Overview
- Resilience, Scenario Planning & Governance
- Demand Planning & Forecasting
- Sales, Order & Fulfillment
- Inventory Optimization
- Production & Capacity Planning
- Supply Planning & Procurement
- Logistics & Transport
- Sustainability & Compliance
- Systemic Intelligence & Control
- Platform, Integration & Security
- Experience & Exception Handling
- Collaboration & Multi-Party Coordination
Resilience, Scenario Planning & Governance
Model and prepare for disruptions, edge cases, and systemic risks—ensuring the supply chain is ready to absorb shocks, recover quickly, and justify decisions with auditable logic.
Model and simulate disruptions across supply, transport, and production: Agents simulate disruptions (e.g., port closures, factory outages) and recommend mitigation across the orchestration graph.
Provide pre-configured “what-if” scenarios for risk testing: Scenario templates (e.g., demand spike, supplier drop) are included and fully customizable per use case.
Score plans for resilience (e.g., time to recover, plan slack, routing flexibility): Plans are scored by resilience KPIs and used by agents to favor higher-fitness options when tradeoffs exist.
Detect and surface risks from live execution signals: Agents monitor for emerging risks (e.g., late shipments, demand volatility) and flag potential cascading impacts before failure occurs.
Automatically trigger alternative plans when thresholds are breached: Agents switch plans or reallocate flows once defined risk thresholds are exceeded. New paths are simulated before execution.
Support human override and escalation for risk events: Agent recommendations can be overridden. Human users can preview, modify, or approve alternate flows via UI or API.
Include ESG and regulatory risks in scenario planning: Scenarios include compliance risk, carbon breaches, and sustainability failures. Mitigations are evaluated in real time.
Simulate time-based risks (e.g., quarter-end backlog, phased disruptions): i5 uses Temporal Logic to model nested risks across short, mid, and long-term windows. Outcomes are ranked by horizon.
Compare multiple scenarios with visual tradeoff impact: Agents present ranked outcomes by cost, time, margin, carbon, and resilience. Human decision-makers can review all options.
Maintain an audit trail of all scenario decisions and overrides: All scenarios, assumptions, outcomes, and overrides are logged with time stamps and decision traces.
Train agents or teams using synthetic risk scenarios: i5-SDG generates synthetic scenarios for training, onboarding, and stress testing. Full orchestration logic is included in sandbox.
Score customers, suppliers, and nodes by resilience risk: Entity fitness includes resilience scoring—used to flag weak points in the network and inform sourcing and routing.
Demand Planning & Forecasting
Accurately sense, shape, and align demand signals across internal and external sources, time horizons, and granularity—while continuously adjusting forecasts based on real-world volatility and feedback.
Generate forecasts using historical sales, seasonality, and market trends: i5 generates forecasts via agent logic using synthetic, historical, or integrated data inputs. Forecast agents apply curve shaping and time-relative reasoning across products and regions.
Support forecast granularity by region, product, channel, and customer segment. Forecasts are structured by any dimension defined in the orchestration input schema (e.g., site, customer, SKU). All outputs are linked to these entities within the i5 Graph.
Allow cross-functional forecast input and override by stakeholders. Forecasts can be refined by multiple agent roles (Sales, Inventory, Production). Human users can preview, override, or simulate changes before committing.
Provide multiple forecast models (statistical, ML-based, heuristic). i5 uses curve-shaped synthetic generation and can incorporate ML signals via custom inputs. Native forecast models are not off-the-shelf statistical engines.
Adjust forecasts based on current execution signals (e.g., order, inventory, transport). Agents continuously simulate forward impact and adjust forecasts as actuals evolve. Real-time updates are scored and propagated through the orchestration graph.
Provide automated confidence scoring for forecast lines. Forecast confidence scores are generated natively by Forecast Agents using historical variance, agent alignment, and simulation divergence.
Detect and resolve conflicting forecast inputs (e.g., Sales vs. Ops). Conflicts are flagged, and resolution is proposed by comparing simulation outputs. Confidence-weighted negotiation logic ensures agent alignment.
