A novel multi-agent architecture has been developed to support human-AI decision-making in high-precision manufacturing, particularly for CNC machining of complex aerospace components1. This framework integrates physics-based models with AI-driven agents to provide risk-aware and traceable decision support. Unlike off-the-shelf large language models, this approach enables the reliable execution of multi-step numerical workflows and generates auditable provenance for high-stakes decisions. The architecture is designed to incorporate process knowledge, simulation, and inspection data to inform bounded compensations and optimize manufacturing outcomes. By providing a transparent and explainable decision-making process, this framework can increase trust in AI-driven decision support systems. This matters to manufacturing practitioners because it has the potential to improve the accuracy and reliability of high-precision machining, reducing the risk of errors and improving overall product quality.