Case Study
- Order Spikes Analysis
- Product Data Hub Implementation
- EXADATA Hardware Migration - X9 to X10
- Legacy System Migration to Oracle with Golden Gate
- Migration of PeopleSoft HCM to Workday HCM
- Standardizing Item, UOM and XRef Processes with EBS
- EBS Item-Vendor Sync Resolution
- PlannerSync PDH
- Dynamic System Integration
- Agile OU Operations
- IaC Enablement Process
- Oracle EBS Optimization Initiative
- Security Patching with Ansible
- Automated Patch Management
- MC Product Hub
- Scalable Division Setup Without Hard Coding
- Data Cleanup
- Multi Unit Integration Under Single Responsibility
- CDH Enablement for Grocery
- OMS Online
- SourceLink, UAM, MESA - Angular and Java
- SailPoint IIQ
- QA Test Automation
- Devops
- Optimizing Testing Strategies in the LedgerIQ
- Java Revamp
- Enhancing Academic Efficiency Through Digitization
- API Management
- OMS Batch Modernization
- Linux Server Automation with Ansible
- Securing Servers through Standardized Hardening
- Azure Recoverability Initiative
- DC Ops Analytics
- Katalon Automation
- Linux Administration
- Leveraging AI in IoT Systems
- Intelligent Discrepancy Resolution Assistant
- AI-Driven Supply Chain Anomaly Detection and Risk Insights
- AI-Driven Traceability Platform
Predictive Delivery Assistant
A blockchain-powered chat-based tracking system enhances customer experience by offering transparent, predictive and automated delivery updates-reducing support load and improving reliability.
Problem
Statement
Customers often face frustration due to delivery delays and lack of real-time tracking clarity, leading to increased support tickets. Manual handling of these issues is time-consuming and error prone.
Solution
Proposed
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Enables a chat-based tracking experience, allowing users to ask questions like “Why is order #456 late?”.
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Pulls real-time tracking data from blockchain ledgers for accurate responses.
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Analyzes delivery exceptions (e.g., customs delays) and provides clear explanations.
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Automates customer updates and sends delay notifications proactively.
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Predicts potential delays using past delivery and exception patterns.
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Detects inconsistencies in blockchain records to maintain data integrity and trust.
Business
Values
01
Reduces support tickets by 40% through self-service tools.
02
Speeds up exception resolution, improving delivery performance.
03
Delivers transparent, verifiable order updates.
04
Strengthens SLA compliance with proactive alerts.