AI TRAINING DATA
Collect structured, schema-consistent JSON across 50+ dedicated APIs with this web scraping API, built for training pipelines, not just one-off scrapes.
Consistent schemas that don't break on page redesigns, critical for reliable pipelines.
Social, e-commerce, real estate, travel, search, app stores, no HTML parsing required.
Structured JSON with consistent field names across requests, so pipelines don't silently break.
SDK pagination and CLI batch commands built for pulling large datasets, not single lookups.
Connect directly from an AI agent's workflow via MCP, no separate ETL step needed.
Structured JSON from dedicated endpoints, or HTML, Markdown, and plain text from the general web scraping endpoint.
Failed requests during a large bulk pull don't cost credits: only successful data counts.
async for product in client.amazon.products.search_all( "wireless headphones", max_items=1000 ): dataset.append(product)
No, those are a different, separate use case: querying the real chatgpt.com, perplexity.ai, or gemini.google.com and tracking how a brand appears in AI answers (Brand Visibility/AEO). This page covers bulk structured-data collection across the 50+ dedicated APIs for building datasets, not AI-answer monitoring.
Yes, the same API key and SDK work across every vertical, so a single pipeline can pull Amazon listings, Reddit posts, and real estate data in parallel without separate integrations.
Every endpoint returns a stable, structured schema, page redesigns on the source site don't break your pipeline the way HTML-scraping-and-parsing would.
Use the Python or Node.js SDK's automatic pagination (search_all() in Python) to iterate through large result sets without manually managing cursors, or the CLI's batch commands for scripted bulk pulls.
1,000 free credits, no credit card required.