More than abnormal-noise inspection — an AI digital engineering team for intelligent production quality management.

AI abnormal-noise screening built for the production line — 100% inspection of every unit, second-level OK/NG verdicts, replacing manual listening without adding cycle time.

The acoustic / vibration / NVH data analysis platform for R&D — build flows with low code, and get from data to root cause fast.

The Digital Employee Workstation wired into the MCP layer — not just talk, but real work. It calls every tool for inspection, analysis and operations, and turns master experience into Skills.

A hundred-eyed watch, on duty around the clock — remote monitoring, alerting and diagnostics that carry quality protection beyond the plant floor.

A self-supervised pre-trained deep listening model — no defect samples needed to get started. Three perspectives — overall voiceprint, perceptual alignment and temporal texture — score independently and fuse at the score layer; a single Error budget dial governs both missed defects and false stops, with the threshold recalibrated daily on site.

A lightweight detection route without deep learning: a 4-second recording compressed into 398 physically meaningful readings, 257ms per unit on CPU alone, and any wrong verdict traceable back to the exact reading. Cold-start with just 10 defective parts, converging to ≈90% detection in about a month.