
May 9, 2026
Just a few years ago, Amazon's 'Just Walk Out' technology was hailed as a game-changer for retail, promising to revolutionise the shopping experience with AI, computer vision, deep learning and sensors.
Customers could effortlessly shop without relying on conventional checkouts. By picking up products or adding to their carts, the innovative technology, powered by computer vision and sensors, seemingly registered and billed items directly to their Amazon accounts.

However, recent revelations show that Amazon's technology wasn't entirely automated. Despite being deployed in half of Amazon Fresh stores, the system relied heavily on a team of over 1,000 remote cashiers in India.
“There’s a grey area in artificial intelligence filled with millions of humans who work in secret — they’re often hired to train algorithms but end up operating much of their work instead.” – Parmy Olson for Bloomberg.
Reports from Business Insider & The Information indicate that the technology faced significant challenges, proving slow and costly to implement. 700 of every 1,000 walkouts had to be reviewed, meaning the remote cashiers took hours to process data, delaying customer receipt generation.
Critics have also raised ethical concerns about Amazon's practices. Not only did Amazon underpay their third-party workers instead of hiring locally, but the company's accumulation of sensitive customer data, including in-store behaviour, has sparked privacy debates, turning routine shopping trips into potential breaches.
As Computer Vision technology has become a formidable force in the CPG industry, this breaking story has forced CPG brands to consider what real computer vision technology looks like and if it is viable for their business needs.
In light of recent revelations about Amazon's 'Just Walk Out' technology, it's evident that the promises of seamless retail experiences through AI and computer vision are not always fulfilled.
As the retail landscape evolves, Neurolabs remains committed to providing technical solutions that empower businesses while upholding the highest standards of integrity and performance.
Our technology leverages synthetic data, generating 3D models for training and surpassing the limitations of real data. This approach ensures enhanced reliability, accuracy, speed, and cost efficiency in data processing and analysis.
“In the past, we relied on a 60-person team of annotators and couldn’t achieve the desired accuracy results. Now, we use Neurolabs for Image Recognition.”— Tier 1 Soft Drinks Manufacturer.

Our state-of-the-art Image Recognition technology ‘ZIA’ (Zero Image Annotations) is designed by experts to offer features such as:
While Amazon's approach faced challenges and ethical concerns, Neurolabs stands apart with our innovative ZIA technology. Unlike Amazon's reliance on third-party workers and questionable data practices, ZIA offers a superior solution that is efficient, reliable, and ethical.
With seamless integrations, rapid product onboarding, advanced training models, and enhanced visibility through In-Store Scene Understanding (ISSU), Neurolabs ensures that businesses have access to cutting-edge computer vision technology that is both effective and efficient.
In the rapidly evolving retail technology landscape, the recent news about Amazon's technology underscores the importance of integrity and efficiency in adopting new solutions.
Using synthetic computer vision, we have created a solution that eliminates human error and offers users superior accuracy, speed, scalability, and reliability.
Experience the transformative power of ZIA firsthand by booking a demo today and revolutionising your business's approach to retail execution.

At Neurolabs, we are revolutionising in-store retail performance with our advanced image recognition technology, ZIA. Our cutting-edge technology enables retailers, field marketing agencies and CPG brands to optimise store execution, enhance the customer experience, and boost revenue as we build the most comprehensive 3D asset library for product recognition in the CPG industry.