Why Response Reviewer and Highlight Collector Exist — The Verbose-Prose-to-Tabular Bridge

The core impedance mismatch Augment-It solves: CRM data is tabular (rows × columns, succinct cells), while LLM and Deep-Research responses are verbose markdown prose (paragraphs, hedging, citations, expansion). Augment-It's purpose is to turn prose back into something that fits in a CRM cell. The response-reviewer and highlight-collector are the two pipeline stages where that bridge gets built — and they exist because no structured-output regime, however good, removes the need for a human-in-the-loop integrity check before tabular data gets written back into a system of record.