10-Minute AI Governance Readiness Assessment
Rapid single-stakeholder maturity benchmark across the 7 pillars.
- Best fit:
- AI, data, or governance leader exploring readiness
- Deliverable:
- Score, radar, top 3 risks
Data Fusion Analytics delivers two integrated practices: ProofLayer AI for AI governance auditability, and enterprise Data Architecture for the platforms that make governance provable.
Stakeholder invitations, role-based variance, downloadable Blueprint, and expanded recommendations. Paid via card — no procurement required.
Pick a role your client is trying to fill, or paste a job title. We'll suggest a scoped Data Fusion Analytics engagement that can help now — often while a permanent hire is still being recruited.
Likely client need: Lakehouse architecture, Unity Catalog governance, migration planning, performance, security, or platform standardization.
Structured three-week review of your Databricks or lakehouse estate covering architecture, Unity Catalog, workload patterns, and governance readiness.
Rapid single-stakeholder maturity benchmark across the 7 pillars.
Multi-stakeholder assessment identifying auditability, evidence, and variance gaps.
30–60 day engineering engagement closing top identity, access, lineage, and evidence gaps.
Recurring advisory + engineering for AI systems, evidence, and control drift.
Secure, scalable warehouse and lakehouse designs for analytics and AI.
Pipeline design, refactoring, orchestration, and performance tuning.
ADF and Databricks patterns, workflow design, and lakehouse enablement.
Fabric and Synapse workspace design, security, and analytics enablement.
Access controls, lineage, metadata, quality, and audit-ready design.
Power BI, Tableau, semantic models, and executive reporting design.
Legacy-to-cloud migration, lakehouse modernization, environment redesign.
Tuning compute, storage, and pipelines for scale and cost.
Side-by-side comparison is included at the top of every Blueprint Report preview.