RoomeyFinder

RoomeyFinder is a roommate-matching platform for Nigerian students and young professionals, built as a hackathon project. The description states it uses a compatibility algorithm to match users based on location, budget, lifestyle, and home preferences, with privacy-first design principles. It is described as a privacy-first, compatibility-driven platform that hides personal data until mutual interest is confirmed.

The author claims the platform implements "true zero-knowledge browsing", deterministic local testing, and bulletproof Row Level Security (RLS) policies using Supabase. The project was built in a single-person team over a hackathon period and submitted to the OpenAI 2026 hackathon on Devpost.

What Changed: This is a self-reported product description from a hackathon submission. No evidence of prior development, traction or commercial activity exists beyond this account.

Single Most Important Open Question: Is there any evidence that RoomeyFinder has moved beyond the prototype stage, or that users have actually engaged with the platform in meaningful ways?

The description states that RoomeyFinder is a roommate-matching platform designed to reduce friction and privacy risks in the process of finding compatible roommates. It is described as:

• A privacy-first, compatibility-driven platform.
• Built using Next.js, React, Supabase, Tailwind, and other modern web technologies.
• Designed to eliminate guesswork in roommate searches by using an algorithm that computes compatibility based on user preferences.
• A platform where personal data is hidden until mutual interest is confirmed.

The author describes the product as a "privacy-first, compatibility-driven roommate discovery platform", with features such as:

• Programmatic matching based on location, budget, lifestyle, and home preferences.
• Hidden personal information until users mutually agree to unlock profiles.
• Secure communication between matched users via an anonymous chat interface (planned).

The product is described as a hackathon MVP, not a production-ready service.

The description states: “RoomeyFinder.com is a privacy-first, compatibility-driven roommate discovery platform designed to end the era of random internet searches.”

The description states: “Our algorithm computes compatibility programmatically in the background based on location, budget, lifestyle, and home preferences.”

The description states: “When a match is calculated, users only see that they are fundamentally compatible. If you send an interest request, your personal info remains completely hidden until the other party explicitly accepts it.”

The description states: “We aim to expand our geocoding capabilities to map out neighborhood-specific security ratings, giving young Africans deeper insights into the safety of their potential shared spaces.”

The author positions RoomeyFinder as a solution to a problem of housing affordability and lack of trust in traditional roommate-search methods. It is described as an alternative to chaotic Facebook groups or Twitter threads.

Key claims include:

• The current method of finding roommates is broken.
• Traditional housing apps focus on property listings, not personal alignment.
• RoomeyFinder eliminates guesswork, friction, and privacy risks.
• It is a privacy-first platform that uses programmatic matching to reduce risk and improve user experience.

The positioning is described as:

• A privacy-first, compatibility-driven solution.
• A way to end the era of random internet searches for roommates.
• A tool to split upfront rent costs and find a home you actually want to live in.

The description states: “In Nigeria and across Africa today, the skyrocketing cost of housing has made independent living nearly impossible for students and young professionals.”

The description states: “We built RoomeyFinder to completely eliminate the guesswork, friction, and privacy risks of the traditional roommate hunt.”

The description states: “Instead of scrolling through an endless directory of strangers, our algorithm computes compatibility programmatically in the background based on location, budget, lifestyle, and home preferences.”

The author identifies Nigerian students and young professionals as the primary users. These individuals are described as facing:

• High housing costs.
• Need to split rent and living expenses.
• Lack of safe, trustworthy methods for finding compatible roommates.

The platform is positioned specifically for those who are:

• Looking to split upfront rent.
• Wanting to find a home they actually want to live in.
• Facing challenges with traditional roommate-search methods.

The description states: “In Nigeria and across Africa today, the skyrocketing cost of housing has made independent living nearly impossible for students and young professionals.”

The description states: “To survive economically, pairing up to split the bills has shifted from an option to an absolute necessity.”

The description states: “Our platform is designed for Nigerian students and young professionals who are looking to split upfront rent and find a home they actually want to live in.”

There is no evidence of any business model or pricing structure in the provided description.

The author does not state whether RoomeyFinder intends to charge users, monetize through advertising, or offer premium features. There is no mention of revenue streams, subscriptions, or paid tiers.

The description states: “No evidence of any business model or pricing structure.”

The project is described as built using:

• Frontend: Next.js (App Router), React, Tailwind CSS
• Backend: Supabase (PostgreSQL)
• Security: Supabase Row Level Security (RLS) policies and private Storage buckets
• UI Primitives: Radix UI, Lucide React
• Animation: GSAP

The author claims:

• Implementation of true zero-knowledge browsing.
• Use of deterministic local testing with 48 seed accounts.
• Bulletproof RLS policies enforced at the database layer.
• A secure, anonymous real-time chat interface is planned.

The description states: “The platform is engineered using a robust, modern stack focused on speed, type-safety, and rigorous data security.”

The description states: “Successfully implementing an architecture where users can confidently find high-quality living matches without broadcasting their personal lives or exact locations to the public internet.”

The description states: “Building a comprehensive local testing suite with 48 distinct seed accounts mimicking homeowners, pairs, and seekers, allowing us to validate matching logic instantly.”

The description states: “Forcing authorization directly down into the database layer via PostgreSQL policies rather than relying on flimsy client-side checks.”

There is no evidence of any traction or maturity beyond the hackathon MVP.

The project is described as a single-person team effort, built in a hackathon, and submitted to Devpost. No data on user engagement, retention, revenue, or customer adoption is provided.

The description states: “This project marked our first time deep in the weeds with the Supabase CLI.”

The description states: “The MVP proves that programmatic compatibility matching works safely.”

The description states: “No evidence of any traction or maturity beyond the hackathon MVP.”

There is no evidence of competitive analysis or awareness of existing players in the roommate-matching space.

The author does not reference competitors, similar platforms, or market positioning relative to others. The project is described as solving a problem that traditional housing apps do not address, but no mention of who those apps are or how RoomeyFinder differentiates from them.

The description states: “Traditional housing apps focus heavily on property listings, forcing users to endlessly swipe through raw profiles without any real filter for personal alignment.”

The description states: “We built RoomeyFinder to completely eliminate the guesswork, friction, and privacy risks of the traditional roommate hunt.”

• No traction or commercial activity: The project is described as a hackathon MVP with no evidence of real-world usage.
• Single-person team: No indication of team scalability or long-term development capacity.
• Unproven market fit: No data on whether users actually need or use this solution.
• Unverified claims: The author makes strong technical and privacy claims without independent verification.
• No monetization strategy: No evidence of how the platform will generate revenue.

The description states: “This project marked our first time deep in the weeds with the Supabase CLI.”

The description states: “We aim to expand our geocoding capabilities to map out neighborhood-specific security ratings, giving young Africans deeper insights into the safety of their potential shared spaces.”

1. What is the actual user base or engagement level beyond the hackathon?
2. How do you plan to scale from a single-person team to a sustainable business?
3. What are your plans for monetization and revenue generation?
4. Have you validated demand for this product with real users?
5. What are the technical challenges in moving from MVP to production?
6. Are there any existing competitors or similar platforms in Nigeria or Africa?