Infrastructure Precedes Autonomy.
AI agents do not fail because of models.
They fail because of weak semantic layers, fragmented governance, and unprepared data estates.
Strategic advisory for healthcare and energy enterprises building an Agent-Ready Data Estate.
The Iceberg Beneath Enterprise AI
Conversational interfaces create the appearance of readiness.
Beneath every agent interface lies the architecture that determines success:
Data modeling discipline
Semantic layer clarity
Governance enforcement
Security segmentation
Observability and audit controls
Organizations that invest only in the visible layer repeat the failure pattern observed in early cloud BI initiatives.
The interface improves.
The underlying estate does not.
An Agent-Ready Data Estate is engineered below the waterline.
Strategic Capabilities
Agentic Strategy
Designing the transition from insight to autonomous execution.
I architect transformation roadmaps that align governance, semantic layers, and risk controls with autonomous AI systems that drive measurable outcomes.
Modern Architecture
Building the Agent-Ready Data Estate.
I assess and refactor legacy data environments into scalable, governed architectures — decoupling storage from compute while enforcing semantic integrity and cost discipline.
Analytic Governance
Governance as the architecture of trust.
I implement row-level security, lineage, and policy enforcement frameworks that ensure data is safe enough to be autonomous.
How We Engage: The Agent Readiness Audit
You don’t need another dashboard. You need a diagnostic.
In a focused 4-week engagement, I evaluate your schema design, semantic integrity, and security segmentation to determine your organization’s readiness for Agentic AI; whether you are scaling an existing data team or building one.
Deliverable:
A Red / Yellow / Green roadmap identifying immediate risks, 90-day priorities, and longer-term architectural investments.
This engagement is designed for healthcare and energy organizations preparing to scale AI beyond dashboards.
Selective Fractional CDO and Executive Advisory engagements for mid-market healthcare and energy organizations.
Dr. Malik Al-Amin, DIT
Scholar-Practitioner, Agentic Data Architecture
Bridging the gap between technical architecture and executive strategy.
Organizations are shifting from static BI (dashboards) to Agentic BI (autonomous action). AI agents, however, cannot operate safely on ungoverned data.
Dr. Al-Amin bridges theoretical rigor with enterprise execution. A "Scholar-Practitioner" with a Doctorate in Information Technology, He does not deploy AI. He architects governance and lineage — the guardrails that allow organizations to move fast without breaking.
During his tenure as Interim Director of Data & Analytics, he led the transformation of cost-center data infrastructure into revenue-aligned assets.
Advisory Mandates and Board-Level Engagements by Invitation.
For strategic engagements, board advisement, or executive-level transformation initiatives: