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Ask in plain language

Your question becomes a governed query, not guessed SQL.

Type the question the way you would say it out loud. Reveliqo resolves the wording to named metrics, approved dimensions and an explicit period, then hands it to the semantic layer to compute. Where a term maps to nothing in the model, it asks instead of approximating.

Natural Language Analytics

  • Plain-language questions across all four layers
  • Resolution to named, governed metrics
  • Explicit period and segment scoping
  • Ambiguous terms flagged, never guessed

How it helps

What Natural Language Analytics gives you

1

Governed vocabulary, not free-text SQL

Questions resolve against the metric catalogue. ‘Revenue’ is the definition your finance data already uses; ‘trial’ is the business event you already send. The agent cannot reach a metric that is not modelled, so it cannot quietly invent one.

2

Ambiguity is surfaced, not guessed

‘Last quarter’ in a fiscal year starting in April, or ‘customers’ when you mean accounts: Reveliqo states the reading it took and offers the alternative in one click, rather than picking silently.

3

The question decides the layers

‘How much revenue came from organic traffic?’ needs edge referrer data and invoiced revenue in the same query. Reveliqo selects the layers the question implies, instead of asking you to choose a report first.

Connect a site today. Read tomorrow's brief instead of building it.

Connect a site and the first brief arrives with the day's changes already explained — traffic separated from bots, conversions attached to revenue, and the evidence behind every sentence one click away.

Real people separated from bots Every answer shows its evidence Reveliqo runs on Reveliqo