Challenge
Multiple engineering teams working across Supply Chain and Support Services were operating in silos, each dealing independently with challenges around cloud monitoring, infrastructure deployment consistency, and access to operational data. Teams needed a way to move faster without adding headcount or centralizing everything through bottlenecks.
What We Did
FusionHit introduced AI tooling across three distinct layers of the engineering and operations stack:
- Development acceleration — AI integrated directly into the React and .NET development workflow, generating coded UI tests and unit tests in context, reducing QA cycles.
- Infrastructure as code — AI-assisted generation and validation of Bicep templates against cloud best practices, reducing deployment errors and review time.
- Operational intelligence — Teams built AI-powered agents in Microsoft Teams using custom embeddings and RAG connected to SQL databases, enabling non-technical users to query operational data and generate reports conversationally, without writing SQL or involving data teams.
Azure MCP Server was integrated directly into the development environment, giving teams real-time access to logs, resource monitoring, and AI recommendations without switching tools.
Results
- Deployment error rate reduced through validated IaC templates
- Operational reporting democratized across Supply Chain and Support Services — from data team dependency to self-serve
- Developer productivity increased across React and .NET codebases with AI-generated test coverage
Why It Matters
Enterprise organizations don’t need one AI project — they need AI embedded across the stack. This engagement shows what it looks like when multiple teams adopt AI in parallel, each at their own layer, with compounding results.
