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Zero-Defect Quality Assurance:
Domain-Driven Intelligence with
Human-in-the-Loop Governance
in Aerospace
A Joint Research by

60-70%
of aerospace non-conformances originate in the supply chain, at tier 2 and tier 3
98%
data quality scores achieved before data enters the EIP intelligence layer
7
purpose-built layers in the Engineering Intelligence Platform
36 months
three-phase target operating model from foundation to zero-defect assurance
Reactive Defect Management Has Reached its Limit
PLM, ERP, QMS and MES systems were never designed to talk to one another. The result is a quality discipline that detects problems after the fact. Agentic AI, domain-trained SLMs and a unified data layer change the economics.
Current State
Reactive, siloed, manual, after-the-fact
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Defects detected once they have already occurred
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Root cause analysis bottlenecked by disconnected systems
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Supplier quality managed periodically and backward-looking
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Cost of poor quality erodes margin and engineering capacity
Target State
Predictive, unified, autonomous, first-time-right
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Non-conformances triaged and dispositioned autonomously
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Root cause surfaced from a unified engineering knowledge graph
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Supplier risk stratified and predicted in real time
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Human-in-the-loop governance keeps decisions audit-ready
What this Report Unpacks?
Why reactive quality no longer works in aerospace
How data silos across PLM, ERP & QMS stall AI
Why supplier quality is the biggest hidden risk
Where agentic AI transforms NC, MRB, CAPA & RCA
How domain-trained SLMs make AI quality-ready
Why human-in-the-loop governance is non-negotiable
Why Choose Cyient?
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Aerospace quality DNA — 30+ years of domain depth
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Workflow-trained AI — validated on real NC, MRB, concession, PFMEA, and CAPA processes
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Practitioner-built models — shaped by experts who have run quality workflows at scale
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Trust by design — governed, auditable, and human-in-the-loop for safety-critical operations
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Outcome-backed engagement — aligned to COPQ reduction and first-pass yield gains