Smart Data Quality (SDQ)
Data Quality Co-Pilot

Generative AI trained on Saama’s proprietary DQ check library turns plain-language requests into tested, production-ready data-quality checks.

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Smart Data Quality (SDQ) Data Quality Co-Pilot

From plain language to production check

The Data Quality Co-Pilot removes the programming bottleneck from data-quality checks. Describe the DQ check you want in plain language, and SDQ writes the code and tests it automatically using generative AI trained on Saama’s proprietary historical DQ check data. Because the Co-Pilot is grounded in years of real clinical DQ checks, it produces relevant, reliable logic — shortening the path from idea to production check and reducing reliance on specialized DQ programming.

Why teams choose the Data Quality Co-Pilot

Minutes

From plain-language request to tested check

Generative AI trained on Saama’s proprietary historical DQ check data

How the Data Quality Co-Pilot works

The Co-Pilot guides a check from request to production while keeping a human in control.

Describe the check

A user explains the desired DQ check in natural language.

Co-Pilot generates the code

Generative AI drafts the corresponding check, with an option to explain the logic it produced.

Auto-test and approve

The check is automatically tested via dry run and unit testing; a reviewer approves it and pushes it to production.

Grounded in real DQ history. The Co-Pilot is trained on Saama’s proprietary library of historical DQ checks, so its suggestions reflect proven clinical data-quality logic rather than generic patterns.

Features

Natural language to code

Turn a description into a tested check.

Automatic testing

Dry run and unit testing built into the flow.

Explainable output

Review the generated logic before approval.

Trained on proprietary data

Grounded in Saama’s historical DQ check library.