Autonomous Supply Chain Disruption Management Using Microsoft Foundry
Microsoft Foundry helps supply chain teams detect disruptions, assess impact, evaluate recovery options, and accelerate informed operational decisions.
Business Process Challenges
Supply chain operations were managing high shipment volumes across ports, carriers, distribution centers, suppliers, and transportation lanes. Operational data was distributed across multiple systems, making it difficult to quickly connect disruption events with affected shipments, customers, routes, and commitments. This created delays in assessing impact and identifying suitable recovery actions.
- Operational data was scattered across transportation systems, shipment records, carrier updates, warehouse information, and external disruption signals.
- Teams spent significant manual effort connecting disruption events with affected shipments, customers, routes, and delivery commitments.
- Alternative carriers, routes, transportation modes, and delivery plans had to be evaluated manually across multiple systems.
- Decision-making relied heavily on individual expertise during high-impact disruptions.
- Executives lacked a continuously updated view of disruption exposure, recovery actions, and business impact.
Our Strategic Approach
We designed an AI-powered, multi-agent solution using Microsoft Fabric and Microsoft Foundry to create a connected disruption management workflow. The architecture brings together supply chain data, specialized AI agents, automated workflows, and Power BI to help teams move from disruption detection to recovery actions with human oversight.
- Used Microsoft Fabric as the unified data foundation for shipment, carrier, route, warehouse, and disruption data.
- Used Azure OpenAI for reasoning, summarization, classification, and recovery recommendations.
- Used Azure Functions for event-driven processing, enrichment, scoring, and integrations.
- Used Power Automate to manage approvals, notifications, and approved operational workflows.
- Implemented specialized agents for disruption detection, impact assessment, risk analysis, alternative evaluation, and recovery recommendations.
- Added human-in-the-loop controls for high-risk decisions before execution.
- Used Power BI to provide operational and executive visibility into disruptions, risks, affected shipments, recommendations, and recovery progress.
Our Engineering & Delivery Process
Our structured project delivery approach takes you from discovery and planning to development, testing, and deployment, ensuring quality, transparency, and predictable outcomes at every stage.
Discovery & Architecture
Deep-dive technical audit of existing systems, security baselines, API mapping, and comprehensive cloud target blueprinting.
UX & System Prototyping
Role-based user journeys, wireframing, high-fidelity clickable Figma prototypes, and API contract specifications prior to build.
Agile Sprint Engineering
Modular development sprints delivering clean, shippable code with automated CI/CD pipelines and continuous testing.
QA & Security Hardening
End-to-end regression suites, cross-device verification, load stress audits, and penetration testing for enterprise resilience.
Production Launch & Scale
Zero-downtime blue-green production deployment, real-time telemetry, administrator training runbooks, and ongoing SLA support.
Explore the Solution Through visuals
What changed for the client.
The solution transformed supply chain disruption management into a more connected and proactive process. AI agents helped teams identify disruption exposure, assess operational impact, evaluate recovery options, and coordinate approved actions while maintaining human oversight. Faster identification of supply chain disruption exposure.
- Reduced manual effort in tracing disruptions to affected shipments and commitments.
- More consistent evaluation of recovery alternatives.
- Improved coordination across logistics, transportation, customer service, and management teams.
- Greater visibility into disruptions, recommended actions, and recovery progress.
- Human oversight maintained for high-value and high-risk decisions.
- Scalable foundation for expanding automated decision support across additional supply chain scenarios.
The numbers behind the rollout.
The full integration layer.
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