Concept Demo — CELSA Procurement AI is a fictitious proof of concept. All suppliers, prices, volumes, contracts and indicators are synthetic and for demonstration purposes only.

Active Sourcing Events

RFQ-2026-1042
Ferrous Scrap HMS 1/2
15,000 t requested 6 suppliers Barcelona Plant · Oct 2026
AI Analysis Completed

AI Opportunities

Generated from live scoring model

Procurement AI Assistant

Good morning. I have completed the analysis of RFQ-2026-1042.

I identified three recommended suppliers and a sourcing combination that balances cost, quality, logistics, risk and sustainability.

Estimated opportunity: €214,350.

Sourcing Workflow

Follow the full AI-assisted sourcing journey: from raw supplier documents to a defensible, explainable award recommendation.

Requested Volume
15,000 t
Delivery Location
Barcelona
Delivery Period
Oct 2026
Offers Received
6
Currency
EUR

Sourcing Pipeline

Invited Suppliers

SupplierRegionOffer Status

AI Summary

All 6 supplier offers for RFQ-2026-1042 have been ingested, normalized and scored by the AI engine. The model estimates a total sourcing opportunity of €214,350 versus a naive lowest-price baseline, while reducing average supply risk and improving traceability and sustainability metrics.

Incoming Supplier Offers (RFQ-2026-1042)

Supplier Comparison — RFQ-2026-1042

AI Score model: default weighting (editable in AI Supplier Score)
SupplierBase Price €/tLogistics €/tTotal Landed Cost €/t Available VolumeQualityOTIFTraceabilityCO₂RiskAI Score

Total Landed Cost = Base Price + Transport + quality/OTIF/traceability adjustments + supply-risk penalty. Global Scrap Trading shows the lowest base price but ranks low overall once landed cost and risk are considered.

Base Price vs. Total Landed Cost

Scoring Weights

Total weight: 100% — weights are automatically normalized before scoring.

Live Ranking

Supplier Profile Comparison

Recommended Allocation — 15,000 t

AI Explanation

Although Global Scrap Trading offers the lowest base price, it is not included in the recommended allocation because its total landed cost, delivery reliability, traceability and supply risk materially reduce its economic advantage.

EcoFer Metals receives the highest overall score due to its combination of competitive landed cost, historical quality, delivery reliability and complete traceability.

Recimet Catalunya is strategically attractive despite a slightly higher purchase price because of its proximity to the plant, very high delivery reliability and reduced logistics exposure.

The recommended multi-supplier allocation also reduces dependency on a single supplier.

Key Decision Drivers
  • €72K estimated logistics saving
  • Higher expected material quality
  • 23% lower supply disruption exposure
  • 27% lower logistics CO₂
  • Increased supplier diversification

All figures shown are simulated for demonstration purposes.

Lowest Price Strategy vs. AI Optimized Strategy

MetricLowest PriceAI Optimized

Cost Components (€/t)

Price Assessment

Supplier Quoted Price
AI Estimated Total Cost
AI Expected Range
Negotiation Opportunity

    100% Recycled Ferrous Input

    Estimated CO₂ avoided vs. virgin steel (synthetic)

    Logistics CO₂ by Supplier (kg CO₂e/t)

    Traceability Score by Supplier

    Certifications on File

    SupplierCertificationsTraceabilityCO₂ Logistics