The biggest risk in GEO isn't that it fails to work. It's feeding AI the wrong specifications: once a model has learned a wrong number, correcting it costs far more than getting it right the first time.
This page publishes our entire quality-control process, so you can use it as your acceptance criteria.
Each one is easy to slip into and expensive to undo. The four checkpoints below exist to block them.
To make content "look professional," a writer fills in values the client never provided. Once AI learns them, buyers come to you asking for a quote against that number, and the client bears the commercial consequences.
Blocked by checkpoint 1
"Close specifications" becomes "fully equivalent to a major brand's grade." That is misleading advertising, and it may also infringe the other company's trademark rights.
Blocked by checkpoint 2
One template, a few keywords swapped, dozens of articles generated in bulk. Search engines classify it as low-quality content and AI won't cite it either. You pay for it, and it damages your site's authority.
Blocked by checkpoint 3
Content goes live only when it clears all four checkpoints. If it fails any one of them, it goes back for a rewrite and doesn't count toward your deliverables.
Fail any checkpoint: back to rewrite, not counted as delivered.
Every value, standard number and certification name in the content must trace back to a TDS, test report or written confirmation provided by the client. Anything that can't be traced is deleted or rewritten as a qualitative statement. We never "fill in a reasonable number."
What you receiveEach delivery includes a source map: every data point is listed with its source file and page number.
Any mapping against a major brand's grade must be based on publicly available specification sheets, and the wording is limited to "specification comparison" or "can be evaluated as an alternative." We never use absolute claims such as "equivalent," "identical" or "official replacement." Other companies' trademarks are used descriptively only.
Sign-offMapping tables go live only after the client confirms them in writing.
Every piece is checked individually. Does the title or body duplicate content already on the site? Does its paragraph structure mirror other pieces? Does it contain standalone conclusion sentences AI can quote directly? Anything over the duplication threshold goes back for a rewrite. We would rather publish 2 pieces this week than 10 that all read the same.
RuleWithin one batch, no title structure may be used more than twice.
Before anything goes live, we confirm item by item: a single canonical URL, structured data that passes the Rich Results Test, internal links pointing to the right pages, specifications presented as HTML tables rather than images, and the page not blocked in robots.txt.
ChecklistThe technical checklist is in our content playbook. It is the same one we use internally.
Any technical specification the client hasn't provided in writing never appears in what we deliver. If we breach this, the entire batch is redone at no charge.
AI recommendations are decided by the model, and no one can guarantee a specific position. What we commit to is the quality of citable assets and a verifiable change in mention rate, not "guaranteed first place."
No hidden text, no cloaking, no bulk link buying. These tactics may work for a while, but once they are detected, your site's trust drops to zero.
Every test record comes with screenshots and timestamps, and every published piece keeps a version history. When the engagement ends, everything is handed over to you in full. No technical lock-in.
Including us.
Either one, and you already have your answer.