Integrate demand signals from external sources (e.g., weather, market events). External signals can be added via orchestration inputs or API calls; not mined automatically today. Agents respond to structured signals, not raw data.
Simulate demand volatility scenarios and evaluate plan fitness. i5 supports structured scenario simulation with curve shaping and volatility modeling. Agents evaluate impacts and recommend mitigation.
Generate multi-horizon forecasts (short, mid, long term). Forecasts are modeled across nested timeframes using i5’s Temporal Logic engine. Time-based planning layers are resolved independently then reconciled.
Optimize forecasts to align with capacity, inventory, and supply constraints. Forecast Agents reconcile with inventory, BOM, and supply-side feasibility. Agents negotiate changes to avoid unfulfillable demand commitments.
Trigger planning or procurement events based on forecast changes. Smart Agreements and downstream agent logic are activated based on forecast deltas exceeding defined thresholds.
Sales, Order & Fulfillment
Integrate order logic with fulfillment reality—ensuring promises, SLAs, and profitability are respected from quote to delivery, even under changing conditions or disruptions.
Capture and validate sales orders from multiple channels (EDI, portal, manual, API). Orders can be posted via API, synthetic inputs, or manual upload. Data structures are validated against orchestration schema and Smart Agreements.
Provide Available-to-Promise (ATP) logic considering inventory, production, and transport. ATP is computed dynamically by Sales Agents using current supply, site constraints, and delivery timelines. Results reflect what can actually be fulfilled.
Confirm, allocate, and track orders through full lifecycle. Confirmed orders are recorded in the i5 Graph and tracked through production, transport, and inventory stages. Exception logic flags issues.
Trigger fulfillment actions automatically upon order confirmation. Order confirmation activates downstream agents—Production, Procurement, Transport. All flows respect current orchestration state.
Allow quote generation based on available inventory and constraints. Sales Agent generates quotes based on current availability and feasibility. Quote logic is aligned with forecast and Smart Agreements.
Simulate impact of major or urgent orders on current plans. i5 simulates any order—real or proposed—and displays impact across demand, supply, capacity, and ESG metrics.
Prioritize orders based on margin, urgency, or agreement tier. Orders are scored by agent logic using configurable business rules and Smart Agreement clauses. Higher-priority orders are protected in orchestration.
Adjust order flow dynamically based on execution signals. Delays or disruptions to any part of the fulfillment flow trigger reallocation, timing shifts, or customer notifications via agent logic.
Link customer orders to Smart Agreements with pricing and terms. Orders inherit or trigger Smart Agreements, which embed price, delivery windows, ESG terms, and penalties. Planning logic respects these terms.
Monitor and alert on order risk (e.g., lateness, margin erosion, carbon breach). Risk scores are computed continuously. Orders at risk of breaching SLA, margin, or ESG limits are escalated and re-optimized.
Simulate quote-to-fulfill scenarios in synthetic environments. i5-SDG enables complete quote-to-fulfill scenario testing without live data. Used for new SKUs, partners, or sales training.
Provide visibility into order status across fulfillment stages. Order status is tracked natively in the i5 Graph with visibility across agents, scenarios, and UI layers. Timeline, exceptions, and next steps are included.
Inventory Optimization
Dynamically manage inventory levels, placement, and policies across the entire network—maximizing service levels with minimal working capital, while adapting to risk, delay, or demand shocks.
Automate replenishment using safety stock, reorder points, and lead times. Inventory Agents manage replenishment using forecast demand, lead time, and safety stock logic. Updates trigger procurement or production actions.
Support multi-echelon inventory planning across DCs, plants, and transit. Inventory is modeled across nodes, with stock positioning evaluated against demand location, timing, and value.
Separate logic for cycle stock vs. safety stock control. Agents differentiate buffer vs operational stock via orchestration parameters. Buffer logic is scenario-aware.
Provide visibility into inventory levels by site, product, and status. Full inventory visibility is native in the i5 Graph. Agents and users can query stock by location, ownership, and availability window.
