
Case Study
Revolutionized critical asset monitoring
Revolutionized asset monitoring in cold chain logistics and smart agriculture using Klyff's Edge AI-powered IoT platform for efficiency, sustainability, and real-time insights.
Open case studyAutomated Quality Inspection That Catches What AOI Misses
Reduce escape defects, rework, and warranty claims with vision AI that runs on the hardware you already have—and keeps your data in your plant.
Problem Statement
Klyff’s Automated Quality Inspection is built to sit on top of your existing lines, cameras, and AOI to catch the defects that get through today—and do it at full line speed.
Escape defects: 0.5–2% of units leaving the plant with hidden or missed issues
Rework & scrap: 5–10% of production cost tied up in fixing what should have been right first time
Manual bottlenecks: Inspectors can’t keep up with line speed—especially on complex PCB, auto, and pharma lines
Inconsistent decisions: Different inspectors on different shifts = different quality thresholds
Klyff Inspeqtr Delivers
Inspeqtr combines measurable quality gains with deployment choices that fit real production environments.
~1.5% → 0.3% or lower.
+2–4 percentage points (for example 94% → 97–98%).
$250K–$500K/year savings per site (depending on volume).
From 100% manual to fully automated, real-time at line speed.
Weak solder joints, subtle paint defects, misalignments, label errors, surface anomalies.
Jetson, Coral, industrial PCs, existing cameras—no lock-in to a single vendor.
All images and models stay inside your facility—ideal for IP-sensitive and regulated environments.
From a single PCB line to global fleets of plants.
How Klyff Inspeqtr Works
The rollout moves from line assessment and model training into edge deployment and ongoing model improvement.
Walk the line with your operations and quality team.
Identify critical defect modes, escape hotspots, and existing AOI/manual flows.
Define target metrics: escape rate, FPY, PPM, rework cost.
Use your historical images and defect records (or capture new data on the line).
Train vision AI models on your real defects—not generic datasets.
Validate against your quality thresholds and sampling plans.
Deploy models to your existing edge hardware (Jetson, Coral, x86, etc.).
Integrate with MES/ERP/SCADA/PLC for automatic logging and Andon/alerting.
Run in shadow mode first, then move to live decisions.
Monitor model performance 24×7.
Capture new defect types and process drift.
Automatically retrain and roll out improved models with zero production downtime.
Why Klyff Inspeqtr for Automated Quality Inspection
Inspeqtr is designed for fast, private, hardware-flexible quality inspection on real manufacturing lines.
Bring your own cameras and compute; Klyff optimizes to whatever you have.
No images leave your site, ever.
Versioning, monitoring, retraining, OTA updates are built-in.
Clear dashboards for FPY, escape rate, and PPM—by line, shift, and defect type.
Examples
Inspeqtr supports defect detection and verification workflows across electronics, automotive, and regulated production lines.
FAQs
Selected Customer Success Stories
Explore how teams are using Klyff to improve quality, safety, and operational performance in the field.

Case Study
Revolutionized asset monitoring in cold chain logistics and smart agriculture using Klyff's Edge AI-powered IoT platform for efficiency, sustainability, and real-time insights.
Open case study
Case Study
Discover how a global retail leader reduced energy costs by 15% using Klyff's Edge AI platform for real-time monitoring, anomaly detection, and proactive energy management.
Open case studyMore Case Studies
talk to an engineer today
Insights
Connect your first site, deploy your first model, and see measurable ROI in weeks, not months.