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Industries/Logistics
Logistics  ·  AI Governance Policies

Operational data at speed and scale. Governed from the first API call.

Route optimization, demand forecasting, and fleet AI agents touch sensitive commercial contracts, shipper data, and real-time location feeds. AutoPIL enforces access policy across every data source — audit-ready from day one, without slowing your agents down.

AI Agent Policies — Logistics

9 policies across supply chain, fleet operations, and customs compliance — addressing the cross-border data sovereignty and trade compliance requirements of global logistics operators.

supply_chain.yaml3 roles
fleet_operations.yaml3 roles
customs_compliance.yaml3 roles
All 9 agent roles
demand_forecast_agentprocurement_agentinventory_reconciliation_agentroute_optimization_agentdriver_compliance_agentmaintenance_scheduling_agenttrade_compliance_agentsanctions_screening_agentimport_export_agent
policies/logistics/supply_chain.yaml
policies:
  # Demand forecast agent — sales and inventory data; blocked from carrier contracts and driver records
  - name: demand_forecast_agent_policy
    agent_role: demand_forecast_agent
    allowed_sources:
      - sales_history
      - inventory_levels
      - market_signals
      - supplier_lead_times
    denied_sources:
      - carrier_contracts
      - driver_records
      - financial_ledgers
    allowed_tasks:
      - demand_forecasting
      - replenishment_planning
      - supplier_recommendation
    denied_tasks:
      - purchase_order_creation
      - carrier_booking
      - sanctions_screening
    max_sensitivity: medium
Applicable Regulations — Logistics
Where AI governance breaks down in Logistics
Commercial contract exposure
Carrier rates and shipper SLAs are competitively sensitive. AI agents that access them without scope limits create both legal and business risk that AutoPIL prevents at the retrieval layer.
Multi-partner data isolation
Logistics platforms aggregate data from dozens of partners. AutoPIL enforces isolation between them so one partner's AI can't access another's data — even accidentally.
Cross-border data sovereignty
International shipment data crosses jurisdictions with different privacy requirements. AutoPIL enforces sensitivity classifications at the data layer before cross-border transfer.
How to use

One path.
Your industry loaded.

Point policy_path at your industry directory. AutoPIL loads every YAML file recursively — roles, sensitivity rules, and process groups wired up automatically from the directory structure. No additional config needed.

Policies are hot-reloaded at runtime. Extend or override any pre-built policy via the REST API without redeploying your agents or restarting services.

setup.py 
from autopil import ContextGuard

# Point at your industry — only those policies load
guard = ContextGuard(
    policy_path="policies/logistics/",
    audit_db="autopil.db",
)

# policies/logistics/ — loads recursively
# Switch verticals by changing the path — nothing else changes.

Start with Logistics.
Extend from there.

Pre-built policies for logistics are included in every AutoPIL trial. Extend or override any rule via the REST API without redeploying.

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