BROWSE AI TRAINING: EXTRACT DATA WITHOUT CODING

We start with the basics: understanding how Browse AI works and creating your first extraction robot.

You discover the interface, the different types of robots (extraction vs monitoring), and the logic behind no-code web scraping. No coding required, but you'll understand what the tool does under the hood.

You create your first simple robot: extracting data from a single page. You learn to select elements to capture, name your fields, and run a test extraction.

You also configure your account properly: credit management, robot organization, best practices from the start.

By the end of this module, you have a functional robot and understand Browse AI's logic.

Now that we know how to extract a page, let's move to lists. This is where Browse AI becomes really powerful.

You learn to create robots that extract entire lists: search results, product catalogs, directories, job offers. Browse AI automatically detects repetitive patterns.

You master bulk extraction: providing a list of URLs and launching extraction on all of them at once. Ideal for scraping hundreds of product pages or profiles.

You handle pagination: configuring your robot to automatically go through all result pages, not just the first one.

By the end of this module, you know how to extract data at scale from any list or catalog.

Extraction is good, but monitoring changes continuously is even better. Let's move to monitoring robots.

You create robots that regularly check a page and detect changes: new price, available stock, new listing, updated content.

You configure scheduled runs: defining the check frequency (every hour, every day, every week) according to your needs and credits.

You set up alerts: receiving a notification (email, webhook) only when something changes. No noise, just signal.

You discover concrete use cases: competitive intelligence (prices, stocks), listing monitoring (real estate, jobs), availability tracking.

By the end of this module, you have an automated monitoring system working for you 24/7.

Not all sites are easy to scrape. Let's see how to handle difficult situations.

You learn to extract from dynamic sites: pages that load content with JavaScript, infinite scroll, "See more" buttons. Browse AI handles this, but you need to know how to configure it.

You handle authentication: extracting data from logged-in spaces (after login). You configure cookies and sessions so your robot accesses protected pages.

You work around common obstacles: CAPTCHAs, rate limiting, IP blocking. We see best practices for scraping responsibly without getting blocked.

You optimize your robots: reduce execution times, save credits, improve extraction reliability.

By the end of this module, you can handle 90% of the situations you'll encounter in production.

Extracted data is useless if it stays in Browse AI. Let's connect it to your stack.

You master native integrations: automatically sending data to Google Sheets, Airtable, or Notion. Configuration in just a few clicks.

You configure webhooks: receiving data in real-time in Make, n8n, or your custom application. Each extraction triggers an automatic send.

You use the Browse AI API: launching extractions programmatically, retrieving results, managing your robots from other tools. Ideal for advanced automations.

You build complete workflows: extraction → enrichment → storage → action. For example: scrape leads → enrich with Clearbit → add to your CRM.

By the end of this module, Browse AI is integrated into your ecosystem and data flows automatically.

Let's put everything into practice with concrete projects you can reuse directly.

Case 1: Competitive intelligence. You create a system that monitors your competitors' prices, detects changes, and alerts you when someone lowers their rates.

Case 2: Lead generation. You extract contacts from professional directories, LinkedIn Sales Navigator, or specialized sites. You enrich and export to your CRM.

Case 3: Listing monitoring. You monitor platforms (real estate, jobs, marketplaces) and get alerted in real-time when a new listing matches your criteria.

Case 4: Market data collection. You extract data at scale for analysis: average prices, trends, availability. You structure and export to analysis tools.

By the end of this module, you have operational robots and reusable templates for your own projects.