Paste a list of candidate sites and get each one back scored against the criteria your team actually uses: is the topic close enough, does the traffic look real, how many outbound links per post, is there a paid-post footprint, does the content read like it was written for readers. Accept, borderline and reject, with the evidence attached — so a junior can run the first pass and a senior only reviews the borderline pile.
Thirty to forty sites a day is what careful review gets you. Everything above that either waits or gets waved through on a metric that was never enough on its own.
Two specialists accept different sites, and neither can fully explain the rule. Six months later nobody knows why half the placements were bought.
A link on a spam farm costs the fee and then costs the cleanup. The signals were visible before the money moved; nobody had ten minutes to look.
We take the criteria your senior actually applies — topical distance, traffic shape, outbound-link density, footprint of paid posts, thin content, the niches you avoid — and make them explicit. Half the value of the project shows up in this conversation.
Third-party metrics where you have subscriptions, plus a crawl of the site itself: recent posts, publishing cadence, author pages, ad density, and a sample of the actual writing.
A model reads the sampled content and rates how close the site sits to your topic and audience — the judgement a keyword overlap score keeps getting wrong.
Accept, borderline, reject, each with the rules that fired and the evidence behind them. Borderline is a real bucket on purpose: it is where a human should spend their attention.
Verdicts land in your sheet, Airtable or CRM with contact details where they are public. Placement outcomes come back in, so the rules tighten on your own results rather than on a vendor’s benchmark.
We build in your stack rather than moving you onto ours. The list below is what this solution most often connects to — other systems are a scoping question, not a blocker.
It works better with them and still works without. Without third-party metrics we lean harder on the crawl and content analysis, and we will be explicit about what that costs in accuracy.
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