Hearth

An agent for London renters

Every London rental, read for you.

Hearth crawls 18 property sources every day, reads each listing and its photos the way I would, and only messages me about the flats that fit my brief. Everything else stays quiet.

  • 18property sources
  • 3scoring passes
  • 85+score for an instant alert
  • 14 daysbefore a flat is ever suggested twice

Hearth now

New match, score 91

Two-bed flat with a private balcony, 6 minutes on foot to an Overground station. Bright south-facing living room; the floorplan shows a separate kitchen.

ShortlistReject
An instant alert. This listing is made up.

How it works

Cheap, certain checks run first. The expensive model only reads what survives them.

  1. 1

    Crawl

    Every morning Hearth collects listings from portals, estate agents and build-to-rent operators. One universal extractor reads them all: structured listing data first, then page data, then OpenGraph tags, then plain heuristics.

  2. 2

    Filter

    Hard rules drop anything that misses the brief: bedrooms, bathrooms, price per bedroom, property type, area, furnished, and phrases I never want to see, such as "shared ownership".

  3. 3

    Score

    A free keyword score gates the language model. Survivors get a text read of the description and a vision read of the photos and floorplan, then a composite score out of 100.

  4. 4

    Check

    Duplicates across sites are merged into one flat. Before anything is sent, every link is checked, so a let-agreed listing never reaches me.

  5. 5

    Alert

    One email and one Telegram digest each morning, a weekly summary on Sundays, and an instant Telegram alert with Shortlist and Reject buttons for anything scoring 85 or more.

Try the scoring

Six made-up listings, scored the way Hearth scores them. Move the threshold to see which ones would make the morning digest.

Description 35% Photos 30% Transport 20% Floorplan 15%

4 of 6 listings would be sent; 1 would also trigger an instant alert.

  • Two-bed flat with balcony

    91

    2 bed · 1 bath · 6 min walk to an Overground station

    Description
    88
    Photos
    94
    Transport
    92
    Floorplan
    90

    Bright living room facing south, separate kitchen, private balcony, recently refurbished bathroom.

    Instant alert, and in the morning digest

  • Three-bed maisonette with garden

    82

    3 bed · 2 bath · 9 min walk to a Tube station

    Description
    85
    Photos
    80
    Transport
    78
    Floorplan
    84

    Own front door and a small garden. Photos show dated kitchen units, which costs a few points.

    In the morning digest

  • New-build two-bed with concierge

    76

    2 bed · 2 bath · 11 min walk to a rail station

    Description
    80
    Photos
    78
    Transport
    66
    Floorplan
    76

    Gym and concierge in the building. Open-plan kitchen and a walk at the edge of the limit.

    In the morning digest

  • Two-bed mansion block flat

    71

    2 bed · 1 bath · 4 min walk to a Tube station

    Description
    72
    Photos
    62
    Transport
    96
    Floorplan
    55

    Great location, but the photos are dark and the second bedroom is a box room on the floorplan.

    In the morning digest

  • Three-bed flat above a shop

    58

    3 bed · 1 bath · 8 min walk to a Tube station

    Description
    60
    Photos
    48
    Transport
    80
    Floorplan
    42

    Busy main road, small windows in two bedrooms, and the description says "some updating required".

    Stays quiet

  • Two-bed with a long walk

    44

    2 bed · 1 bath · 19 min walk to the nearest station

    Description
    60
    Photos
    52
    Transport
    0
    Floorplan
    48

    A decent flat, but the walk to a station scores zero and drags the total down.

    Stays quiet

Every listing on this page is made up. Real listings stay private.

Where it looks

Portals catch most flats. Estate agents and build-to-rent operators often list on their own sites first.

Portals

  • Rightmove
  • Zoopla
  • OnTheMarket
  • OpenRent
  • PrimeLocation
  • Foxtons

Estate agents

  • Kinleigh Folkard & Hayward
  • Hamptons
  • Winkworth
  • Strutt & Parker
  • BlackKatz
  • Lurot Brand

Build to rent

  • Get Living
  • Quintain Living
  • Battersea Power Station
  • Way of Life
  • NHG Homes
  • Greystar UK

Adding a new agent is about five lines of configuration. The universal extractor does the parsing.

Under the hood

Spending model calls only where they matter

Each filter cuts language-model work before it happens.
StepWhat it saves
Hard rulesFailing listings never reach a model
Keyword gateAbout 30% of model calls
Content-hash cacheAbout half of re-scores reuse an earlier result
Description budgetAbout half the input tokens

Together that is roughly 60 to 70% less model spend than scoring every listing.

The stack

  • APIPython, FastAPI and SQLite on a small always-on cloud VM
  • CrawlersA daily VM job, plus GitHub Actions for the sites that block datacentre addresses
  • TextClaude Haiku reads each description against the brief
  • VisionClaude Sonnet looks at up to six photos and the floorplan
  • TransportTfL journey data, with a fallback to the nearest known station
  • AlertsEmail through Resend and a Telegram bot with inline buttons

Where it stands

Hearth runs for my own flat search, so the code and the real listings stay private. If you want to see how the agent thinks, play Swipe vs the Agent: swipe through twelve made-up flats, then see what Hearth would have picked.