The Challenge
Supply chain data was severely fragmented. Critical information lived in siloes: master data in SAP, real-time updates in 5,000+ WhatsApp messages, and planning in offline Excel sheets. This created a "Tower of Babel" scenario where no single party had visibility on stock reality or lead times, leading to stock-outs and excess inventory.
- Disconnected data (SAP vs. WhatsApp vs. Excel).
- Reactive firefighting instead of proactive planning.
- High risk of stock-outs due to lack of visibility.
The AIQU Systems Solution
We built a centralized Supplier Collaboration Hub that acts as a middleware layer. It ingests and normalizes data from all sources—extracting text from PDFs and chats using AI. The system then runs predictive models to detect forecast deviations and automatically triggers call-off signals to suppliers.
- AI extraction of unstructured data (PDF/Chat).
- Predictive "Risk Scoring" for potential stock-outs.
- Self-healing inventory dashboard.
System Architecture
Inputs
SAP / WhatsApp / Excel
AI Logic Core
- Data Normalization
- Anomaly Detection
- Demand Prediction
Portal
Supplier Access
Actions
Auto Call-Offs