Submission type
UiPath for Coding Agents
Name
Warehouse Management System - Predict shipping delays
Industry category in which use case would best fit in (Select up to 2 industries)
Operations
Complexity level
Intermediate
Summary (abstract)
The project tackles the challenge of detecting shipment delays, a task traditionally difficult to do manually and most of the times done too late to prevent issues.
It automates data extraction from the WMS and uses an AI agent to predict delay risks and explain the causes.
When a risk is detected, it alerts the manager and recommends alternative suppliers with lower delay probability.
Detailed problem statement
Modern logistics operations rely on timely deliveries, yet many organizations still detect shipment delays only after they have already occurred, causing customer dissatisfaction, operational bottlenecks, and increased costs. Shipment monitoring is typically performed manually by reviewing WMS data, which is slow, error‑prone, and unable to scale with growing shipment volumes.
Teams lack predictive insights and have no systematic way to analyze historical delay patterns. As a result, managers receive late or incomplete information, limiting their ability to take proactive corrective actions.
Detailed solution
The solution automates the early detection of shipment delays by combining RPA, AI Agents, and RAG‑based knowledge retrieval. It eliminates manual monitoring, provides predictive insights, and proactively alerts managers when shipments are at risk. The entire system is orchestrated and generated using UiPath Coding Agents powered by Claude Code, which automatically produces the SDD, tasks, RPA workflows, and agent logic through the UiPath CLI.
Description
-
Data Extraction via RPA (UiPath Robot)
The workflow begins with a UiPath RPA process that interacts with the internal Warehouse Management System (WMS). -
AI Agent Processing (Delay Prediction Agent)
Each shipment record is passed to a custom AI Agent built using UiPath’s Agent Bulider and generated via Coding Agent + Claude Code.
The agent uses Retrieval‑Augmented Generation (RAG) to enrich its predictions, with historical shipment data -
Risk Evaluation & Decision Logic
The RPA workflow receives the agent’s response and applies business rules:
- If delay_probability < threshold → mark as On Track
- If delay_probability ≥ threshold → trigger an exception workflow
- Manager Notification & Escalation
For shipments flagged as high‑risk, the automation generates a proactive alert.
The notification includes:
The entire solution is produced using UiPath’s Coding Agent, which leverages Claude Code to:
- Create SDD (from a initial PDD)
- Create Task details
- Verify and enrich the RPA workflow
- Create and integrate the Agent
Narrated video link (sample: https://bit.ly/4pvuNEL)
Expected impact of this automation
The automation dramatically reduces manual monitoring time by eliminating daily WMS checks and enabling instant, AI‑driven delay detection. Predictive insights and early alerts help prevent costly disruptions, improving on‑time delivery rates and supplier performance. Overall, organizations can expect faster decision‑making, fewer operational bottlenecks, and a strong ROI driven by time saved, reduced delays, and improved service quality.
UiPath products used (select up to 4 items)
UiPath Agent Builder
UiPath Automation Cloud™
UiPath Studio
Automation Applications
Internal WMS System, Excel
Integration with external technologies
Outlook
