Raising Azure and AI Engineering Practice Across Multiple Operating Companies
$3B+ Publicly-Traded Industrial Manufacturer
Business Situation
A publicly traded industrial manufacturer was running AI and Azure initiatives independently across several operating companies, each with its own engineering team, cloud footprint, and delivery approach.
The Challenge
Capability was accumulating inside individual teams rather than across the group, with architecture, identity, and cost decisions made separately on each initiative. Left alone, that divergence compounds with every system added.
Why It Matters
Compose ran recurring advisory sessions with the client’s engineering teams across their active AI and Azure workstreams, reviewing solution architecture, Azure OpenAI usage patterns, permissions and identity, the Power BI and Azure data estate, and production-readiness practices, with written technical overviews per topic.
What Compose Delivered
- Recurring technical advisory sessions with client engineering teams
- Solution architecture reviews across multiple operating companies
- Azure OpenAI usage patterns and cost-management guidance
- Permissions and identity guidance: managed identity, Key Vault, RBAC
- Azure data platform review: Power BI, Azure SQL, Data Factory
- Production-readiness guidance: hosting, CI/CD, environment promotion
- Written technical overviews issued per session topic