Simulate stockout and overstock risk under forecast volatility. Inventory scenarios are simulated forward under changing forecasts, BOM shifts, or transport disruptions. Risk alerts are surfaced.
Proactively rebalance inventory across network to avoid exceptions. Inventory Agents initiate reallocation across nodes based on timing, value, and disruption risk. Triggered dynamically.
Align inventory targets to downstream Smart Agreements and demand plans. Inventory positions are tied to Smart Agreement terms and expected demand. Agents maintain readiness within delivery windows.
Optimize inventory for margin, service level, and carbon impact. Multi-objective optimization includes margin, fulfillment risk, and ESG metrics. Agent logic prioritizes tradeoffs per business rules.
Adjust stock strategy dynamically based on execution signals. Agents detect transport delays, production misses, or demand surges and adjust safety stock, reordering, or allocation in real time.
Visualize tradeoffs between inventory decisions and downstream impacts. Inventory decisions are simulated through the orchestration graph—showing effects on transport, margin, and SLAs.
Score inventory resilience (e.g., reallocation readiness, shock absorption). Inventory nodes are scored on agility, buffering capacity, and cross-node flexibility. Used by agents during rebalancing.
Test inventory strategies in synthetic environments before deployment. i5-SDG generates full synthetic inventory networks for testing reorder logic, positioning rules, and risk posture before go-live.
Production & Capacity Planning
Orchestrate production decisions with full visibility into constraints, lead times, and capacity buffers—supporting alternate routings, BOM substitutions, and flexible manufacturing responses.
Generate feasible production schedules based on demand, BOM, and capacity. Production Planner Agents align forecasts, BOMs, and site capacity to build executable plans. Constraints are validated pre-commitment.
Support multi-level BOM explosion and materials alignment. BOM structures are fully modeled within i5 Graph. Cascade logic supports parent-child dependencies with demand roll-down.
Coordinate production across multiple sites or contract manufacturers. Agents simulate cross-site allocation, optimize based on capacity, and consider Smart Agreements with external manufacturers.
Rebalance production based on disruptions, delays, or new demand. Agents monitor execution risk and dynamically reassign production to alternate sites or timelines.
Include lead times, calendars, and shift schedules in capacity plans. Calendars, shift constraints, and time windows are modeled in the orchestration layer. Production logic respects them natively.
Trigger procurement and inventory actions from production plans. BOM-aware production plans generate material demands, which trigger Procurement and Inventory Agent workflows.
Monitor production order lifecycle from plan to completion. All production orders are tracked in the i5 Graph with real-time status updates. Agent exceptions flag delays or scrap risks.
Simulate production capacity under “what-if” scenarios. i5 supports full-scenario simulations (e.g., surge, shutdown). Agents model production feasibility, lead time shifts, and cost tradeoffs.
Prioritize production based on urgency, margin, or agreement terms. Agents reason using time-based priority logic (TNR) and Smart Agreement terms to prioritize what to make, when, and where.
Integrate energy usage and emissions data into production planning. Energy and carbon impact per product/site are modeled and included in production optimization.
Adjust production dynamically based on execution signals. Agents update production plans in real time based on inventory, transport, and demand shifts. Simulation ensures no blind spots.
Simulate new product or line launches in sandbox before live execution. New SKUs or sites are introduced in synthetic mode using i5-SDG. Scenarios are validated before API posting.
Supply Planning & Procurement
Convert demand into executable supply and sourcing plans that are contract-aware, multi-tier, and adaptive—balancing cost, service, risk, and ESG goals.
Calculate raw material needs based on BOM, forecast, and lead times. i5 interprets forecast and BOM structures to calculate precise material needs by product, site, and period. Constraints and timing are respected across the orchestration window.
Maintain master data for suppliers, locations, lead times, and profiles. Supplier entities and their attributes are managed within the i5 Graph and updated via input templates or APIs. Agents use this data when planning or re-allocating.
Create and manage purchase orders across the full lifecycle. Procurement Agents generate and update POs in response to scenario logic. PO lifecycle is tracked with change history and agent-based adjustments.
