What is Five Blocks’ AI reputation methodology?

Our AI reputation methodology is the same Track / Analyze / Impact framework we built for the Google era, applied to the AI layer. The Track phase uses AIQ to capture what each of eight engines is actually saying about the client and named peers, the sources each engine is citing, the sentiment and themes, and the trajectory over time. The Analyze phase identifies the leverage points: which sources are driving which framings, where the engines diverge from each other, where peer comparisons reveal opportunity, and which interventions will most efficiently move the picture. The Impact phase does the hands-on work on those sources (Wikipedia, Wikidata, owned content, authoritative third-party coverage, structured entity signals), that is, changing the sources the engines read rather than the engines themselves. Trying to fix things by prompting the engine directly does not work and is not part of our approach: the engine does not remember what you tell it and rebuilds every answer fresh from the sources it trusts, so the only durable fix is at those sources.