• Demand forecasting.
• AI-supported recommendations on supply chain optimization (e.g., how much and when to order).
• Supply chain digital twin – a real-time supply chain model to test different supply chain action plans (e.g., safety stock planning, transportation optimization) and evaluate their impact before choosing the best one.

Value: improved and more cost-efficient fulfillment of customer demand, increased resource utilization, synchronization between different supply chain components.

• Supply chain control tower, offering real-time, AI-supported visibility into all supply chain operations, including operations of suppliers and external carriers.
• Configurable dashboards for a unified view of supply chain processes and related KPIs (fill rate, order cycle time, etc.).
• Collaborative issue resolution with suppliers via a shared space for issue discussions, issues status tracking and notifications, etc.

Value: end-to-end supply chain visibility, proactive risk management, improved collaboration with suppliers.

• Inventory levels and location tracking (with a barcode, RFID, or computer vision technology).
• Optimal safety stock calculation.
• Automated replenishment triggers.
• Lot and serial number tracking.
• Expiration dates and shelf life monitoring.

Value: decreased inventory carrying costs, increased order fulfillment speed and accuracy, optimized labor costs, minimized inventory loss and shortages.

• Quick template-based creation of purchase requisitions, RFxs, and purchase orders.
• Automated approval workflow for purchase requisitions and purchase orders.
• Analytics-based recommendations on supplier assignment to purchase orders.
• Creation and management of preferred supplier lists.
• Automated three-way matching (purchase orders, order receipts, and supplier invoices are cross-compared to reveal inconsistencies if any).
• Purchase order execution tracking (for several tiers if required).
• Collaboration tools to discuss orders with suppliers.

Value: standardized and streamlined purchasing, improved spend visibility.

• Analytics-based supplier pre-qualification (financial viability, technical capabilities, ethical business processes, etc.).
• Quick template-based creation of sourcing events (e-tenders, e-auctions).
• Collaboration with internal teams on supplier selection and nomination.
• Supplier performance analytics and ongoing compliance checks.
• Supplier portal for improved capacity planning (via collaboration with suppliers), etc.
• Automatic alerts for suppliers to update expiring data (accreditations, certifications).

Value: reduced supply chain compliance and regulatory risks, improved supplier engagement, optimized sourcing strategy.

• Calculating and monitoring all necessary supply chain KPIs: supply chain performance, orders, inventory, employee productivity, supplier risks, spend, and more.
• ML-based supply chain diagnostic analytics.
• Trend-based forecasting of supply chain metrics, transactions, and events.
• AI-powered prescriptions on optimal supply chain management decisions.
• Scheduled and ad hoc supply chain reports.

Value: accurate supply chain planning, minimized supply chain risks, optimized costs.

• Freight tracking.
• Planning and optimization of route schedules.
• Vehicle accident case management (accident notifications and reports, repair request issuing and routing, etc.).
• IoT connectivity to monitor product condition during transportation.

Value: improved vehicle utilization, decreased logistics operating costs, on-time delivery.

• Centralized processing of multichannel, multi-format sales orders.
• Analytics-based order routing to an optimal fulfillment location.
• Support of multiple order fulfillment methods and types (BOPIS, ship-from-store, same-day delivery, etc.).
• AI-guided order picking and packing.
• Automated return management.

Value: increased order fill rate, reduced order fulfillment costs, reduced shipping and expediting costs, increased customer satisfaction rate.