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Introducing Extralt: AI-Generated Web Crawlers That Run at Machine Speed

Traditional scrapers break. AI scrapers are too slow. Extralt generates crawlers using AI, then compiles them as Rust binaries that extract thousands of pages per minute.

Jerome Blin_

We've been building Extralt for the past year. Today, we're showing you what we've made: AI-generated web crawlers that run at machine speed.

The Problem

Every data team we talked to had the same story. They needed web data. Product prices, inventory levels, competitor listings, market signals. The data was right there on public websites. Getting it reliably was the hard part.

Traditional scrapers broke constantly. Every time a website updated their layout, someone had to fix the selectors, and teams were spending more time maintaining scrapers than actually using the data. The new wave of AI-powered tools helped with adaptability, but introduced a different problem: running an LLM on every single page doesn't scale, and at high volumes, the inference costs eat into any ROI the data provides. We kept asking ourselves: what if there was an alternative?

An Alternative Approach to Extraction

That question became our name. Extralt comes from combining "extraction" and "alternative." We wanted to build something fundamentally different.

The insight was simple: AI should run once, not on every page. Most vibe scraping tools work by pointing an LLM at each page and asking it to extract data, which is powerful but expensive at scale. We realized that the AI doesn't need to see every page. It just needs to understand the site's structure once, then generate code that can extract data at machine speed. So that's what we built.

Meet Agent Smith

Every Extralt extraction starts with Agent Smith, the name we give to our AI agent.

When you give Smith a URL and describe the data you want, it doesn't just extract data directly. Instead, it autonomously navigates the website to understand its structure, discovers how pages link together and where the relevant content lives, then figures out the optimal way to extract it. Some sites need full Chrome rendering to execute JavaScript, others work fine with simple HTTP requests, and some expose APIs that can be called directly; Smith analyzes the site and determines the right approach for each, often combining multiple methods for maximum efficiency.

Once Smith understands the site, it builds a custom crawler (we call that a robot) designed specifically for that domain. The robot is a compiled Rust binary that runs at native speed, processing thousands of pages per minute with no per-page inference costs because the intelligence is baked into the code itself. Think of Smith as a blacksmith forging tools: you describe what you need, and Smith builds the right tool for the job.

How It Works

The flow is straightforward:

  1. Blueprint: You describe the data you want: product names, prices, availability, images, whatever fields matter to your use case.

  2. Agent Smith explores: Smith autonomously navigates the target website, mapping its structure, discovering how to find relevant pages, and determining the best extraction method for each (Chrome rendering, HTTP requests, or direct API calls).

  3. Robot generated: Smith builds a robot, a compiled Rust crawler optimized for that specific site, encoding everything it learned about navigation and extraction into native code.

  4. Data extracted: The robot runs at machine speed, extracting structured data that matches your blueprint without any further AI involvement.

When the website changes, Smith can rebuild the robot. You don't maintain selectors. You maintain intent.

Interested in seeing this in action? Join our waitlist for early access.

What You Can Build

Extralt is designed for teams that need web data at scale:

  • Price intelligence: Track competitor pricing across thousands of products
  • Market research: Monitor listings, inventory, availability across your industry
  • Lead generation: Extract contact information and company data from directories
  • Content aggregation: Pull structured data from news sites, job boards, real estate listings

If the data is on a public website and you need it structured and fresh, that's what we built Extralt for.

Web Scraping Across Industries

Anywhere there's a list of things on the web, there's data to extract. Extralt works across verticals:

  • E-commerce and retail: product catalogs, marketplace listings, price monitoring at scale
  • Real estate: property listings, rental platforms, MLS data aggregation
  • Automotive: dealership inventory, used car marketplaces, parts catalogs
  • Recruiting and HR: job board scraping, candidate databases, company directories
  • Travel and hospitality: hotel rates, flight prices, vacation rental availability
  • Financial services: alternative data, SEC filings, fund directories, fintech aggregators

The pattern is the same: structured listings on the web become structured data in your systems.

Get Early Access

We're currently in private beta, working with early users to refine the experience. If you're spending too much time maintaining scrapers, or if your AI extraction costs are eating into your margins, we built Extralt for you.

Join the waitlist and we'll reach out when we're ready.

For the data behind the shift to AI-powered extraction, read Web Scraping in 2026: Why AI-Generated Crawlers Are Winning.