Is your data actually ready for AI — or just plentiful?
Most AI initiatives stall on data quality and unclear ROI, not on the models themselves. Symhas' AI Analytics Readiness Audit Template is the same checklist our architects use to scope AI engagements before a single model gets built.
- ✓ Score your data quality and governance maturity honestly
- ✓ Prioritize the 3–5 AI use cases with the highest ROI
- ✓ A build-vs-buy worksheet for your first production model
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- ✓ Data quality & governance scorecard
- ✓ AI use-case prioritization matrix
- ✓ MLOps & model deployment readiness checklist
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An honest readiness check, before you spend the budget
Six sections that mirror the discovery work our AI architects do on every engagement.
Data Quality & Governance
Completeness, lineage, and access-control checks across your core data sources.
AI Use-Case Prioritization
Rank candidate use cases by feasibility and business impact, not novelty.
MLOps & Deployment Readiness
What it actually takes to get a model from notebook to production safely.
Data Pipeline & Infra Audit
Ingestion, storage, and compute checks across your chosen cloud platform.
Bias, Ethics & Compliance
Guardrails to review before any model touches customer-facing decisions.
ROI & Business Case Worksheet
A simple worksheet to defend budget for your first production use case.
Built for the people scoping the first real AI initiative
Production AI, not proof-of-concepts
Not sure which AI use case to start with?
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