COMPARE:
Browse AI or Apify for scraping on a schedule
Browse AI against Apify for pulling data off a website again and again, with the same seven questions asked of each and neither one flattered. Mamba Labs builds the Apify actors here, Page Finder Extractor included, and the page says where it is the wrong answer.
The verdict
Browse AI is point and click and needs nobody technical. Apify is a platform with proxies and a runtime, and it does not fall over when a site fights back.
Side by side
| Browse AI | Apify | 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. | Runs a program against the public web on a schedule or on demand, and hands back a dataset. | 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. | A few thousand published actors, plus anything you write yourself, which is the part that matters. | 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 event or per compute unit, depending on the actor, and it is usually cents per row. | 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. | An API, a scheduler, webhooks, and a dataset you pull or push onward. Clay calls it as an HTTP step. | 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 public web, read directly, which means you can see exactly where a field came from. | 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. | Running a published actor takes minutes. Writing your own takes a developer. | 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. | There is no table, no interface for a list, and no view of your accounts. | 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.
- Apify wins on what it costs, where the data comes from. A platform for running scrapers and data actors, yours or somebody else's.
- 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 coverage and hit rate, where it stops. Browse AI and Apify give the same answer on those, and we are not going to invent a difference.
Where to get them
What is best for you
Browse AI is the right first tool for a marketer who needs one site watched and has no engineer. Fifteen minutes and it is running. It stops being the right tool at a predictable point. The target puts real bot defences up, or a layout change breaks the robot and nobody notices for a fortnight. Apify costs more attention and survives both. Start on Browse AI if you have no engineer. Move the moment a process depends on the data, because a broken scraper that reports nothing is worse than no scraper at all.
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