Nyra
Nyra
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Developing an AI Agent that analyzes automated ordering systems, applies supplier policies, and recommends optimized procurement strategies — saving costs and improving efficiency.
A distribution company with an automated ERP ordering system needed to optimize procurement decisions. While the system automatically generated orders based on inventory levels, it didn't account for supplier commercial policies, volume discounts, and promotional offers — resulting in missed savings opportunities.
The automated ordering system operated efficiently but lacked intelligence. It generated orders based solely on inventory levels and reorder points, without considering:
The company needed a solution that would analyze each automated order, apply relevant commercial policies, and suggest optimized alternatives — without disrupting the existing ERP workflow.
We proposed an intelligent AI Assistant that would act as a "smart colleague" — analyzing automated orders in real-time, comparing them against supplier policies, and proposing more cost-effective alternatives through an interactive chatbot interface.
Establish the AI workspace, define business rules for discount thresholds, 1+1 offers, pallet optimization, and supplier priorities. Create the foundational logic that would guide the Agent's decision-making process.
Test PDF parsing with 2-3 supplier policies. Develop standardized "clean PDF" templates to ensure accurate rule extraction. Convert policy documents into structured rules the Agent can apply.
Collaborate with vendor to establish read-only API or database access. Connect Agent to auto-orders table and supplier policy PDFs. Test real-time data flow and connectivity.
Build web-based chatbot widget that would display Agent recommendations with full justification. Implement accept/reject feedback mechanism. Create reporting dashboard for tracking savings and performance.
Conduct testing with actual auto-orders. Refine integration and business rules based on results. Deliver fully operational system with comprehensive documentation and training.
Monitors automated ordering system for new orders. Reads product codes, quantities, unit prices, and supplier data.
Applies relevant supplier commercial policies. Calculates volume discounts, promotional offers, and pallet optimizations.
Presents optimized alternative via chatbot. Shows cost savings and justification. User decides to accept or reject.
Automated Order: 10 boxes of Product X
Agent Recommendation: Order 13 boxes instead
Justification: Supplier offers -3% discount for 12+ boxes. By ordering 13, you save €45 and qualify for free shipping.
Result: €45 saved + free shipping
ERP System (Auto Orders) → AI Agent → Policy Analysis → Chatbot Interface → User Decision
Through optimized volume purchases and policy application
Every order analyzed against all applicable supplier policies
Instant recommendations as orders are generated
Let's discuss how AI can help your business make smarter purchasing decisions
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