SQL Transparency in Analytics | Kubit AI You Can Trust

See the SQL behind every insight

Every report. Every explanation. Full visibility into how your AI Analyst builds answers. Directly in your warehouse.

Why SQL Transparency Matters

Full Visibility

We surface the SQL behind every report your Agentic AI Analyst runs, showing joins, filters, and calculations in plain view. .

Preserve data quality

We surface the SQL behind every report your Agentic AI Analyst runs, showing joins, filters, and calculations in plain view.

Warehouse Native

Our warehouse-native design means every report runs on governed data with zero duplication or data movement.

Data Transparency and Control

Dynamic configuration

Insights are generated in real time from warehouse data — no caching, scrubbing, or vendor intervention. Teams know exactly how numbers are created, protecting reconcilability and trust.

Real-time adaptability

Analytics reflect changes to the underlying data instantly. Test new hypotheses with virtual events or properties and analyze unstructured data without delay.

Flexible data modeling

Support for multi-schema environments allows raw and clean data to coexist. Updates to dimensions apply across historical data automatically, without backfills. Combine operational and clickstream events seamlessly for a unified view.

Hear from Our Customers

“With Kubit, we’re enabling self-service analytics and giving our Data Team a better experience—with a faster turnaround to insights.”

When Alex Li was a CTO, he faced the same problems every digital-first leader knows: endless waits for reports, data locked in ETL jobs, and dashboards that showed “what” but never “why.” He built Kubit so teams could finally get the answers behind the numbers without bottlenecks, black boxes, or wasted cycles.

“Within a month of onboarding Kubit we were able to analyze and improve our onboarding flows, increasing ROI by over 30%, which paid for the whole year of service many times over.”

“With Kubit, if I have a question pop into my mind about user behavior, within a minute or two, I can get an answer.”

“We had over a year’s worth of Snowplow data sitting idle in a data warehouse. Data Analysts were swamped with questions, requiring custom SQL to be written, or a day’s worth of planning to execute problem solving. Now, we get insights in minutes.”

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