Define a schema, pass a URL, get back JSON that matches. Tabstack's extract endpoint turns any web page into structured output, no parsing code and no LLM call to maintain. generate endpoint adds AI instructions for reasoned answers, not raw fields. Both enforce your schema on every call, even when the page changes. Tune speed with effort levels, target any country with geo_target. Mozilla-backed: your data is never sold or used to train models. 10,000 free credits to start.
Tabstack is a web data and automation API that delivers reliable structured output. Pass a URL and a schema, get back JSON that matches every time. Run research in one call and get cited answers back. Automate browsers without running infrastructure. The intelligence is built into every API call. No scraper to build, maintain, or watch break when a site changes. Built at Mozilla.
/research gives your app or agent cited answers from the live web in one API call. Not a pre-indexed corpus: the actual live web. Every request comes back with source URL's users can verify. Source selection, synthesis, and citation formatting are all inside the call. You write or maintain none of that code. Built for legal, financial, and competitive intel, where a wrong answer is a liability. Free to try.
I joined Tabstack four weeks ago. The fastest way I know to understand a product is to build something real with it not tutorials, not toy examples, but an actual app that uses the API under real conditions and breaks in interesting ways.
So I built Rival. Open-source competitive intelligence dashboard that tracks competitor pricing, changelogs, careers, docs, and GitHub signals, diffs what changes, and generates intelligence briefs automatically.
