lovable AI Gateway; deal-scoring agent with tool use for comps, yield, and ROI calculators.
WhatsApp Business API + web widget, both routed through one conversation service with human-handoff queue.
Cloudflare Workers for edge APIs, serverless cron for ingestion, observability via Logflare + Sentry.
Measurable outcomes
Indicative figures from the engagement. Exact numbers are placeholders pending client approval to publish.
Let's scope a pilot or a discovery sprint.