Enforce sourcing rules and supplier constraints (e.g., capacity, region, compliance). Smart Agreements encode constraints like region, MOQ, capacity, or carbon rules. Procurement Agents enforce and optimize sourcing accordingly.
Dynamically adjust sourcing based on supplier performance or disruption. System reassigns sourcing in response to delays, disruptions, or new data. Agents trigger reallocation with risk scoring.
Optimize sourcing based on cost, lead time, and supplier ranking. i5 evaluates sourcing options across multi-criteria scores (cost, time, carbon, reliability). The best-fit is selected and logged with rationale.
Integrate forecast changes into procurement signals. Forecast Agents communicate deltas directly to Procurement Agents. Updated PO proposals and sourcing plans are generated in response.
Generate and manage Smart Agreements with suppliers. Agreements are modeled as structured, agent-readable contracts including terms, dates, quantities, and carbon limits. Used in procurement logic.
Model and simulate supplier disruption scenarios. i5 supports scenario runs such as port shutdown, capacity drop, or ESG non-compliance. Agents simulate and propose mitigation actions.
Evaluate supplier performance and fitness over time. Supplier fitness is tracked and scored using historical and simulation-based data. Used by agents for sourcing decisions and agreement ranking.
Trigger transport and production updates from procurement changes. Procurement Agent actions feed directly into Transport and Production planning agents. All changes are reflected in orchestration flows.
Incorporate ESG metrics (e.g., carbon, ethical sourcing) into sourcing decisions. ESG attributes are embedded in supplier profiles and evaluated in real-time. Sourcing outcomes are scored for ESG compliance.
Logistics & Transport
Plan and execute transport across modes, lanes, and carriers with live visibility, carbon awareness, and intelligent fallback strategies—coordinating tightly with upstream and downstream nodes.
Select optimal carrier based on cost, lead time, and service level. Transport Planner Agents evaluate all carrier options based on configurable cost, service, and ESG scoring logic. Selections are auto-logged with rationale.
Optimize routing across modes and constraints (e.g., capacity, timing). The i5 Move Graph dynamically models all routing options and constraints. Agents plan full or partial multimodal moves based on urgency and feasibility.
Plan loads and consolidate shipments efficiently. i5 Agents auto-consolidate loads by region, mode, and schedule—minimizing underutilization while preserving commitments.
Provide real-time tracking and visibility of in-transit shipments. Shipment status and ETA logic are natively modeled. Real-time signal ingestion from TMS/IoT partners via API is supported but not natively sourced.
Trigger re-routing based on disruption, delay, or urgency changes. Agents detect transport risk and automatically simulate alternatives. Feasible re-routes are executed based on system-wide context.
Model and manage transport capacity by carrier, lane, and timeframe. Published transport capacity is modeled as a first-class object. Agents allocate moves based on availability and reservation windows.
Include carbon impact in routing and carrier selection. Emissions profiles are modeled per carrier, lane, and load type. Agents include carbon in tradeoff logic for all move decisions.
Simulate transport disruptions and recovery scenarios. Transport scenarios (e.g., port shutdown, lane closure) are modeled with agent reallocation, delay scoring, and risk mitigation planning.
Automatically update downstream plans based on shipment status. Shipment delays, holds, or exceptions automatically trigger reallocation, reordering, or escalation across agents. No batch re-planning required.
Manage Smart Agreements with logistics partners. Agreements define pricing, capacity, time windows, and emission thresholds. Agents reference these in planning and compliance logic.
Track and score carrier performance across cost, timing, and ESG. Carrier fitness is scored continuously based on actual execution and synthetic scenario performance. Used for partner selection and escalation.
Include ESG and compliance metrics in all logistics planning. ESG compliance flags (e.g., CBAM, mode restrictions) are built into transport rules. Agents filter out non-compliant options proactively.
Sustainability & Compliance
Embed carbon, ethics, and compliance into every plan, policy, and decision—making ESG performance measurable, enforceable, and aligned with enterprise commitments.
