Competitive intelligence team using an AI agent to track pricing
The AI employee scrapes competitor pages on a schedule and reports changes. No manual checking.
Scrape Any Website
Extract structured data from any website or crawl entire sites automatically for research and competitive analysis.
When you need more than search results, the web scraper goes deeper. It visits specific pages, extracts structured data, and delivers clean content: product listings, pricing tables, contact directories, job postings, article archives. Ask your employee to "pull all pricing from competitor X's website" and it returns a structured table, not raw HTML.
The crawler goes further. Point it at a domain and it follows links across the site, respects rate limits, and builds a complete map of the content. Perfect for competitive audits where you need to understand an entire website. Your employee crawls, extracts, and summarizes hundreds of pages into an actionable brief.
Scraping and crawling work together with other skills. Your employee can scrape competitor pricing, compare it against your own catalog in Google Sheets, draft a pricing strategy memo, and post the summary to your Slack channel. The data flows from extraction to action without manual steps.
Extract Structured Data From Any Website
Sistava gives your AI employee the ability to scrape and parse web pages, pulling out the specific data you need in a structured format. Whether it is product prices, contact information, job listings, or research data, the agent extracts and organizes it without manual copying.
Web scraping as an agent tool means you can combine it with other capabilities in a single task. Scrape a list of companies, look up each one, pull contact details, and push them into a CRM, all delegated to your AI employee as one instruction.
Crawl Entire Domains, Not Just Single Pages
The web crawler capability lets your AI employee traverse multi-page sites, following links to collect data across an entire domain. Instead of scraping one URL at a time, the agent can map and extract content from a full website structure.
This is useful for comprehensive research tasks: auditing a competitor's full product catalog, collecting all press mentions from a publications archive, or indexing a documentation site for later reference. The agent handles pagination and link-following automatically.
Clean Output Ready for Downstream Use
Scraped data is parsed and cleaned before the agent uses it. The agent strips navigation menus, ads, and irrelevant page furniture, delivering only the content you actually need. Output can be passed to other tools, written to a document, or pushed to an external system.
Combining the web scraper with API endpoints or OAuth app integrations gives you a full pipeline: scrape the source, transform the data, write it to your destination system. Your AI employee handles the entire chain.
Use Cases
Research team extracting structured data from public sources
The agent visits target pages, pulls the data, and formats it for analysis. Hours of manual work handled automatically.
Sales team equipping an AI employee with company data before outreach
The agent scrapes a prospect's website before the meeting and prepares a briefing with current context.
Operations team automating data collection from supplier portals
The AI employee visits portals, extracts the relevant information, and logs it, without any manual steps.
Comparison
| Before | After |
|---|---|
| Collecting data from websites is manual, slow, and inconsistent. | The AI agent scrapes and structures web data automatically. |
| Web data is only as fresh as the last time someone checked manually. | The agent scrapes on demand and always returns current information. |
| Extracting structured data from pages requires developer support. | The AI employee handles scraping as a standard part of its workflow. |
| Monitoring multiple sites for changes is a full-time task. | The AI agent tracks and reports changes automatically. |
FAQ
What is the difference between web search and web scraping?
Web search finds relevant pages across the internet based on a query. Web scraping extracts specific content from one or more pages the agent visits directly. They work well together: search to find the right pages, then scrape to extract structured data from them.
Can the AI agent scrape pages that require JavaScript to render?
Yes. The scraper supports JavaScript-rendered pages, which covers most modern web applications and single-page apps. Static HTML pages are also supported and processed faster.
Are there limitations on which sites can be scraped?
The agent respects standard scraping boundaries. Sites that block automated access or require authentication beyond what the agent has may not be scrapable. You are responsible for ensuring your scraping use cases comply with the target site's terms of service.
How does the crawler know when to stop?
You can configure crawl depth and scope, such as limiting the crawler to a specific subdomain or a maximum number of pages. Without limits, the agent applies reasonable defaults to avoid unbounded crawls.
Can my AI employee extract data from websites automatically?
Yes. The web scraper lets your AI agent visit any URL and pull structured data from the page as part of a workflow. It works without you needing to build or maintain a separate scraping pipeline.
We scrape 200 job postings a week to track hiring trends. The agent structures everything into a spreadsheet and files it automatically. Used to take a junior analyst two hours.