FlatSignal.
FlatSignal.
London rental intelligence for the moment that matters. Good flats go before the viewing — this one watches so you don't have to.
Everyone who has hunted for a flat in London knows the feeling: you find the one, you message about a viewing, and it’s already gone. A year and a half ago I was helping someone close to me search for short-term stays, watching that loop play out daily, and thought: this should be a system. Back then I couldn’t build it. Now it takes a day.
FlatSignal watches new London listings on a half-hourly cycle, normalises and dedupes them into distinct properties, and scores each one 0–100 with a deterministic model — preference match, real commute minutes from TfL, value against the rolling area median, freshness, completeness, source confidence. No black box anywhere in the ranking: every score ships with its own breakdown, the weights showing, and a plain-English “why it matched.” When something clears the bar, the phone gets a push with the score, the reasons, and a tap-through to the listing — fast enough to be first in the queue.
The part I’m proudest of is what it refuses to do. There is no compliant public feed of London listings, so FlatSignal doesn’t scrape — it ingests the portals’ own saved-search alert emails from a dedicated inbox, under my own accounts, facts and deep-links only. And the scoring has teeth: a “luxury three-bed” at a too-good-to-be-true rent with MUST-GO-TODAY language gets marked down hard and its warnings carried on every alert — the scam patterns every London renter has met, encoded as penalties. Warnings are never silently dropped.
Ninety-six London areas across eight regions, sectioned the way people actually search. One day’s build — the same architecture as the surf and flight systems: no database, no server, scheduled runs committing their own state to git, a hand-written static dashboard on top. London is deliberately kept out of the core code, so a second city is a config file. New York behaves exactly the same way about good apartments. Just a little thing to help people — you never know where it leads.


