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DataReady AI Lab

How the Audit Works

A practical AI-ready data audit is not an AI tool rollout. It is a careful readiness review that helps leaders understand what data they have, what is missing, what needs cleanup, and what can safely come next.

1

Scope the Review

We identify the organization type, reporting goals, data sources, constraints, and privacy boundaries.

2

Review Safe Samples

Only sample, anonymized, or non-sensitive examples are reviewed before any formal agreement. The public request path does not accept uploads.

3

Assess Readiness

We score data quality, KPI clarity, dashboard-readiness, automation opportunities, and future AI/RAG suitability.

4

Prioritize Improvements

Recommendations are grouped by impact, effort, privacy sensitivity, and whether the work should happen before dashboards or AI.

5

Plan the Next Build

The organization can optionally move into dashboard prototyping, workflow automation, or private document-search planning later.

Privacy Boundary

Privacy and Scope Boundary

The public request path does not include uploads, automatic AI analysis, payment checkout, or a client portal. Confidential data should not be sent through the public form.

No public upload
No payment workflow
No client portal
No automated AI analysis
No automatic document processing
No confidential data through public forms