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Home / The method

ekai runs discovery first, then semantics and ontology.

ekai builds a semantic layer in six steps. Discovery: connect, model the structure and draw the architecture plan. Then semantics and ontology: generate, verify and publish.

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What does ekai ask your experts?

Plain questions, grounded in your actual data. Your expert answers once, and the answer becomes a written, owned definition.

ekai asks

"customers.type shows 18% trial. Do trials count as active customers?"

18% trial
Your expert answers

"No. Active means a completed order in the last 90 days."

✓ Definition capturedActive customer · completed order in the last 90 days
Illustration · demo data

How does a business question become a trusted answer?

1 · You ask"What was net revenue last quarter?"
2 · ekai finds the dataIt knows which tables hold the answer.SALES.ORDERSSALES.CUSTOMERS
3 · It applies the definitionNet revenue, as approved by Finance.AMOUNT − TAX − DISCOUNT
4 · You get a trusted answer$1.32Mnet revenue, last quarter
Illustration · demo data

How does ekai check a model before it ships?

Every miss becomes a new test.

Validation rules
dbt tests
Independent review
Approval checkpoints
Human review
Every miss becomes a new test
Illustration · demo data

Of three ways to build a semantic layer, only one proves the result.

Where meaning comes from
Checked against your warehouse
Time to a first model
Who keeps it current
What you own
Best fit when
Built by hand
Where meaning comes fromYour experts, through long modeling engagements
Checked against your warehouseRarely, and by hand
Time to a first modelMonths
Who keeps it currentYour engineers, by hand
What you ownStandard code, if it was written that way
Best fit whenYou have a small, stable set of metrics and time to spare
Mined from query history
Where meaning comes fromWhatever past queries happened to do
Checked against your warehouseNo
Time to a first modelFast, but it repeats the past
Who keeps it currentWhoever writes the next query
What you ownDepends on the tool
Best fit whenYou only need to reproduce existing reports
ekai
Where meaning comes fromYour experts, asked only what the data cannot explain
Checked against your warehouseEvery definition, before it publishes
Time to a first modelHours, not months
Who keeps it currentYour experts and engineers, with ekai drafting the changes
What you ownStandard dbt, YAML and JSON in your own Git
Best fit whenYou need AI tools to give verified, consistent answers

Common questions

Last updated October 28, 2026

How does ekai build a semantic model?

In six steps. Discovery: it connects, models the structure with the Onboarding Agent and draws the architecture plan with the Schema Agent. Then semantics and ontology: it generates the model with your experts, verifies it and publishes it.

Does ekai use query history?

No. ekai learns from your data and your experts rather than mining query history.

Where does ekai publish semantic models?

To Snowflake semantic views and Cortex Agents, Databricks Genie, BigQuery data agents, or dbt MetricFlow for Postgres and Redshift, plus a dbt project in your own Git.