Track carbon emissions across shipments, products, and flows. Emissions are calculated per move, product, and batch based on transport mode, routing, and production inputs. Data is visible and used in orchestration.
Include carbon impact in planning decisions. Carbon is treated as a cost or constraint across sourcing, production, and logistics. Agents evaluate carbon tradeoffs along with cost and urgency.
Support ESG compliance with global and regional regulations. Smart Agreements and orchestration logic can enforce CBAM, REACH, CSRD, and other compliance rules by geography or partner.
Maintain digital records for ESG audits (e.g., carbon footprint, supplier declarations). All ESG data and decisions are recorded in the i5 Graph with full auditability and reporting export options.
Integrate supplier compliance data (e.g., certificates, policies). Supplier ESG attributes can be ingested and referenced in Smart Agreements and sourcing logic. Non-compliant partners are deprioritized or excluded.
Score decisions and flows by ESG impact. Every option (route, supplier, product) is scored in simulation for carbon, ethics, or waste—then ranked against cost and time.
Include carbon cost in margin calculation. True margin includes embedded carbon cost or shadow price, enabling smarter prioritization for low-emissions fulfillment.
Auto-flag or block non-compliant options during planning. Non-compliant plans (e.g., carbon breach, restricted mode) are filtered before presentation to agents or users.
Simulate ESG impacts of strategic or operational decisions. Users or agents can simulate the ESG outcome of new SKUs, suppliers, production shifts, or routing changes before committing.
Provide ESG metrics per order, shipment, and agreement. ESG data is available contextually at all orchestration levels—order, flow, partner, agreement—and used for compliance and reporting.
Generate audit-ready ESG disclosures and data exports. All ESG events and decisions are logged with metadata and can be exported for compliance reporting or third-party audit.
Support dynamic ESG contract terms (e.g., carbon limits, green incentives). Smart Agreements can include ESG clauses that impact planning behavior—e.g., route caps, supplier filters, emissions penalties.
Systemic Intelligence & Control
Treat the enterprise as a living system—using feedback loops, graph logic, and simulation to make intelligent, adaptive decisions at every node, flow, and time horizon.
Full-system scenario simulation Enables simulation of entire supply chain graph under varied disruption or strategy conditions.
Graph-centric orchestration logic Treats supply, demand, and move nodes as a connected graph with dynamic dependencies and flows.
Feedback loop and control modeling Embeds closed-loop control logic to enable continuous adjustment based on execution signals.
Systemic deviation and root cause detection Detects and traces system-wide patterns, not just local failures or noise.
Model calibration and learning Continuously tunes model parameters (lead time, volatility, yield) based on observed data.
Multi-agent negotiation and conflict resolution Supports negotiation between intelligent agents with different goals (e.g., cost vs. service).
Latency and delay detection Measures time lags in signal → plan → act loop and identifies where speed matters most.
System entropy and complexity scoring Quantifies systemic unpredictability, over-planning, and noise.
Plan stability monitoring Scores and suppresses unnecessary replanning to improve plan consistency.
Systemic carbon and ESG logic Integrates carbon, compliance, and sustainability directly into orchestration decision loops.
Margin-aware orchestration logic Tracks and optimizes margin across all flows, adjusting for delay or disruption.
Systemic intelligence dashboarding Provides live visibility into orchestration health, resilience, control loop function, and deviations.
Platform, Integration & Security
Ensure orchestration logic is extensible, secure, and integrable across legacy systems, APIs, and governance structures—without slowing down innovation.
Modular platform architecture Supports deployment of independent, composable orchestration services.
Open API framework Enables full integration with external data, planning tools, and execution systems.
Event-driven integration hooks Allows orchestration logic to respond in real time to signals from external systems.
Data model extensibility Users can extend or customize key entity types (SKU, node, flow) without vendor code changes.
Master data sync framework Keeps core planning objects aligned with ERP, MDM, TMS, and external sources.
Time-series and stateful data support Handles both snapshot and streaming data for use in planning, simulation, and agents.
