Product · Ask
Ask your data, see the answer’s workings
Most questions about data are simple to ask and slow to answer. Natural-language querying shortens that loop, provided the answer is transparent.
From question to checked answer
- 01
Ask in your own words
“How many records were added last quarter, by region?”
- 02
See how it was answered
The datasets used, the generated query and any filters or assumptions are shown next to the result.
- 03
Check and refine
Adjust the question, correct an assumption, or open the query to edit it directly.
- 04
Share with context
Share the answer together with its sources, so the next person does not have to start again.
Where natural-language querying goes wrong
Language models can misread an ambiguous question, pick the wrong table, or produce a confident-looking number from incomplete data. Good practice is to ground answers in documented datasets, show the query, flag low-confidence results and keep a human in the loop for anything that matters.