Extraction cases, by source name.
One case file per source — the largest system we run against each of them. Each card opens the full file: what the client needed, what the source put in the way, how the pipeline is built and what the numbers are today.
Ticketmaster
Half a million events on sale, priced continuously
A secondary marketplace cannot price anything without knowing what the primary market is doing right now — but it only needs that for the events that are actually moving.
- price records since 2019
- 210B
- measured coverage
- 99.2%
Zillow
135M properties, and the whole live market daily
The client had been buying a national listings feed for two years. It turned out to be missing roughly a third of the market — not randomly, but systematically, in exactly the segments their investment model cared about.
- property records to date
- 26B
- measured coverage
- 99.1%
Booking.com
1.6M properties, 120M rate quotes a day
A hotel revenue-management product is only as good as its view of the competition, and on an OTA the competitive rate is not a number sitting in a field.
- rate quotes since 2022
- 130B
- rate accuracy
- 99.3%
Amazon
A 180M-SKU competitive catalogue, swept weekly
A repricing engine that runs hourly against week-old data is an expensive way to lose money slowly. The client needed the whole catalogue they compete in — not a watchlist — with offers and buy-box state, at a cost per million rows that left room for a business.
- SKU records since 2023
- 40B
- measured coverage
- 98.4%
Walmart
Every store, every day: 64M rows
In grocery, the chain price is a fiction. What matters is the price and the stock in the specific store a shopper walks into, which turns the unit of work from a catalogue into a matrix — thousands of stores multiplied by a tracked basket of thousands of items, refreshed before the client's morning report.
- SKU-store rows a year
- 23B
- measured coverage
- 99.0%
DoorDash
640k merchants found by a 46k-point grid
On a delivery platform nothing exists in the abstract. What you can see — which restaurants, which menu, which fees — depends entirely on the address you ask from.
- menu-item records since 2024
- 26B
- measured coverage
- 98.2%
StubHub
9.4M live listings, the whole book every six minutes
Resale prices only mean something next to the other resale prices for the same seats. The client needed the whole secondary book — every listing, its exact seats, its fees and its age — refreshed fast enough that a broker's repricing decision is made against the market as it is, not as it was this morning.
- listing records since 2020
- 230B
- measured coverage
- 98.8%
Eventim
Eleven European markets, 640k events, one schema
A European ticketing platform is not one site. It is eleven country sites with different layouts, languages, currencies, tax treatments and even different ideas of what a seat is — and a client trying to compare markets needs all of that arriving as one clean table.
- event records to date
- 15B
- measured coverage
- 98.6%
Rightmove
The whole UK market, under a search ceiling
The UK residential market is well served by one dominant portal, which is convenient until you try to collect all of it.
- property records to date
- 12B
- measured coverage
- 99.0%
Clients stay anonymous — every engagement is under NDA, and what is published here is what each of them agreed to publish. Under NDA we walk through the architecture, the failure modes and the cost model of any of these against the source you actually care about. Case files for the other three disciplines are in preparation.
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Have a source of your own? Two lines are enough.
Send the source, the fields you need and roughly how often. You get a straight answer within 24 hours: whether it can be done, what makes it hard, what coverage is achievable and roughly what it costs to build and to run. Whatever the size.
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NDA before technical detail, as always. If it isn't our kind of work, we say so in the first reply.