Visual QA
Deploy Vertex AI Vision models to industrial edge sensors. The system identifies production defects in real-time and integrates directly with ERPNext quality records and physical rejection hardware via MQTT.
The Operational Bottleneck
"Human inspection on high-speed production lines is prone to fatigue, leading to 'scrap escapes'. High-end vision systems are often proprietary data silos, making it impossible to track accurate scrap-by-batch ROI in the ERP."
The Sovereign Solution
We deploy custom Vertex AI Vision models to industrial edge cameras (Google Coral hardware). The system identifies defects at line speed, triggers physical rejection via MQTT, and logs failing telemetry directly into ERPNext.
Core Mesh Architecture
Sovereign Cloud Integration
Edge Camera Feed
Sub-100ms Industrial Capture
Coral AI / Vertex
Real-time Defect Classification
MQTT / IoT Core
Automated Line Rejection
Real-World Application
Sterile Blister Line Inspection
A medical device packager is running a high-speed sterile blister line. A subtle defect occurs where the heat-seal is incomplete by less than 1mm—invisible to the naked eye at 200 units per minute. Visual QA detects the seal breach via a specialized anomaly model.
The system triggers a pneumatic arm to eject the unit and creates a Quality Inspection entry in ERPNext, linking the defect to 'Machine A / Shift 2 / Film-Batch 902'. This allows the manager to recalibrate before wasting $10k in material.
Operational Logic
Continuous
Decision Flow
Image Capture
High-speed frame acquisition from industrial edge sensors.
Edge Inference
Vertex AI Vision models running on local Google Coral hardware.
Classification
Instant PASS/FAIL logic applied to every production unit.
System Loop
Auto-rejection of defects and real-time scrap rate logging in ERP.
Measurable Impact
ROI Dashboard
Exceeding human capability at high line speeds.
Eliminated through automated real-time rejection.
Saved through early detection and rapid recalibration.
Google Cloud Ecosystem Alignment
* Infrastructure costs billed directly via your private GCP project.