How does AIQ track narratives across multiple AI platforms simultaneously?

AIQ tracks narratives across multiple AI platforms by running identical prompts against the eight engines it currently tracks in parallel, then exposing the differences directly. The actionable layer is the source-level diagnostic that sits next to the comparison view.

For every topic, the same prompts run against ChatGPT, Gemini, Copilot, Perplexity, Claude, Grok, Google AI Overviews, and Google AI Mode at the same time, so the responses are directly comparable.

What the parallel, multi-model view shows

• Side-by-side responses. The multi-model comparison view places each engine’s answer next to the others, so divergence is visible at a glance – when ChatGPT is telling one story and Gemini another, the difference is on screen rather than buried.
• Per-engine source attribution. Beside the comparison view, the platform shows which sources each engine is pulling from. That source-level diagnostic is the actionable layer: it shows not just that engines differ, but why.

Why per-engine differences matter

A brand is rarely uniformly well or badly described across leading AI engines; the picture is usually mixed, and the leverage points are different per engine. By showing the differences and the sources driving them, AIQ gives a comms team the specific information it needs to decide what to do – and where.