Multi-engine monitoring is the daily practice of measuring where your brand appears across every AI engine that answers buyer questions. You see who cites you, what they quote, which queries you own, and which ones your competitors are stealing. You see it every morning, not every quarter.
ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews, Bing Copilot, and Grok each pull from a different slice of the web and each refreshes on its own schedule. We run your category's real prompts against all seven, every day, and ship you one number that moves: citation share. When a model refresh redraws the map, you know the same morning, not six weeks later.
Most brands measure AI visibility once a quarter, from one engine, on a prompt list some analyst wrote six months ago. Then a model refreshes, the retrieval behavior shifts, and the report is fiction by lunch. The engines don't tell you when they change. You find out when a competitor's name starts showing up in your pipeline.
Before and after, across a typical 90-day engagement. Directional, representative. Your numbers will differ.
We don't publish the playbook. The advantage is in the execution, not the explanation. If we taught it, it would stop working. Not just for you, for everyone we work with. What we'll show you is the result.
A category-leading fintech brand grew its citation share across seven engines from 3% to 41% in 90 days. Without publishing more content.
Each engine retrieves from a different mix of sources and refreshes on its own schedule. ChatGPT, Perplexity, and Grok index live web differently; Claude leans harder on training data; Gemini and Google AI Overviews blend retrieval with Google's index; Bing Copilot reflects Bing's. A single-engine dashboard hides most of the truth about your visibility.
A refresh is when an engine updates its retrieval index, ranking model, or underlying weights. Your citation share can move ten points overnight. Brands watching quarterly reports discover the damage six weeks in. Daily monitoring catches it the same morning.
We start from your category's real buyer questions, sourced from search intent data, sales calls, support tickets, and community threads. The prompt set grows every month based on what's actually moving the needle, not a static keyword list.
Every 24 hours against all seven engines, plus targeted re-runs within minutes of a detected refresh. The dashboard shows the last run timestamp and the next scheduled one.
Yes. Every sample is archived with the full response text, the citation list, the timestamp, and the prompt. Click any data point to read exactly what the model said and who it cited.
We maintain four independent retrieval paths per engine so a single API change never blinds the dashboard. When an engine removes citation metadata, we fall back to named-entity extraction on the answer body itself.
A free citation audit shows exactly which queries surface you, which surface a competitor, and what's costing you share.