Architecture & capabilities
Overview
The Inventory Replenisher is built on a set of integrated agentic skills coordinated by a Digital Worker agent. This article covers the core skills, agent modes and configuration options, the full replenishment workflow, integration points, and how the system determines when to process automatically versus when to route to a planner.
Agentic Skills
The Inventory Replenisher operates through five core skills, each handling a distinct part of the replenishment process.
Actionize Planning Outcomes
Translates planning recommendations, shortages, and demand signals into actionable replenishment steps rather than leaving them as static insights. This skill bridges the gap between what the planning system has identified as needed and what actually needs to happen in IFS Cloud, turning MRP signals, reorder point triggers, and project demand into executable replenishment actions.
Supplier Validation
Confirms that replenishment actions are tied to the correct supplier based on sourcing rules, contracts, and approved vendor lists. Before any purchase order is created, this skill verifies that the supplier is active and approved in the system, properly connected to the relevant company and site, and that expected delivery timelines are available and valid.
Conditional Selection
Evaluates business conditions such as MOQ, value thresholds, lead times, and approval rules to determine whether actions can be automated or require human review, applied per supplier, per site, or per any other configured dimension. This is the skill that enforces consistency: the same rules are applied to every line, every run, regardless of which planner would have otherwise handled it manually.
Purchase Order Creation
Generates purchase orders automatically when all conditions are met, ensuring accuracy in quantities, pricing, and delivery dates. This skill handles both the creation of new purchase orders and the decision of whether to add lines to an existing purchase order or create a new one, logic that can be customized through the Digital Worker's configuration.
Stock Re-Allocation
Optimizes inventory by reallocating available stock across sites or demands to prevent shortages while minimizing excess inventory. When stock exists elsewhere in the network that can address a shortage before triggering a new external procurement, this skill identifies and acts on that opportunity.
Agent Modes and Configuration
The Inventory Replenisher offers two agent configurations to match the complexity of different replenishment environments.
Basic Agent Mode uses standard language models for straightforward requisition processing with clear business rules. This mode is suitable for environments with well-defined supplier conditions and predictable replenishment patterns.
Reasoning Mode employs advanced reasoning models for complex scenarios requiring deeper analysis of business rules, supplier conditions, and freight optimization. This mode is appropriate when supplier-specific rules are numerous or interdependent, when freight grouping logic is complex, or when exception handling requires more nuanced evaluation.
In Reasoning Mode, administrators can configure:
Reasoning effort: Controls the computational effort applied to rule evaluation and supplier selection
Verbosity: Adjusts the detail level in responses and logging for transparency and debugging
Concurrent processing: Enables parallelization of supplier processing to improve performance when handling multiple suppliers simultaneously
Replenishment Workflow
The following table outlines the full replenishment workflow from demand signal monitoring through to exception handling.
Stage
What the System Does
Action / Output
Channel
Demand Signal Monitoring
Monitors MRP, order points, and project demand; monitors purchase requisition lines in planned state
Initiates replenishment workflow
IFS
Replenishment Decision
Applies business constraints including MOQ, lead time, and supplier availability
Decides whether to procure or fulfilll internally; routes to sourcing if needed
IFS
PR Creation & Enrichment
Checks requisition with correct supplier, quantity, and constraints
Auto-checks PRs; enriches with context for faster approvals
IFS
PR to PO Conversion
Evaluates PR readiness for conversion; aligns with ERP authorization rules; detects safe-to-auto-release scenarios
Auto-releases valid PRs; converts PR to PO; routes to Supplier Order Manager for execution
IFS
Exception Handling
Identifies MOQ conflicts, supplier constraints, and abnormal demand; detects ambiguity in decision-making
Triggers human-in-the-loop workflows; suggests alternatives such as reallocation, delay, or order splitting; resumes automated flow after decision
Teams / IFS
Tools and Integration Layer
The Inventory Replenisher uses a comprehensive set of tools to interact with IFS Cloud and connected systems:
Get Planned Requisition Lines: retrieves all requisition lines in planned status within the specified date range
Validate Supplier: confirms supplier status, company assignment, and approval conditions
Check Business Rules: applies customizable conditions for MOQ, pricing thresholds, and supplier-specific requirements
Auto-Release Requisition: changes the status of valid lines from planned to released
Create Purchase Order: generates complete PO records in IFS Cloud with all validated information
Log Results: stores detailed execution logs for audit and troubleshooting
Send Notifications: alerts users through Teams, Slack, or email for exceptions and approvals
Integration Points
ERP Platforms: Connects directly with IFS Cloud and other enterprise systems to read requisition lines, validate supplier data, and write purchase orders automatically.
Email Systems: Integrates with Microsoft Outlook and Gmail for supplier communications and exception notifications.
Collaboration Platforms: Uses Microsoft Teams and Slack for exception notifications, approval workflows, and real-time visibility into processing status.
Planning Systems: Integrates with material planning (MRP), demand forecasting modules, and automated planning systems to receive requisitions from multiple sources.
IoT Sensors: Receives demand signals from connected equipment and sensors to inform replenishment decisions.
Logistics/TMS: Connects with transportation management systems for delivery coordination and inbound visibility.
CRM Systems: Connects with Salesforce, HubSpot, and Qoncierge to maintain supplier relationship context and historical performance data.
Human-in-the-Loop Design
The Inventory Replenisher is designed so that routine replenishment processing happens automatically and human judgment is applied to lines and scenarios that genuinely require it.
The system proceeds independently when:
Suppliers are valid, active, and approved in the system
Requisition lines meet minimum order quantity requirements
Line totals fall within configured price thresholds
Orders align with freight load optimization rules
Human review is required when:
Suppliers are invalid or blocked in the system
Requisitions do not meet minimum order quantities
Line totals exceed configured price thresholds
Forecast deviations or unexpected demand patterns are detected
High-value orders require strategic judgment
When exceptions are detected, the system identifies the specific validation failures preventing automatic processing, sends a detailed notification via Teams or Slack with complete context, provides a clear reason for each invalid requisition line, and maintains a complete audit trail of all decisions and validations.
Testing and Validation
The platform includes an evaluation environment for testing and development. Teams can trigger processing runs manually with specific date ranges, monitor execution in real time as the agent processes each supplier, review validation results for each requisition line, and observe purchase order creation attempts.
Debug mode provides detailed visibility into inputs and outputs of each validation step. Execution summaries show total valid lines processed, invalid lines flagged, purchase orders created, and any failures, with complete audit trails available in detailed logs.
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