Data platforms & pipelines
Getting data in, checking it, and keeping it correct — from a handful of spreadsheets to millions of rows a day.
Data processing · Data standards & validation · Transactional databases · Web data acquisition
Data & storage
Data standards & validation
Schemas that travel with the data, and one validation contract from database to browser.
- Fairspec
- Data Package
- JSON Schema
- Zod
- Pydantic
- DataCite
What it is
Machine-readable descriptions of what a dataset or a payload contains, and the runtime checks that hold it to that description at every boundary it crosses.
Why we chose it
Most integration failures are schema failures discovered late. We use Zod as the single runtime contract inside TypeScript, Pydantic on the Python side, and JSON Schema wherever the contract has to outlive a language choice. Fairspec, the specification we author, extends that to whole datasets: a data exchange format compatible with DataCite and JSON Schema that makes data findable and reusable rather than merely downloadable. Schemas are generated from the database rather than hand-copied, so there is one definition and no second copy to forget.
What we build with it
Where we use it
In every API boundary and file import we build, and as the subject of the standards work we publish openly.
captureapplication.fairspec.org
Fairspec — data framework in TypeScript and Python
A specification for describing tabular datasets, with reference implementations in TypeScript and Python.
we author
Get in touch
Tell us what you need built.
We are a small team in Portugal, working London hours. A site, an app, an internal tool, or the platform behind them — start with a sentence about the problem and we will take it from there.