Orchestration sandbox environments Supports safe, isolated testing of new agents, plans, or simulations.
Enterprise-grade security and auditability Offers robust identity, access, audit, and encryption features across platform.
Role-based access control (RBAC) Assigns precise user and agent permissions based on function and sensitivity.
API-first orchestration deployment All planning, simulation, and decisioning functions exposed via secure APIs.
Cross-system data lineage and traceability Tracks where each plan input came from, and how it was transformed.
Platform performance and scalability controls Allows tuning and scaling of orchestration workloads across enterprise nodes or clouds.
Experience & Exception Handling
Give users and agents shared access to alerts, dashboards, and guided interventions—enabling fast, intelligent response when plans go off course.
Unified orchestration alerting Aggregates all system, execution, agent, and plan-level alerts in a user-tailored console.
Exception classification logic Tags and categorizes exceptions by source, impact, and recommended ownership (human vs. agent).
Guided intervention workflows Offers human users recommended actions, escalation paths, or override options per exception.
Plan deviation explanation engine Explains why a plan changed, what triggered it, and how it differs from the prior baseline.
Agent-human collaboration loop Allows agents to request human input, justification, or override before finalizing orchestration.
Context-aware notification system Prioritizes alerts by user role, urgency, and historical behavior patterns.
Dashboard-to-action continuity Users can act directly from dashboards (e.g. cancel, reroute, approve) without switching systems.
Event replay & trace mode Users and agents can “replay” the decision history for any plan or event.
Role-based visibility & filtering Limits what each role sees (alerts, decisions, risks) based on policy or Smart Agreement.
Exception risk scoring Scores each exception by margin risk, SLA impact, and systemic propagation potential.
Confidence-based override guardrails Prevents override actions when signal quality is too low or contradiction is detected.
Multimodal interface support Supports dashboard, mobile, email, and API-based alerting and approvals.
Collaboration & Multi-Party Coordination
Enable secure, traceable, and intelligent orchestration across external partners—sharing logic, plans, and events while maintaining governance, compliance, and resilience.
Provide secure access for suppliers, carriers, or partners to view and update forecasts, orders, and shipments. Multi-party access is supported through role-specific agent portals or API connections. Visibility is controlled by orchestration context and agreement permissions.
Support structured data exchange via EDI, API, and manual upload. i5 ingests structured data via configurable interfaces. Inputs can be mapped to orchestration schema for full agent logic execution.
Notify stakeholders of exceptions, approvals, or plan changes in real time. Agents trigger alerts for specific events—delays, demand shifts, re-routes—based on priority and role. Notifications are routed per agreement.
Track all interactions and changes with audit history. All orchestration steps are versioned and auditable, with full traceability across agents, inputs, and outputs.
Allow multiple parties to contribute to or adjust orchestration logic collaboratively. i5 supports shared scenario editing, agreement negotiation, and joint simulation across users or agents from different orgs.
Simulate multi-party disruptions or recovery scenarios. Scenarios can include cross-entity variables (e.g., dual supplier failure, shared transport node issue). Recovery paths are modeled with agent alignment.
Evaluate and score partner performance on cost, reliability, and ESG. Partner fitness scores are continuously updated based on real and simulated behaviors. These scores influence agent decisions on routing and sourcing.
Model Smart Agreements between parties and enforce terms operationally. Smart Agreements include terms like volume, lead time, carbon, and penalties. Agents monitor compliance and adjust planning accordingly.
Enable real-time negotiations between internal and external agents. Agents negotiate supply, transport, and timing tradeoffs across roles and orgs—based on alignment logic and scenario feasibility.
Provide partner-specific views of the orchestration plan. Views are filtered by role, agreement, and authorization—showing only relevant orchestration paths, not system-wide data.
Share compliance or ESG performance data across entities. ESG metrics (e.g., carbon by shipment or SKU) can be exposed to partners as part of agreements or visibility layers.
Allow shared sandbox environments for training or partner onboarding. i5-SDG supports synthetic onboarding with partner-specific scenarios. New agents or flows can be validated before live integration.