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Capability 04

AI, Automation & Data

Automate defined business or operational workflows, develop control or simulation logic, and apply data or AI where its value can be tested.

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Useful when

Situations this scope can address

  • A repetitive business or data workflow needs automation and clear exception handling.
  • A process, room, facility, or item of equipment needs rule-based monitoring or control.
  • A training simulator needs state logic, scenarios, faults, operator controls, or event logging.
  • An AI-assisted feature needs a bounded prototype and evaluation method.
  • Operational data needs to be collected, transformed, reported, or used within an accountable workflow.

Possible outputs

Milestone deliverables that may be included

  • Problem, workflow, control, and data requirements
  • Process map, state model, rules, and acceptance measures
  • Automation, control, or simulator prototype
  • Data pipeline, dashboard, reporting, or integration components
  • AI or model integration and evaluation when justified
  • Monitoring, human review, fallback behaviour, testing evidence, and handover plan

Project boundary

Responsibilities, dependencies, and exclusions are agreed first.

Operational authority, equipment interfaces, electrical and physical safety responsibilities, data rights, privacy, data quality, human review, failure modes, model or service providers, cost, retention, accuracy expectations, and ongoing accountability are agreed in writing. Accuracy, savings, autonomy, compliance, or safety performance are not claimed without relevant evidence.

Next step

Define the next useful technical milestone.

Share the current state, users, interfaces, constraints, existing software or equipment, expected outcome, and what the next milestone must prove or deliver.

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