Notte's scraping capabilities combine AI-powered extraction with typed output. Instead of writing CSS selectors that break when pages change, you describe what data you want and Notte returns it as structured Pydantic models.
How it works:
- Define your output schema as a Pydantic model (or let Notte infer it)
- Point Notte at a URL or describe a multi-step navigation
- Notte's AI extracts the data and validates it against your schema
- You get typed, validated JSON back
Why this matters:
- No selector maintenance: Pages change layouts constantly. AI extraction adapts automatically.
- Structured output: No post-processing regex. Data comes back typed and validated.
- Multi-step flows: Handle login, navigation, pagination, and extraction in one workflow.
- Scale: Run many extractions in parallel with cloud browser sessions.
Example use cases:
- Price monitoring across competitor sites
- Lead enrichment from LinkedIn, Crunchbase, etc.
- Compliance data collection from regulatory sites
- Product catalog extraction from e-commerce sites
Works with the Python SDK, REST API, or the Anything API (natural language). Docs at docs.notte.cc/quickstart.