Modern models go beyond memory: they search the web mid-answer. We run every topic both ways and capture the sources behind the grounded answer, so you see your rank alongside the pages feeding it.
Each model runs twice a day, so you can tell what it believes from what it just read.
The model answers from its own training, its baked-in view of your market. This is what it recalls about you on its own, before any live search result.
The same prompt, this time with live web search switched on. This is the answer a real user sees today, shaped by whatever is ranking right now.
Grounded answers come with the pages the model actually pulled from. Those citations are your map of where to build presence to change the answer.
For every run we also pull a classic web search for the same question from Brave, and show it right next to the AI answers. Where the model and a traditional engine part ways, recommending different names or leaning on different pages, that gap is exactly where the opportunity, or the risk, sits.
Across every grounded run we gather the domains the models cite, rank them by how often they come up, and label each one, so you can tell a competitor from an independent publisher, a community site, or your own pages at a glance. It is a running map of the sources shaping AI answers in your market, and a shortlist of exactly who to reach out to. Aggregated per topic over time, so you see who is gaining ground.
Track grounded answers and their sources on every topic you watch.