COMPARE:
Browse AI or Octoparse for scraping without code
Browse AI and Octoparse both do scraping a website without writing code, and this page puts them on the same seven questions. Mamba Labs builds Apify actors. Page Finder Extractor is ours, it is the third column, and it does not win most of these rows.
Last updated September 21, 2026
The short answer
Browse AI when a marketer needs one site watched and nobody technical is around. Octoparse when the job is a big pull from a marketplace or a directory and a template already exists for it. Both break when the page changes, and only Browse AI tells you.
The same questions, both tools
| Browse AI | Octoparse | Page Finder Extractor | |
|---|---|---|---|
| What it actually does | Trains a robot by recording a browsing session, then reruns it on a schedule and reports what changed. | Builds an extraction by clicking through the page in a desktop app, then runs it locally or in the cloud. | Takes a list of domains and a page to look for, then returns the URL and the extracted content. |
| Coverage and hit rate | One site per robot, and it handles login and pagination as long as the page does not fight back. | Any public site, with ready made templates for the marketplaces, social networks and directories people scrape most. | Any page type a site actually publishes: pricing, careers, security, leadership, integrations. |
| What it costs | Credits per row extracted on a monthly plan, with the schedule frequency gated to the higher tiers. | Per plan per month, set by cloud task slots and speed, with a free tier that runs on your own machine. | Cents per domain, charged on a returned page rather than on a search. |
| How it fits a workflow | No code at all. The output goes to a sheet, a webhook or an integration. | Build the task in the app, run it locally or in the cloud, and export to a file, a database or the API. | One call for the whole list, from Clay or from a script, and finished rows come back. |
| Where the data comes from | The pages you record, read live at the schedule you set. | The pages you point it at, read live when the task runs. | The sites themselves, fetched directly, so the source URL is on every row. |
| What it takes to set up | Fifteen minutes for a first robot, and no engineer involved at any point. | An hour to a first task, longer for a site with pagination and detail pages. | Give it the domains and say which page you want. |
| Where it stops | A layout change breaks the robot. Sites with real anti bot defences are outside what it can do. | The desktop app is Windows first, and the visual builder gets fiddly on a page that changes shape. | It reads pages. Anything behind a login is not something it can reach. |
The same seven questions are asked on every compare page here, in this order, so two of these pages can be read against each other.
Where each one genuinely wins
- Browse AI wins on how it fits a workflow, what it takes to set up. Point and click scraping. You record what to grab and it repeats it on a schedule.
- Octoparse wins on coverage and hit rate, what it costs. A visual scraper with a desktop app, a cloud runner and templates for the sites people scrape most.
- Page Finder Extractor wins on what it actually does. Finds one named page across hundreds of websites and extracts what is on it.
- Nobody wins on where the data comes from, where it stops. Browse AI and Octoparse give the same answer on those, and we are not going to invent a difference.
Where to get them
What we would actually do
Browse AI is the one to hand to somebody who has never scraped anything. Fifteen minutes, a webhook, done. Octoparse is the one for a bigger pull. The templates for the large sites save the build, and the free tier runs on your own machine for as long as you like. Both stop at a site with real bot defences, and both go quiet when a layout changes. If the data feeds a process, put a check on the row count so an empty run does not pass as a clean one.
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