nBases — Off-Market Monthly Rentals, Booked Direct

The best homes are never on Airbnb. They sit in local agency inboxes, WhatsApp groups and property-manager spreadsheets. nBases collects them city by city and hands the contact straight to the renter. No platform fee, no markup.

Where it stands today

2,361

homes listed

cities live

1–6

months per stay

platform fee

Direct contact with the host, agent or property manager — WhatsApp, Telegram or email
Foxie, an AI agent that rates every home on remote-work criteria: workstation, connectivity, amenities
Supply seeded city by city through property-manager partnerships
Curated collections: remote-work ready, full workstation, budget

nBases listing page — monthly price and direct contact with the host

Four pivots, one thesis

Same conviction every time — long stays are chosen on information the listing never gives you. Four attempts to find the model that pays for it.

Manual validation

Negotiated and upgraded apartments myself, closed the first bookings by hand. Nomads pay for vetted longer stays.

AI scoring + Chrome extension

Scored Airbnb listings on remote-work criteria and shipped an extension that rated them in place. The value was the judgment, not the storefront.

Widget SaaS for property managers

Sold the score back to property managers as a conversion widget. They would not pay for conversion lift they could not attribute.

Direct aggregator

Killed the middleman entirely: bring supply, expose the contact, take no fee. The first model where both sides had an obvious reason to show up.

Earlier version — AI-scored listings site

Version 2 — AI-scored listings

Earlier version — scoring widget for property managers

Version 3 — widget SaaS

My Role

Founder. Product builder. Full-stack growth owner.

What I Delivered

•Shipped 4 product versions (Next.js, Supabase, Stripe, PostHog)
•Designed and coded the full product and brand
•Built the AI scoring models — workstation, cleanliness, amenities
•Sourced 2,361 listings across 21 cities and 5 regions
•Launched city-based GTMs (landing pages, Meta Ads, CAPI, funnels)
•Negotiated partnerships covering 250+ units

Impact

•$3–$6 CPL depending on city
•Demand validated in Buenos Aires, Lisbon and Tbilisi
•Chrome extension shipped and iterated with real users

What it cost me to learn

For months the H1 said “mid-term rentals” while the market typed “monthly rentals”. A positioning gap no ad budget fixes — and the kind of thing I now check on day one of any GTM.

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