Classify website changes
When Wachete detects a change on a monitored page, have Claude judge whether the change is significant before anyone is alerted.
Google for Startups AcceleratorHow Knit builds this workflow
The Agent researches both APIs and wires the trigger on one side to the action on the other — no pre-built connector required. Here is the vocabulary it has to work with.
Wachete Explore Wachete →
TriggersFires when a scrape, crawl or robot run finishes in Wachete.
Fires when Wachete returns a new batch of extracted data.
Fires when Wachete detects a change on a monitored page.
Extracts the content of a web page with Wachete.
Starts a crawl of a whole site in Wachete.
Runs a saved scraper, task or robot in Wachete.
Claude Explore Claude →
TriggersFires when Claude returns a completion, prediction or other result.
Fires when a request to Claude errors or times out.
Fires when a fine-tuning job in Claude finishes.
Sends a prompt to Claude and returns the model's response.
Sends text, an image or other data to Claude and returns the model's output.
Uses Claude to classify or extract structured data from text or images.
More Wachete + Claude workflows
See all Wachete + Claude integrations → · Browse the full workflow library →
Enterprise-grade security
Common questions
Can Knit build “Classify website changes” between Wachete and Claude?
Yes — describe it in the box above and Knit's Integrations Agent researches Wachete and Claude's public API docs (or your own uploaded docs) and builds a working workflow, whether or not either app already has a pre-built connector.
How long does it take to build?
Minutes to a first working version, not weeks — you test it against real data before it goes anywhere near production.
Why send scraped pages to an AI model?
Scraped HTML and text are noisy. Passing each Wachete result to Claude lets you pull out prices, names or key points in a consistent shape instead of cleaning the data by hand.
Can the model decide which pages to scrape next?
Yes. You can have Claude produce a list of URLs or search terms, then run a scrape in Wachete for each one.