Comparison

AEROCERT vs Foundation Models or AI Wrappers

Feature / Criteria	Generic Foundation AI Model	Aerocert
Confidentiality	Risk of Data Compromise	Built for sensitive information based on private RAG
Domain Assurance	Not trained for the aviation sector	Trained on aviation standards using real project data
AI-Human Interface	Generic UI/UX	Tailored with aviation experts to prevent deskilling & enhance correct use
PLM Integration	Complex & difficult (requires dedicated effort & poses privacy risks)	Seamless integration with existing workflows
Continuous Learning	Static; lacks domain knowledge updates	Dynamic RAG continuous learning on company data updates
Contextual Memory	Limited / Not effective long-term memory	Maintains dynamic operator profiles (preferences, past outcomes, facts)
Configuration Control	Unannounced version changes & updates	Predictable, controlled, and agreed-upon upgrades
Risk Profile	High AI risks: data breaches, operator deskilling, biases & errors	Mitigated risks by design: Safe AI adoption for proprietary workflows