Can I trust the numbers iDBQuery gives me?
Yes — you can trust and independently check iDBQuery's numbers. Each figure runs as real SQL against your live data and is cited back to its source rows, and iDBQuery shows the query it used, so you can verify any answer instead of taking it on faith.
Trust in an analytics tool should come from being able to check it, not from being asked to believe it. iDBQuery is built around that principle.
- Real computation. Numbers are produced by SQL run against your actual data, not generated by an AI from memory.
- Cited to source. Every figure links to the exact rows behind it, so you can see what it is made of.
- Visible logic. iDBQuery shows the query it used, so a technical reviewer can confirm the joins, filters and date logic are right.
- Self-checking. The Analyst agent verifies its own steps and flags ambiguity rather than guessing.
The honest caveat is that iDBQuery reflects your data faithfully — so if a source system holds a wrong value, the answer will too. But that transparency is exactly what lets you catch it: because you can trace any figure, a suspicious number leads you straight to the row that caused it. For example, if a total looks too high, open the citation, find the duplicate transaction, and you have both the explanation and the fix. Compared with a black-box dashboard or a chatbot, iDBQuery gives you a number you can defend line by line.
Updated 2026-06-22