Muhammad Zohaib@mzohaibkhan

LazyNest is an AI-powered home-hunting assistant designed to solve the housing shortage challenge starting in the Netherlands, where over 400,000 homes are missing and buyers must act within hours to secure a viewing. Our system of intelligent agents continuously crawls property sites, filters listings based on personal criteria, scores them with AI, and instantly books viewings—giving house-seekers a real speed advantage in a hyper-competitive market. By automating the search and booking process, LazyNest reduces stress, saves time, and helps buyers beat the crowd. After launching in the Netherlands, we plan to scale across Europe and eventually worldwide, bringing fast, automated home discovery to millions of seekers each year. Users begin by answering a conversational, multi-step questionnaire that defines their ideal property criteria (location, budget, bedroom count, size, etc.). These criteria are then fed into an Opus-powered Crawler Workflow, which monitors real estate websites 24/7. When a matching listing appears, LazyNest instantly surfaces it through a clean, modern interface. With one click, users can book viewings for individual properties—or all matched properties at once. The Opus Booking Workflow handles the entire communication flow behind the scenes, ensuring users are among the first to request a viewing. LazyNest supports English and Dutch, features a responsive UI, and is engineered with a powerful server-centric architecture using Next.js Server Actions. While Genkit currently supports type definitions, the system is designed for future AI-driven enhancements like automated property summarization and smart input validation. * Technology & Category Tags Tech Stack: Next.js (App Router, Server Components) TypeScript Tailwind CSS shadcn/ui Opus Workflows (Crawler + Booking) Vercel Hosting Categories: Real Estate Tech AI Automation Productivity Workflow Automation Web Application Property Search Booking Systems

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