An AI web agent is software that browses websites on your behalf. You give it a goal in plain English, and it opens a real browser, clicks, logs in, searches, paginates and reads pages until the goal is met. A scraper follows a fixed recipe of selectors. An agent decides its next move from what is actually on screen, which is why it keeps working after a site is redesigned.
Last updated July 2026
Robot console · WR-01
Standing by Running · s Complete · rows
1 · Pick a target
3 · Fields to extract
Agent log
Crawl graph
Extracted data · rows
Want this data fresh every morning, without lifting a finger?
STEP 1
The agent loads the URL in a real browser, waits for scripts to settle, and builds a picture of what is on screen: headings, buttons, list items, form inputs, the price sitting next to each product title. Not a raw HTML dump, a map of meaningful elements.
STEP 2
Your instruction is the goal state: "every listing in Austin under $600k with beds, baths, square footage and the agent's phone number". The robot asks whether the current page contains that, contains part of it, or is a step on the way to it.
STEP 3
Dismiss the cookie wall. Type into the search box. Apply the price filter. Click "load more". Sign in with the stored credentials. One action, executed in the browser, then back to step one. Sites that need ten steps get ten passes through the loop.
STEP 4
When the target data is on screen, the agent pulls the fields you named and checks each one against its description. A price should look like a price. A date should parse as a date. Rows that fail the check are flagged rather than quietly written as empty cells.
STEP 5
Because the robot stores intent ("product title, price, stock") and not a CSS path, a redesign is not a fatal error. The agent re-locates the fields from their meaning, resumes the run, and records what changed so you can see it in the run log.
STEP 6
The loop ends in a destination, not a download folder: CSV, Excel, Google Sheets, Slack, Zapier, a webhook, or the REST API. Runs can be scheduled daily, hourly, or set up as real-time monitors.
| Dimension | Classic scraper | Browser script (Selenium, Playwright) | AI web agent |
|---|---|---|---|
| What it stores | CSS or XPath selectors | An ordered list of coded commands | Your intent, in plain English |
| Reaction to a redesign | Returns empty cells, often silently | Throws element not found, run dies | Re-locates the fields and continues |
| Handles login and search forms | Usually not | Yes, if you code the flow | Yes, described in a sentence |
| Unknown page it has never seen | Needs a new selector set | Needs new code | Works from the goal, no setup per site |
| Who can build one | Anyone patient with a point-and-click UI | An engineer | Anyone who can describe the data |
| Ongoing cost | Repair tickets after every site change | Engineering time forever | Flat plan, self-healing runs |
| Best at | One static page shape, high volume | Deterministic app testing in CI | Messy, interactive, changing sites |
None of these is universally better. If a site publishes a clean, stable API, use the API. That trade is worked through in web scraping vs API. If you want the fastest path from "I need this data" to a spreadsheet, start with the web scraping tool overview.
BARRIER 01
Supplier portals, ad platforms, marketplace seller dashboards. The agent signs in with stored credentials, waits for the dashboard to render, and reads the numbers you named. Agent actions including logins are on the Scale plan and above.
BARRIER 02
The results you want may only exist after a query is typed and three filters are ticked. An agent performs the search, applies the filters, and then reads the result set. A selector tool can only read the page it was pointed at.
BARRIER 03
"Load more" buttons and lazy lists hide the majority of records. The agent keeps clicking and scrolling until the list stops growing, which is the only reliable definition of "the end".
BARRIER 04
Listing pages rarely carry every field. The agent opens each result, collects the fields that only live on the detail page (specs, contact, full description), and folds them back into one flat row per record.
BARRIER 05
Quote tools, availability checkers and shipping calculators need input before they produce output. Describe the inputs once and the agent runs the form for every row you feed it.
BARRIER 06
Public records, small vendor catalogs, regional job boards. If a person can open it in a browser, an AI agent for data extraction can turn it into rows.
| Team | Instruction given to the agent | Agent actions required | Delivery |
|---|---|---|---|
| Pricing | "Every SKU on these six competitor sites with price, promo flag and stock status." | Pagination, variant selection | Hourly to Google Sheets |
| RevOps | "Every company on this directory with name, headcount band, HQ city and website." | Search, filters, detail pages | CSV plus webhook to CRM |
| Recruiting | "New postings on these job boards for senior data roles, with title, company and date." | Filter state, load more | Slack alert on new rows |
| Supply chain | "Log in to the supplier portal and pull lead times for every part number in this list." | Login, form input per row | Daily Excel export |
| Product | "Reviews for these ten products with rating, date, verified flag and body text." | Load more, sort by newest | REST API into the warehouse |
More patterns are collected on the use cases page, and if the job is specifically tracking competitor prices, the price monitoring tool is the shorter route.
If the source publishes a stable, well documented API and your access is permitted, use it. It will be faster, cheaper and contractually cleaner than any browsing agent. An agent earns its keep where no API exists.
Regression testing your own app in a pipeline wants deterministic, assertion-driven code. Playwright and Selenium exist for that and are the right answer. WebRobot is built for data workflows, not QA suites.
The robot honors robots.txt and rate limits, and it will not defeat CAPTCHAs or paywalls put up to keep automation out. The legal picture is worth reading first: is web scraping legal.
Where an agent does fit, pricing is flat rather than metered by credit: Launch at $79 per month (5 robots, 10,000 records, daily schedules), Scale at $249 (25 robots, 100,000 records, hourly schedules, change alerts and agent actions such as logins and multi-step forms), Autopilot at $699 (100 robots, 1 million records, real-time monitors and autonomous multi-step agent flows). Yearly billing brings those to $63, $199 and $559. Full detail on the pricing page, and the mechanics of a run are broken down in how it works.
FINAL ASSEMBLY
Describe the goal in one sentence. The robot browses, clicks, logs in and hands back clean rows, today and after the next redesign.