Audit departmental needs.
Evaluate the distinct operational and data requirements across all seven business units.
All case studiesMulti-division industrial group
Preemptive Enterprise Architecture: Mitigating Tech Debt Across Conglomerates
Seven distinct operational departments were preparing to independently procure and build siloed AI solutions. We preempted this fragmentation by designing a unified, enterprise-wide architectural layer for the entire corporate group to build upon.
Company profileMulti-division industrial group.
Systems in playFinance, stock, imports, transport, factory operations, HR, and customer service data streams.
EngagementTop-down enterprise AI architecture design and foundational deployment.
How the build ran.
The same stepped process we run on every engagement, applied to this company.
Define core infrastructure.
Engineer a singular, scalable foundational layer capable of supporting diverse operational schemas natively.
Establish build governance.
Mandate top-down that all operational units must sit on, and build within, this shared layer.
Sequence the rollout.
Deploy the central architecture immediately to prevent localized groups from wasting budgets solving the same problem.
The architecture, in one picture.
The Sources (seven departmental data streams) flow into The Shared Company Layer (a standardized enterprise schema), which feeds Department-Specific AI Tools and Executive Dashboards.
The sources
7 Departmental Data Streams
The shared company layer
Standardized enterprise schema
What reads from it
Department-Specific AI Tools
Executive Dashboards
What changed operationally.
Erased Technical Debt.
Prevented the creation of seven incompatible AI systems, establishing clean governance from day one.
Unified Conglomerate Data.
Leadership gained instant, cross-departmental alignment built on a single architectural foundation.
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