Natural-language analytics is only useful if the answer is trustworthy. A model that hallucinates table names produces confident, wrong numbers.
SemanticFed is built so a plain-English question resolves against the governed semantic model: the metrics and dimensions it references actually exist and are documented, and the resulting federated query is inspectable. Access policy applies to the generated query exactly as it would to a hand-written one.
A business user gets an answer in seconds; a skeptic can open the query plan and see precisely how it was computed.
An illustrative pre-launch scenario describing the natural-language interface being built.
The natural-language interface is still on the roadmap; this story is illustrative and does not yet have a clickable "Do it yourself" web walkthrough.
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