BROWSE AI AGENCY: EXTRACT WEB DATA WITHOUT WRITING A LINE OF CODE

STEP 1: AUDIT YOUR DATA NEEDS

We start by understanding exactly what data you need and from which sources.

We map out the websites you want to scrape, identify the specific data points to extract (prices, names, descriptions, contact info, whatever matters), and analyze the site structures to anticipate challenges.

We check for anti-scraping measures, pagination complexity, dynamic content loading, and rate limiting issues.

We also look at how this data will be used—do you need real-time monitoring, daily bulk extraction, or triggered collection? This shapes the entire architecture.

At the end of this step, you have a clear extraction plan with identified data sources, fields to capture, and potential technical challenges mapped out.

STEP 2: ROBOT CONFIGURATION

We build your Browse AI robots with proper selectors and extraction logic.

We configure each robot with precise CSS selectors or XPath expressions to capture exactly the data you need. We handle pagination to scrape multi-page results, set up wait conditions for dynamic content, and configure proper scheduling intervals.

We use prebuilt robot templates when they fit your use case, and create custom robots when you need specific extraction patterns.

We test thoroughly across different scenarios—different data volumes, edge cases, and site variations.

At the end of this step, you have functional robots ready to extract data reliably from your target sources.

STEP 3: MONITORING AND ALERTS SETUP

We configure change detection and notification systems.

If you need to track changes (price drops, new listings, stock updates), we set up monitor robots with custom triggers. We define what constitutes a meaningful change versus noise.

We configure alert workflows—email notifications, Slack messages, webhook calls—so you know immediately when something important happens.

We set appropriate check frequencies based on how fast your data sources change and your Browse AI plan limits.

At the end of this step, you have a monitoring system that catches important changes and alerts you in real-time.

STEP 4: INTEGRATIONS AND DATA FLOW

We connect Browse AI to your existing tools.

We set up native integrations with Google Sheets, Airtable, or other supported destinations. For more complex workflows, we configure webhook triggers and API connections via Make or n8n.

We build data transformation logic to clean and format extracted data before it lands in your systems. We handle deduplication, data validation, and field mapping.

We create automated workflows that process new data—adding leads to your CRM, updating inventory systems, or triggering follow-up actions.

At the end of this step, extracted data flows automatically into your stack without manual intervention.

STEP 5: TESTING AND DEPLOYMENT

We test everything in real conditions before going live.

We run full extraction cycles to verify data quality and completeness. We stress-test with larger volumes to ensure robots handle scale without errors or blocks.

We check integration pipelines end-to-end—from extraction to final destination—to catch any data loss or formatting issues.

We document robot configurations, scheduling patterns, and troubleshooting steps.

At the end of this step, you have a production-ready extraction system with clear documentation.

STEP 6: TRAINING AND ONGOING SUPPORT

We train you to manage and maintain your robots.

We walk you through the Browse AI dashboard—how to monitor robot runs, check extraction results, handle errors, and adjust configurations when sites change.

We provide documentation specific to your setup with troubleshooting guides for common issues (selector changes, rate limiting, blocked requests).

We stay available for questions and offer maintenance if you want us to handle robot updates when target sites change structure.

At the end, you have a working extraction system and the knowledge to keep it running—or the option to let us handle maintenance for you.