Schema-typed output
Pass a JSON Schema and the response conforms to it exactly, so your code gets predictable, typed fields every time.
POST /v1/extract
Structured data extraction powered by LLMs.
Point an LLM at any URL and get back the exact JSON shape you asked for.
Define a JSON schema or write a plain-English prompt, send a URL, and an LLM reads the page and returns typed, structured data ready to feed straight into your agent or pipeline. No selectors, no parsing code, no brittle scrapers to maintain.
What you get
Everything in one call.
Prompt mode
Skip the schema and describe what you want in plain English, and the LLM infers the structure from the page.
Clean input, fewer tokens
Pages are stripped to LLM-ready content before extraction, cutting roughly 90% of the tokens versus raw HTML.
Handles hard pages
JS rendering and bot protection are resolved automatically, so extraction works on the same sites a scrape would.
How it works
From URL to output in four steps.
01
Send a URL
POST the target URL with either a JSON schema or a natural language prompt describing what to pull.
02
Fetch and clean
The page is fetched in Rust and stripped of nav, ads, and boilerplate into compact content for the model.
03
LLM extracts
An LLM reads the cleaned content and maps it onto your schema, or builds a structure that fits your prompt.
04
JSON returned
You get back a data object with the typed fields you defined, ready to use directly in your application.
API
One request, structured back.
POST /v1/extract
Send a URL to POST /v1/extract along with a JSON schema describing the fields you want. The endpoint fetches and cleans the page, then an LLM maps the content onto your schema and returns a typed data object. No selectors or parsing code required.
Ship an agent that actually sees the web.
One credit pool, every endpoint. Cancel anytime, or self-host the open-source core for free.