How the engines decide, how the rulebooks bite, and what we have measured across hundreds of audits. Written by the team building the platform — no filler, no listicles, no SEO theatre.
Cognoverge runs competing-firm engagements behind ethical walls. A model adapted from outside counsel conflict-management practice, suitable for any AI-search agency.
Not every citation is created equal. The publications LLMs actually quote when answering legal queries, ranked by aggregate citation weight, with submission paths for each.
Engine answers drift continuously, often before any visible ranking change. The detection math that turns continuous answer streams into actionable alerts.
Perplexity prioritizes recency and link recency; ChatGPT weights pre-training corpora and embedded relationships. A firm-visibility checklist tuned for each.
What actually happens inside a 24-hour Cognoverge audit, end-to-end: how the prompt library is assembled, how engines are probed, and how the composite score lands.
When an LLM cites your firm in a way that touches FCA-regulated activity, you may already have a SUP 15 reporting obligation. A walk-through of when, what, and to whom.
Why the schema models lift in answer engines is different from the schema Google rank-rewards, and what to ship first to move the AI sentence.
Independence and AI-paraphrased claims are a worse combination than most audit firms realize. The substantive analysis under §1.400 and §1.600, with concrete review steps.
A model paraphrase you didn't write can still trip Rule 7.1. A practical framework for substantiation logs and partner sign-off when AI re-renders your claims.
Inside the citation graph: how ChatGPT picks the firms it names when in-house counsel asks for a shortlist, and how to enter it without violating bar rules.
Most of what we write about is measurable. Run the free 24-hour audit and we will show you specifically what the eight engines say about your firm — verbatim.