What in-house AI visibility tracking costs to run

The cost of collecting AI answers in-house is rarely the API bill you avoid. It is the engineering time to reach production quality on each engine, plus the maintenance that follows for as long as you run it. Building is the right call when the collection layer is itself your product or you need data no provider returns; the build vs buy comparison covers that decision, and the framework below fills in the numbers behind it. Definitions Collection layer: everything between "we have a prompt" and "we have a structured record of what the engine answered": execution, parsing, retries and storage. Analysis layer: what you build on top: share of voice, citation tracking, competitor reports, alerts. This is where customers compare products. Run: one prompt, on one engine, in one market, collected once. What building involves Consumer AI products such as ChatGPT, Perplexity, Gemini, Copilot, Grok and Google AI Mode show answers that include web search, citations,