Does iDBQuery explain how it reached an answer in plain language?
Yes — alongside the number, chart, or table, iDBQuery explains its answer in plain language, states any assumptions it made (like the date range or how a metric was defined), and cites every figure back to source rows. You get the result, the reasoning, and the evidence together, not a bare number.
A figure with no context is hard to trust and easy to misuse, so iDBQuery presents answers with their reasoning attached.
- Plain-language explanation. It describes what it did in words a non-technical reader can follow — which data it used, how it filtered, what it calculated — so the answer is understandable without reading SQL.
- Stated assumptions. If it resolved "last quarter" to specific dates, chose the invoice date over the ship date, or applied a particular metric definition, it says so, so nothing important is hidden.
- Evidence on demand. For those who want to go deeper, the generated SQL is visible and every figure is cited to its exact source rows.
This layered transparency serves everyone: an executive reads the plain explanation and trusts it; an analyst inspects the SQL and citations to verify it. It's the core of iDBQuery's answer over a black-box chatbot that just asserts a number. For open-ended investigations, the Analyst agent extends this by narrating each step of its reasoning. Either way, the principle holds — you never have to accept a figure on faith, because the explanation and the receipts always travel with it.
Updated 2026-06-22