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Industries/Manufacturing
Manufacturing  ·  AI Governance Policies

Quality, safety, and IP data are your competitive core. Govern who sees them.

Process control systems, supplier quality agents, and safety compliance AI touch data you cannot afford to expose — to competitors, regulators, or each other. AutoPIL enforces data isolation between processes and produces the audit chain your certifications require.

AI Agent Policies — Manufacturing

10 policies across quality control, supply chain operations, and safety compliance — separating defect detection and SPC data from procurement financials, and isolating OSHA incident records from production and customer data.

quality_control.yaml4 roles
supply_chain_ops.yaml3 roles
safety_compliance.yaml3 roles
All 10 agent roles
defect_detection_agentspc_agentsupplier_quality_agentcalibration_agentprocurement_agentproduction_planning_agentinventory_reconciliation_agentincident_reporting_agentmfg_safety_inspection_agentenvironmental_compliance_agent
policies/manufacturing/quality_control.yaml
policies:
  # Defect detection agent — sensor and vision data; blocked from supplier contracts and financials
  - name: defect_detection_agent_policy
    agent_role: defect_detection_agent
    allowed_sources:
      - sensor_data
      - vision_system_outputs
      - spc_charts
      - product_specs
    denied_sources:
      - supplier_contracts
      - financial_ledgers
      - customer_data
    allowed_tasks:
      - defect_detection
      - quality_flagging
      - root_cause_initiation
    denied_tasks:
      - purchase_order_creation
      - pricing_decision
    max_sensitivity: medium
Applicable Regulations — Manufacturing
Where AI governance breaks down in Manufacturing
IP exposure across agent pipelines
Proprietary process parameters and formulations are competitively critical. AI agents need boundaries enforced at the data layer, not just access credentials, to prevent inadvertent disclosure.
Safety system data isolation
OSHA incident records and safety inspection data must be isolated from supplier-facing AI. AutoPIL enforces that boundary automatically, at the retrieval layer.
ISO 9001 audit readiness
Quality management certification requires demonstrable controls over data access in automated systems. AutoPIL's audit chain satisfies that requirement with no additional instrumentation.
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/manufacturing/",
    audit_db="autopil.db",
)

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

Start with Manufacturing.
Extend from there.

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