Property listing parsing
Listings are collected on your filters, the same property is collapsed into one object, and price, time on the market and removal are written into a history.
- Buildfrom $1,400
- Timeline1–3 weeks
- Supportfrom $420/mo
Who this suits: Agencies, investors and developers who see one property as five listings from five agents and cannot say how long it has stood or how often its price moved.
What is in the first version
- search filters
- listing merges
- price history
- alerts
The figures above are the package this sits on: Parsing and reverse engineering. Anything past its edges the calculator adds before the work starts, not after.
How the path goes
- 01
The feed is read on filters
A pass separates a listing that appeared, changed or vanished, and that distinction is made at collection, not reconstructed later.
- 02
Listings collapse into a property
Address, floor, area and layout line up: five agents, one flat, one record, with price history kept against the property.
- 03
The history outlives the listing
Removal is an event, not a gap: the property keeps its time standing, its price moves and any return.
What decides whether this works or annoys people
A repost makes no new property
A repost resets the publication date, so time listed is counted from the property’s first appearance in your own base instead.
Merging goes wrong in both directions
A missed merge inflates the market, an extra one mixes two histories: only strong matches merge, and any merge can be undone.
Asking price is not sale price
Listings say what was asked and how often it was cut, not what was paid: the figure is labelled an asking price.
What to measure once it is live
- listings collapsed into properties automatically
- doubtful merges waiting on a person
- time from a listing appearing to the alert
- properties with an unbroken price history
Why this comes out faster
The shape of this one is known: the states, the edge cases and the things that usually go wrong have been decided before. Nothing here is a template, and the saving is not in your half of the work. It goes into your process, your content and the systems this has to talk to, which is the part nobody can have solved in advance.
A likely stack for this
Picked against the task when we scope it, not decided in advance. This is the shelf it usually comes off.
- CollectionPythonPlaywrightGoDocker
- Merging and historyPostgreSQLClickHousepgvectorOpenAIRedisS3
- Schedule and alertsTemporaln8nTelegram Bot APIGrafana
Price it yourself, right here
Five steps, and you can see the number without leaving a contact. The estimate accounts for the kind of work, what you already have and what it will need inside.
These bills do not come from us
- proxies and captcha services for closed sites
- geocoding and maps
- AI model calls comparing listing descriptions
- hosting and storage for the photo history
Asked before the first call
- Is this legal?
- The public parameters of a property and its asking price generally are. Phone numbers, names and anything that makes a contact base we do not collect: separate regulation, checked per site before the estimate.
- How accurate is the duplicate merging?
- We name no share before seeing your city and sites. What we commit to: only strong matches merge automatically, doubtful ones go to a person, the share is on screen, any merge can be undone.
- Will we get actual transaction prices?
- No, and no collection of listings gives them: the system shows the asking price, its cuts and time standing, which is enough to see overpriced lots. Registry data is a separate conversation.