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Scope the AI transformation, then deliver it in hours.

You sit with the enterprise to decide which data products and agents it needs, end to end. ekai turns those conversations into verified semantic models and dbt pipelines, so the plan becomes a working data product in hours, not months.

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Semantics › Sales and revenueOwner: FN

Model DetailsBusiness RequirementsAI ModelingData TransformationCode Sync

EXPLORERBusiness Requirements 6Schema NotesDBML SubsetConversation LogsBRD ReviewTechnical DocumentBusiness Requirements Document

Business Requirements Document

Executive SummaryNet revenue for the finance team, by region and quarter.

Business ContextBusiness Glossary · KPIs & Metrics · Consumer & Decision Context

Business RulesRevenue is reported by region and fiscal quarter.

Unresolved GapsGross or net AMOUNT, asked of Finance.

Business Requirements agentasking

Is `AMOUNT` gross, or net of tax and discount?

1Gross, before tax and discount. Matches the invoice total.

2Net of tax and discount, which matches the finance ledger.

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Engagements slow down before the AI work starts.

Every engagement starts with discovery.

Weeks go into learning how each enterprise defines its business before any AI work can begin.

Roadmaps stall at the data layer.

The agents are ready, but the business context they need was never written down.

Proving value takes too long.

Leaders want to see a working result early.

Customer result6 hours, $56

Secunetics built its production dbt pipeline with ekai in 6 hours for $56, against 96+ hours and about $26,400 by hand.

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Raw rows stay in your warehouse

Discovery reads your tables in place. ekai's SOC 2 Type II audit found zero exceptions.

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