Kappa — Usable Signal From Unstructured Data

How do you pull usable signal out of unstructured data with AI — and make its reliability measurable?

• The problem: unstructured data is a gold mine, but unusable as-is. How do you pull signal you can rely on out of it, with AI?
• The measure, and the name: a high kappa — the measured agreement between the AI and ground truth. An AI that calibrates itself and watches its own performance and drift, rather than promising a reliability you couldn't check.
• The method: MECE decomposition + ground truth built with Tinderize; analyses plug into the IS data via MCP.
• The idea: have the AI build knowledge corpora on demand, on a given problem — then reusable in the IS alongside the rest of the data.