Domain Authority was built for the Google era. PAS is built for the AI one. Score any publication across five pillars: AI citation weight, crawl access, schema, editorial signals, and entity surface. One number, out of 100.
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Publication · scored
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From the score to the byline
PAS tells you which outlets AI models cite. Fast Press gets your story onto outlets in that league: distributed across our 144-publication network, indexed inside 48 hours, and live in AI training data on the next crawl.
Run any outlet through PAS. The score tells you whether a placement there will move AI citations or just collect dust.
One-off announcement, product launch, funding news, founder profile. Fast Press handles placement on outlets in the same weight class as the ones you scored.
Every placement adds a sourced page on a publication AI models already trust. Re-run PAS on your own brand domain a month later and watch what moves.
If ChatGPT and Perplexity aren't naming your brand yet, the gap comes down to one thing: not enough publications with weight have written about you. Fast Press fixes that for less than a team lunch.
Get featured for $49 →Publication Authority Score (PAS) is a 100-point metric that measures how authoritative a publication looks to AI search engines like ChatGPT, Perplexity, Claude, and Gemini. It aggregates five pillars: AI citation weight, crawl access, schema and structured data, editorial signals, and entity surface.
Domain Authority was built around link graphs that powered Google PageRank. PAS is built around the signals that drive AI citation: whether the publication is in Wikidata, whether AI bots can crawl it, whether it has schema, whether it has a public masthead and corrections policy. The two scores correlate loosely but PAS predicts AI citation, not Google ranking.
Yes. The tool is free. No login, no credit card, no email gate. You paste a publication URL and get the score plus a breakdown of which pillars need work.
Any publicly accessible web publication. Major outlets like the Wall Street Journal, TechCrunch, and Forbes will score high. Independent blogs and newer outlets typically score lower because they lack entity surface and editorial signals, which the tool surfaces as specific fixes.
The score is deterministic from observable signals: HTTP responses, public APIs (Wikidata, schema.org), and content scraping. It does not estimate or model. Two runs on the same URL the same day will produce the same score.
Two main use cases. First, evaluate publications before pitching, paying, or accepting a placement. A high-PAS outlet is more likely to get cited by AI engines. Second, score your own publication and use the pillar breakdown as a roadmap for improving AI visibility.