Transforming Manufacturing Workflows: Zebra Technologies Unveils Machine Vision Ecosystem at Automate 2026
Key Terms
machine vision technical
rfid technical
frame grabbers technical
optical character recognition (ocr) technical
Company debuts new high-performance machine vision camera and showcases solutions that empower connected frontline workers

Zebra debuts its new CV70 CXP machine vision camera, a high-performance solution for customers implementing high-speed, high-resolution applications.
According to Zebra’s latest Manufacturing Vision Study,
“We relentlessly deliver innovation to help our customers overcome their biggest operational challenges,” said Charlie Long, Vice President and General Manager, Machine Vision, Zebra Technologies. “We are eager to connect with attendees at the event to discuss how combining machine vision, data, and AI with human expertise can drive immediate efficiency gains, tailored to their unique environments.”
High-Performance Camera Optimizes Quality Control
As manufacturers look to automation to improve quality, Zebra’s study shows that
The CV70’s design accelerates demanding tasks like small parts inspection, EV battery assembly, and semiconductor inspection. With Zebra’s Aurora software, frame grabbers, and vision controllers, customers have a complete vision solution and fully tested and validated system from a single vendor to solve their most challenging machine vision needs.
Interactive Demonstrations Highlight Live Workflows
Attendees visiting Zebra’s booth will experience live demonstrations of how Zebra’s solutions create fully connected, optimized operations including the 4Sight XV7 vision controller and the Rapixo CXP Pro Octo frame grabber. Other solutions on display include:
- Machine vision hardware and software featuring 3D inspection, AI-based anomaly detection, and AI-based optical character recognition (OCR).
- An in-line, fully automated print and apply process using machine vision and RFID technology for package and label validation.
- An automated factory staging and storage setup with Zebra’s RFID solutions driving real-time tracking and workflow efficiency.
- Photoneo, now part of Zebra Technologies, is demonstrating vision-guided robotics applications for bin pick, box depalletizing, and picking parts from custom dunnage, alongside 3D volume measurement.
In addition, Charlie Long will lead a speaking session titled, “The Augmented Operator: Driving Productivity with Machine Vision and Mobile Intelligence,” which takes place on June 22 from 12:00 – 12:30 CT at the Automate Innovation Stage in Booth #19046.
KEY TAKEAWAYS
- At Automate 2026, Zebra showcases intelligent automation solutions that empower frontline workers and create smarter, end-to-end supply chain operations extending from raw material receiving to final distribution.
- Zebra launches the CV70, a new high-performance, ultra-compact machine vision camera designed to accelerate performance in high-speed and high-resolution applications.
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Visit Zebra in Booth #1825 at McCormick Place in
Chicago , June 22-25, to experience an ecosystem of solutions for asset visibility and intelligent automation.
WHO IS ZEBRA TECHNOLOGIES?
Zebra (NASDAQ: ZBRA) provides the foundation for intelligent operations with an award-winning portfolio of connected frontline, asset visibility and automation solutions which empower our customers to deploy AI on the frontline. Organizations globally across retail, manufacturing, transportation, logistics, healthcare, and other industries rely on us to deliver outcomes today while driving innovation for what’s next. Together with our partners, we create new ways of working that improve productivity and empower organizations to be better every day. Learn more at www.zebra.com.
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View source version on businesswire.com: https://www.businesswire.com/news/home/20260622743565/en/
Media Contact:
Matt Towson
Zebra Technologies
+1-773-454-5396
matt.towson@zebra.com
Industry Analyst Contact:
Kasia Fahmy
Zebra Technologies
+1-224-306-8654
k.fahmy@zebra.com
Source: Zebra Technologies Corporation