AI-Driven Delivery Delay Automation for PepsiCo
This project focused on automating delivery status updates & delay tracking across multiple ServiceNow instances for PepsiCo’s logistics operations. Each instance—Logistics, Retail, and Delivery—was previously siloed, causing delays and data inconsistencies. The new AI-powered framework now connects them in real-time.
Using AI Agent Studio and the Multi-Client Processor (MCP), this system detects late deliveries, calculates penalty impact, and auto-updates records across instances. It also monitors system logs using an intelligent agent that flags repeated failures, reducing troubleshooting time and improving uptime.
- Reduced dispatch update time from 20 minutes → under 3 seconds
- Eliminated manual coordination between teams
- Enabled proactive issue detection through AI log analysis
Project Information
- Category: AI Automation
- Type: ServiceNow System
- Client: PepsiCo (Simulation Project)
- GitHub Repo: agentic-logistics-incident-response
Key Highlights
- Built cross-instance orchestration using MCP
- Integrated AI Agent Studio for predictive logic
- Achieved real-time dispatch automation
- Cut manual coordination by 100%
- Implemented proactive log anomaly detection