Synoptek’s AI Data Readiness (AIDR) helps assess data maturity, identify AI use cases, and build an implementation roadmap to create a solid foundation for outcome-driven AI initiatives.
Synoptek’s Azure AI Data Readiness (AIDR) assessment helps organizations evaluate their data landscape and readiness to adopt AI solutions. This two-week engagement identifies AI opportunities, measures data maturity, and delivers a practical roadmap to move from data discovery to implementation.
AIDR ensures your organization’s data is accurate, available, secure, and actionable—laying a strong foundation for AI initiatives that drive measurable business outcomes.
Day 1–2: Stakeholder Interview
Conduct workshops with SMEs to understand data sources, integrations, and platforms
Map critical data domains (transactional, behavioral, third-party)
Assess risk appetite, compliance, and data access boundaries
Day 3–5: Data Evaluation & Assessment
Conduct workshops to review data readiness, connectors, and security boundaries
Assess data across five dimensions — Availability, Volume, Quality, Integrity, and Governance
Profile sample datasets by source, volume, and quality
Day 6–8: AI Readiness Evaluation
Identify 3–5 potential AI use cases
Score each using the AIDR Scoring Matrix (Business Impact, Feasibility, Adoption Readiness, Integrity, and Compliance)
Rank use cases based on readiness and strategic value
Day 9–10: Implementation Guidelines
Review AIDR scoring matrix with stakeholders
Finalize 1–2 priority use cases
Define implementation roadmap and next steps
Data Readiness Report: Scoring, gaps, and risk analysis
Scope & Roadmap Document: Prioritized AI initiatives with dependencies
Implementation Blueprint: Action steps, owners, and tool recommendations
Each dimension is rated 1–5 across:
Business Impact: Score for measurable ROI or strategic value potential.
Feasibility: Ease of implementation using the current data, technology stack, and resources.
Adoption Readiness: Organizational and business readiness to adopt and operationalize the solution.
Integrity: Quality, completeness, and lineage of data; schema health and reliability.
Compliance: Adherence to risk, privacy, and policy standards.