Most web scrapers hand you data and hope it's correct.

I think that's the wrong default—especially when the output is feeding an AI pipeline, where a silently incorrect field is often worse than a missing one.

That's why the Actors I build on Apify are designed around verification, not just extraction:

✅ Extract against your JSON Schema ✅ Validate and automatically repair structured output ✅ Ground extracted values back to the source page ✅ Score confidence for each field so you know what to trust

The goal is simple: deliver structured data that's reliable enough for production AI systems—not just demos.

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Most scraping problems aren't about getting data once—they're about getting it correctly every day.

I focus on building Actors that remain stable, predictable, and maintainable over time.

No marketing fluff.

Clear documentation about:

• What a tool does
• What it doesn't do
• Known limitations
• Expected output formats

Clean, typed JSON designed for:

• Retrieval-Augmented Generation (RAG)
• AI agents
• Knowledge bases
• ETL pipelines
• Workflow automation

Less cleanup. More building.

Simple pricing that reflects value delivered.

No surprises. No hidden complexity.

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A missing field can be handled.

A confidently wrong field can quietly break an entire AI workflow.

That's why verification, validation, and confidence scoring are first-class features—not afterthoughts.

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Whether you're building:

• 🧠 AI agents
• 📚 RAG systems
• 📊 Data pipelines
• 🔄 Business automations
• 🕸️ Custom web scrapers

Feel free to open an issue on one of my Actors.

I read every issue and actively use feedback to improve the tools.