Aerospace Compliance Change Control

Supports aerospace-defense manufacturers and operators with automated assembly of traceable compliance evidence for CSI oversight and structured change-management workflows for DAA equipment modifications, including new sensors and software.

The Problem

“Aerospace Compliance Evidence and Change Management for CSI Oversight and DAA Modifications”

Organizations face these key challenges:

1

Evidence is scattered across disconnected repositories and formats

2

Manual traceability matrices are slow to build and easy to break

3

Compliance completeness checks depend on tribal knowledge

4

Change packages for DAA modifications lack consistent structure and rationale capture

Impact When Solved

Reduce manual evidence assembly time for CSI oversight packagesImprove completeness and traceability across plans, tests, reviews, and corrective actionsSurface missing, outdated, or conflicting compliance artifacts earlierStandardize DAA modification workflows for new sensors and software updates

The Shift

Before AI~85% Manual

Human Does

  • •Collect compliance artifacts from PLM, QMS, SharePoint, file shares, email, and test repositories
  • •Classify documents and build traceability matrices in spreadsheets for CSI oversight items
  • •Compare modified DAA configurations to prior approved baselines and draft impact assessments
  • •Route change packages through email reviews and compile approval packets

Automation

    With AI~75% Automated

    Human Does

    • •Review and approve proposed trace links, completeness findings, and evidence selections
    • •Decide change impact, safety rationale, and disposition for DAA sensor or software modifications
    • •Handle exceptions, conflicting evidence, and gaps requiring additional investigation

    AI Handles

    • •Ingest, classify, and extract metadata from compliance documents across repositories
    • •Link requirements, plans, tests, reviews, hazards, and corrective actions to oversight criteria and checklists
    • •Detect missing, stale, duplicate, or conflicting evidence and prioritize follow-up actions
    • •Compare proposed DAA changes against prior approved behavior and draft delta summaries and impacted artifacts

    Operating Intelligence

    How it works

    AI runs the first three steps autonomously.

    Humans own every decision.

    The system gets smarter each cycle.

    Confidence88%
    ArchetypeRecommend & Decide
    Shape6-step converge
    Human gates1
    Autonomy
    67%AI controls 4 of 6 steps

    Who is in control at each step

    Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.

    Loop shapeconverge

    Step 1

    Assemble Context

    Step 2

    Analyze

    Step 3

    Recommend

    Step 4

    Human Decision

    Step 5

    Execute

    Step 6

    Feedback

    AI lead

    Autonomous execution

    1AI
    2AI
    3AI
    5AI
    gate

    Human lead

    Approval, override, feedback

    4Human
    6↺ Loop
    AI-led step
    Human-controlled step
    Feedback loop
    TL;DR

    AI handles assembly, analysis, and execution. The human gate sits at the decision point. Every cycle refines future recommendations.

    The Loop

    6 steps

    1 operating angles mapped

    Operational Depth

    Real-World Use Cases

    DAA equipment change-management workflow for operators integrating new sensors or software

    When a drone operator adds a new safety sensor or updates avoidance software, this workflow helps show what changed and whether the drone is still safe to fly BVLOS.

    Structured compliance workflow rather than autonomous cognition; compares modified system capabilities against prior approved or documented behaviorprocess-mature but approval-mature only in context; the checklist supports repeatable documentation, while acceptance remains operation-specific.
    10.0

    Automated compliance evidence assembly for CSI oversight

    Use automation to gather all the paperwork and records that prove a supplier followed the rules for safety-critical aircraft parts.

    Document classification, extraction, linkage, and compliance completeness checkinghigh near-term practicality as document workflow automation; source provides explicit artifact types and governance checkpoints.
    10.0

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