First, unless your initial dataset includes every company out there, you're already losing opportunities. Most GTM teams start with limited lists from keyword or industry searches, often based on Google Maps scrapes or incomplete LinkedIn-based sources like Apollo or Clay.

Right there, valuable targets get missed, while obsolete or fake accounts get mixed in.

Then comes website scraping, and that’s far from a straightforward API call. Many top-tier sites are armored with bot protections, resulting in a flood of errors, captchas, or garbled texts.

Even if the scrape works, the content is frequently muddied with cookie notices and irrelevant disclaimers, causing your GenAI prompts to mistakenly disqualify genuinely great targets.

So what’s the solution? Start with us. Give us your full-page ideal company description, and we match it directly to the full website text across all 60M businesses, already translated into English.

There’s no subset, so no initial loss. There's no messy website text, we use a robust, 20-plus-step waterfall system, retrying for days or weeks, solving captchas, rendering through browsers, and meticulously removing cookie banners and legal clutter that would send your prompt spinning.

The result: just a clean, complete, actionable TAM of every secure business website matching your ICP.

Now you're ready to fire up Clay or n8n automation powers: layer on intent signals, technographics, and other data to build that ultra-targeted final list, with the fit that actually makes customers take action. You will save substantially on the processing fees as well.

Post below if you disagree, will set you up with the complementary access so you can compare.