Transforming Manufacturing Into Intelligent Quality Systems
Your factory's quality failures cost millions—we solve that with AI-native systems that deploy fast, learn continuously, and integrate with your existing workflows
Our
Enhanced Quality Intelligence Platform (EQuIP)
Intelligence That Sees What MOM Systems Miss
Cross-Modal Quality Detection
Visual inspection + machine data + sensor readings processed simultaneously to identify defects that single-camera systems miss. Our patented scalable models require 90% less training data while detecting quality issues across 50+ defect classes with superior accuracy.
Rapid Scalable Deployment
60-day implementations vs 6+ month traditional systems. Pre-trained models with 500K+ industrial datapoints enable same-day deployment pilot programs. Edge-first architecture with predictable costs eliminates cloud dependency and variable pricing.
Continuous Learning Architecture
AI-native systems that adapt to production variations automatically. Simple yes/no feedback improves accuracy from 85% to 99%+ during pilot phase. Network effects across customer deployments accelerate learning for all installations.
Deep Workflow Integration
Connects quality systems (CMMs), upstream MOM/MES workflows, and production data streams. Real-time quality intelligence flows directly into existing manufacturing operations, enabling proactive quality management instead of reactive inspection.
Industries We Transform
Quality intelligence for high-value discrete manufacturing
02
Research & Technology
Customer Pain Points — In Their Own Words
01
We invested over a million in this laser system, but were only seeing 40-45% utilization.. Every idle hour costs us $2,000.. The frustrating part was knowing the capacity was there, but we couldn't seem to capture it.
John Holzheimer,
President, WLS Stamping
Cleavland, OH
02
In PCB manufacturing, it's rarely one big problem—it's dozens of small optimizations that add up.. We needed visibility into process deviations before they became defect patterns.
Noor Kaiser,
Quality Manager, Meritronics,
Milpitas, CA
03
An issue at station 3 may be actually at station 1 or somewhere else. Current systems look only at station 3... but we don't have a comprehensive way of linking all different datapoints... we are addressing the problem, not the core issue.
Global Head of Enterprise,
A Large Manufacturing Company
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