Request type
Research and obscure data
Scattered public data from PDFs and registries, in one table.
Planned
Planned. Sources checked one by one before you pay.
Who asks for this
Statisticians, academics, journalists, analysts.
Say it like this
“Collect the annual rainfall tables published by these 14 regional water authorities into one table, with the source and year for every row.”
What you supply
- The sources, or a description
- Fields per record
- Years or date range
What you get back
Your table · 4 rows shownIllustrative
| regiontext · collected | yearnumber · collected | rainfall_mmnumber · collected | source_formattext · derived | source_urlurl · collected |
|---|---|---|---|---|
| North Basin | 2,024 | 1,120 | northbasin.example/annual-2024.pdf | |
| Coastal | 2,024 | 1,580 | html | coastalwater.example/stats |
| Highlands | 2,024 | — | highlands.example/report24.pdf | |
| Valley | 2,024 | 640 | html | valleywater.example/data |
collected from the page · derived at no cost · extra work raises the estimate
Workflow
How the agent handles it.
- 1
You list the sources.
- 2
We check each one and report the fields.
- 3
You approve the estimate.
- 4
We extract, normalize units, add a source URL per row.
- 5
Export, ready to cite.
Cost and limits
What moves the price, and where the answer can be no.
Cost drivers
- Number of sources
- PDFs cost more than web pages
- Reconciling formats
Where we say no first
- Not every source publishes every field every year.
- Scanned PDFs can be misread. We flag low confidence.
Early access
Want research and obscure data?
Describe the sources, the columns, and roughly how many rows.