WebSkillet.ai - web automation that gets cheaper every run

Launch Video: https://youtu.be/mXxe3P7hMzg

What is Webskillet.ai?

Webskillet is a single API for web automation - extracting data, downloading files, crawling sites, filling forms, research tasks. You send a task in plain English (plus optional parameters, output schema, and start URL), and an agent executes it in a real browser using code.

That code is saved as a skillet, and since most web automation is repeat work (the same task on a schedule, or the same task with different parameters), the skillet gets reused on every later run. That's why run 2 can be 4x faster and cheaper than run 1. Here are 20 real tasks with run 1 vs. run 2 numbers.

Why this is different?

Pure AI browser agents treat every run like the first one. Nothing transfers: the agent re-explores, re-reasons, and you pay full price in time and tokens every time. Fine for one-offs, but web automation is mostly repeat work.

Webskillet captures what the agent learns as code in the skillet, so run 2 starts from a working solution instead of a blank browser. And it's code reuse, not caching: same skillet, new parameters, fresh data from the live site.

Our story

We've been building Intuned for the past 3 years: a browser automation platform that's been powerful for our customers, but it takes some setup to get up and running. Meanwhile, the world is moving to a place where agents just want everything as an API.

Webskillet is our new product: everything we learned, packaged differently. One endpoint, no setup, and our infra (stealth browser, proxies, captcha solving, AI agent) behind it.

Demo: https://youtu.be/U9WPX2bG_GI?si=0qoXtt7JKaTP-eXG

Who it's for

• AI agent products that need the web as a tool. An example: a sales agent calling Webskillet to scrape a big website and build target lists
• Product teams whose product needs data from sites that don't have an API in a repeat manner: government sites or legacy systems
• Growth/GTM engineers doing enrichment and competitor monitoring: pricing pages, job postings, hiring signals
• Ops teams doing repeated lookups: insurance verification, compliance checks, order status
• Data/analyst teams building on web data: price intel, listings, market data, 10-K filings

Here's a sheet of 20 real tasks we ran, with costs and timings for run 1 vs. run 2. Every row has a "try it" link so you can run yourself.

Asks

• Try it! Sign up at webskillet.ai
• Watch the demo and tell us what you think, especially on the skillet concept
• If you has a scraping/automation use case, lets talk!