Data Extraction

What is Data Extraction?

Data Extraction turns any webpage into structured, usable data — without writing code or configuring CSS selectors manually. Autonoly's AI examines the page, identifies repeating patterns like tables, product grids, job listings, or search results, and extracts them into clean rows and columns that you can export or feed into the next step of your workflow.

This is different from traditional web scraping tools that require you to inspect elements, write selectors, and handle edge cases yourself. With Autonoly, you describe what you want in plain English through the AI Agent Chat, and the extraction happens automatically. The AI understands the visual structure of pages — it sees headers, data rows, and detail links the same way you do.

When to Use Data Extraction

Data extraction is the right tool whenever you need to pull structured information from websites:

• Price lists, product catalogs, and inventory data from e-commerce sites

• Job listings from career pages and job boards

• Contact information and company directories

• Real estate listings, financial data, news articles

• Any tabular or list-based data displayed on the web

Types of Extraction

Autonoly supports several extraction modes, each designed for different scenarios:

Single Element Extraction

Grab a specific piece of information from a page: a product price, a headline, a stock ticker value, an address. You describe what you want, and the agent finds and extracts it. This is useful for monitoring dashboards, checking specific data points, or pulling individual values into a larger workflow.

Collection Extraction

This is the most common mode. The agent identifies repeating structures on a page — rows in a table, cards in a product grid, items in a search result list — and extracts every instance into a structured dataset. Each item becomes a row, and the agent detects columns automatically: name, price, URL, date, description, image, and more.

Collection extraction works well with:

• Product listings on e-commerce sites

• Search results on any platform

• Directory listings and contact pages

• Job boards and real estate sites

• Social media feeds and comment threads

Nested Collection Extraction

Sometimes you need more than what's on a single page. Nested extraction lets the agent click into each item on a list page, visit the detail page, extract additional fields, and merge everything back into a single dataset. For example:

1. Extract a list of 50 products from a category page
2. Click into each product page
3. Grab the full description, specifications, and reviews
4. Combine everything into one comprehensive dataset

This is where Autonoly's Browser Automation engine shines — the agent navigates between pages seamlessly.

Full HTML Capture

For advanced use cases, you can capture the raw HTML of any page or element. This is useful when you want to feed content into AI & Content tools for summarization, sentiment analysis, or custom processing.

AI-Powered Field Detection

Traditional scraping tools require you to specify exactly which CSS selectors to use for each field. Autonoly takes a different approach:

• Describe what you want — "extract company name, website, and funding amount" or "get all job titles and locations"

• The AI identifies field types automatically — it recognizes text, numbers, dates, URLs, email addresses, images, and more

• Preview before committing — see a sample of extracted data before running the full extraction. If a field is wrong, send a correction via the AI Agent Chat and the agent adjusts

• Learning over time — through Cross-Session Learning, the system remembers which selectors work on specific sites, making future extractions on the same domain faster and more reliable

Handling Pagination and Scale

Real-world data rarely fits on a single page. Autonoly handles pagination automatically:

• Traditional pagination — the agent clicks through page 1, 2, 3... and collects data from each

• Infinite scroll — continuous scrolling to trigger lazy-loaded content until all items are visible

• "Load more" buttons — clicking expansion triggers repeatedly until the dataset is complete

• URL-based pagination — modifying page parameters in the URL for efficient multi-page crawls

For very large extractions (thousands of pages), combine data extraction with Logic & Flow to build loops, handle errors gracefully, and manage rate limiting.

Output Formats

Extracted data can be delivered in multiple formats:

• Excel — with support for multiple sheets, formatting, and formulas. Great for reports shared with non-technical stakeholders.

• CSV — lightweight and universal. Works with every data tool, database import, and programming language.

• JSON — structured format ideal for developer workflows, API integrations, and custom processing.

• Direct integrations — push data straight to Google Sheets, Notion, Airtable, or any of 200+ connected tools without intermediate files.

You can also chain extraction output directly into Data Processing for cleaning, deduplication, and transformation before delivery.

Data Volume and Pricing

Extraction volume depends on your plan. The pricing page has full details on how many pages and records are included at each tier. For large-scale extraction projects, check the templates library for optimized pre-built workflows.