AI Quality Inspection & Predictive Maintenance in Vietnam

To qualify for the preferential 10% CIT rate for up to 15 years, your AI investment must be documented as a high-tech project in qualifying areas. We help structure your AI implementation -- including documentation, milestone tracking, and technology classification -- to meet the criteria. Note that the new CIT Law (effective October 2025) includes a grandfather clause for existing beneficiaries.

Decree 182/2024 established the Investment Support Fund offering cash grants for qualifying high-tech investments including AI and R&D. Manufacturing firms investing in AI-powered production systems, quality inspection, or predictive maintenance may qualify. First applications were accepted until July 2025, with ongoing rounds expected.

Vietnam's AI Law, effective March 2026, introduces a risk-based classification system (high, medium, low risk). High-risk AI systems require mandatory pre-market conformity assessments and human oversight. We help you assess which classification applies to your use case and prepare the necessary governance documentation before enforcement begins.

Starting point: 500-1000 images per defect type (good parts plus defect examples). AI can work with less using transfer learning, but more data improves accuracy. We teach data collection strategies, image augmentation, and active learning to accelerate model training.

Yes, basic predictive maintenance can use existing data (run hours, cycle counts, historical failures). Adding low-cost vibration or temperature sensors dramatically improves accuracy. We teach phased sensor deployment strategies matching budget and ROI priorities.

AI models require calibration to balance sensitivity (catching all defects) and specificity (minimising false positives). We teach threshold tuning, human-in-the-loop review for edge cases, and continuous model improvement. Expect 4-8 weeks of refinement post-deployment.

Trust builds through accuracy and transparency. We teach explainable AI showing what data drives predictions (e.g., rising vibration, temperature anomaly). Start with low-risk equipment, prove ROI, then expand. Champion-challenger testing accelerates adoption.