AI search is an unruly beast. There's no algorithm document, no index to buy, no rulebook
anywhere — and there isn't one coming. The AI engines are independent companies competing for
market share, each pulling from different sources, on different timeframes, and reading what it
finds its own way.
We knew the answer to the chaos was in the data. If no one publishes the rules, the rules are
hiding in the results. So we scanned more than 30,000 local businesses that AI systems
actively recommend and worked backward to the facts: what they have in common, and what
AI needs to see before it will put a business on its short list.
That work produced roughly 140 criteria common to every major AI system, each
weighted by how much it actually matters. And because the AI engines keep shifting, we
re-weight the criteria on a regular schedule — so you always know which
factors are gaining or losing importance, month to month.
One thing we deliberately don't do: we don't use AI to rank businesses. Scoring
and ranking are computed from historical significance across that 30,000-business dataset — not the
opinion of a chatbot. The system feels simple to use because every hard problem was solved upstream,
in the scanning and scoring engine. What you hand your client is concrete
evidence — not conjecture, not speculation, not guesswork.