Problem Statement

The customer had a multi-region logistics network with:

• Global SD-WAN and MPLS links
• Cloud applications in AWS and Azure
• On-prem warehouse and distribution center infrastructure

Despite significant investment in tools, they faced:

Architecture

Scout-itAI sits on top of existing tools and AppNeta for global logistics to deliver AI-driven incident response:

• Telemetry Ingest: AppNeta provides path-based network performance monitoring for logistics (latency, jitter, loss), while other NPM/APM/log tools feed events into Scout-itAI.
• Reliability Intelligence: Scout-itAI converts raw metrics into a unified RPI Score, applies Six Sigma (Blender) and KAMA trends (Trender) to detect anomalies and uses Predictor to simulate reliability impact of changes.
• Agentic Automation: An agentic AI framework runs automated root cause analysis for logistics incidents, opens tickets in ITSM tools and routes context-rich incidents to NOC/SRE teams.
• Business View: Dashboards show end-to-end paths, RPI by region/app and business impact (orders, SLAs, delays) for incident response for global logistics.

Results & Outcomes

• MTTR Down 40–60%: Automation and RCA reduced investigation time, accelerated real-time incident response logistics.
• Fewer Shipping Delays: Proactive detection of network performance issues in global logistics operations reduced delay-related incidents.
• Clear Reliability Story: RPI Scores gave IT and business a common language to talk about logistics incident management automation.
• Better Network Performance: Monte Carlo forecasting told where to invest in carriers, routes and regions to optimize global logistics network performance.

TCO & Operational Efficiency

• Tool Consolidation: Scout-itAI unified event intelligence on top of AppNeta and existing tools, reduced overlapping licenses.
• Less Work: Automated workflows reduced manual triage and ticketing, so NOC was more productive.
• Downtime Savings: Less downtime and fewer SLAs helped offset the cost of Scout-itAI.
• Investment Reuse: We reused existing AppNeta deployments and observability stacks instead of replacing them, so total cost of ownership was flat.

Lessons Learned

• Prioritize Critical Paths First: Start with lanes where downtime hurts most, then expand.
• Make RPI the Common Language: Use RPI to align network, app and business teams on reliability.
• Bake Automation into Existing ITSM: Put Scout-itAI incident response automation into current ticketing and NOC workflows.
• Tie Incidents to Business Impact: Always frame issues as delivery risk, SLAs and customer impact.
• Tune Policies Continuously: Use Blender and Trender to adjust thresholds and automation over time.