Natural-language querying
Ask business questions against modeled warehouse data
Business teams often wait on analysts for answers that fall outside existing dashboards. ThoughtSpot shortens that queue with search-led analytics, governed metrics, and embedded BI built for cloud data warehouses.
When teams need an answer no existing report covers, ThoughtSpot lets them search governed warehouse data in natural language and refine the result as a chart or table. Liveboards collect findings for recurring monitoring, while Spotter adds conversational AI to the same semantic layer.
ThoughtSpot uses contract pricing rather than a public monthly subscription. Cost varies with deployment, usage, user roles, and embedding needs, so buyers need a sales quote. Trials can support evaluation, but there is no practical free BI tier.
The experience feels quick once models and synonyms are prepared. That work matters: ambiguous fields, weak naming, or complex joins produce confusing answers. Data teams still own permissions and performance tuning, so the platform reduces ad hoc reporting rather than removing BI administration.
Ask business questions against modeled warehouse data
Pin answers and track changing operational metrics
Create follow-up questions, summaries, and visual answers
Add interactive analytics to customer-facing applications
Define joins, formulas, synonyms, and access controls
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