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  • Writer's pictureNeurolabs

How Synthetic Image Recognition is Revolutionising Consumer Packaged Goods

Retail is a highly competitive industry whereby speed, accuracy, scalability and efficiency are often key differentiators between the success or failure of any software/solution serving the sector.

Successful image recognition is reliant on 4 key factors: speed, accuracy, scalability and efficiency

As we have explained previously, synthetic data, particularly synthetic computer vision, is both the future and natural evolution of Retail Shelf Auditing and image recognition. External Field Marketing Agencies (FMAs) and Sales Force Automation companies (SFAs) that aren’t making strides towards a synthetic pipeline are going to be left behind by their competitors who will be able to provide Consumer Packaged Goods companies (CPGs) with better analysis and performance due to the improvements that synthetic image recognition delivers.

Over the course of this article, we will be exploring what is synthetic image recognition and explaining how it revolutionises CPGs.

What is Synthetic Image Recognition?

Synthetic image recognition is a revolutionary and technologically advanced form of image recognition that harnesses the power of synthetic data.

All image recognition solutions are built using artificial intelligence (AI) called computer vision. This form of AI essentially acts as the eyes of a computer, allowing it to “see” and contextualise real data and imagery. However, as the name suggests, synthetic image recognition uses synthetic data and synthetic computer vision to break away from the limitations of real data and traditional computer vision. The end result is a synthetic image recognition solution that is faster to deploy and vastly more accurate than traditional image recognition. In addition, synthetic image recognition is also far more scalable, allowing it to streamline product catalogues across multiple retail locations and cater to FMAs and SFAs of all sizes.

Traditional IR versus Synthetic IR methods

How does Synthetic Image Recognition work?

Synthetic computer vision and synthetic data are both crucial to how synthetic image recognition works. Using our synthetic data-driven ZIA (Zero Image Annotations) solution as an example, instead of requiring numerous images and various other types of real data, our synthetic computer vision solution allows us to create realistic, 3D digital twins of SKUs from a single PDF of the manufacturing artwork/packaging.

Once the 3D digital twin has been generated it is then placed in a number of virtual scenes under numerous lighting conditions and angles. These virtual scenes generate synthetic data which is then used to train our synthetic computer vision model.

The virtual scenes created by ZIA help replicate countless real-world lighting scenarios, product positioning and product deformations, allowing our synthetic image recognition solution to produce accurate and reliable results.

In other words, for a more cost-effective, faster to deploy, and more accurate way to generate training data for image recognition, synthetic data is the answer.

How synthetic image recognition works

What can Synthetic Image Recognition do for CPGs?

By leveraging synthetic image recognition technology, CPG companies can gain valuable insights into their products and how they are marketed and sold. Below we have outlined three ways that synthetic image recognition is benefiting CPGs:

  1. Accurate identification: Synthetic image recognition technology offers unparalleled accuracy when it comes to product detection, far surpassing traditional image recognition. In a matter of seconds, CPGs can acquire high-grade data, and since synthetic image recognition accuracy does not decrease over time – as is the case with traditional image recognition technology – it is dependable and consistent, allowing CPGs to enjoy improved inventory management, product tracking, and planogram compliance.

  2. Faster onboarding: Synthetic image recognition solutions make it possible for a CPG’s SKU catalogue to be onboarded faster into the respective image recognition technology. With a synthetic solution, CPGs face almost no downtime when onboarding. As such, the speed of onboarding for both a CPG’s initial catalogue and new SKUs is considerably quicker when using synthetic image recognition compared to traditional image recognition solutions.

  3. Robust image recognition: Powered by synthetic computer vision, synthetic image recognition solutions such as our ZIA tool have the ability to recognise product deformations. Unlike traditional image recognition, which can struggle to identify when a product has been damaged, synthetic image recognition allows products to be detected even if there are defects, inconsistencies or other quality issues affecting the product.

Synthetic image recognition is revolutionising the CPG industry by providing companies with valuable insights into their products, packaging, and displays.

By leveraging synthetic image recognition, CPGs can optimise their product placement, improve shopper insights, ensure quality control, and gain a competitive edge. As synthetic image recognition technology evolves, it will become an essential tool for CPG companies, FMAs and SFAs who want to stay ahead of the curve and improve their bottom line.

Why will Synthetic Image Recognition revolutionise Retail Shelf Auditing?

Synthetic image recognition harnesses the power of synthetic data and synthetic computer vision to deliver a truly next-generation image recognition solution.

As referenced at the beginning of this article, speed, accuracy, scalability and efficiency are crucial components of any viable software or technology in the retail sphere. Below we have highlighted how synthetic image recognition technology, such as our ZIA solution, offers a revolutionary evolution to retail execution.


ZIA ensures a streamlined, effortless experience from start to finish. Our onboarding process is significantly faster than traditional image recognition solutions, and we can swiftly create 3D Digital Twins of SKUs with unprecedented speed. Rather than building datasets from real product images - a process that is often time-consuming, prone to human error, and limited in the number of variations achievable. ZIA uses SKU Digital Twins created from manufacturing artwork to generate thousands of synthetic image variations that would be impossible to achieve otherwise. With ZIA, onboarding, catalogue creation and model training are lightning-fast. In fact, an FMA can onboard a new CPG customer in just one day and provide a time to market of one week for up to 1,000 SKUs.


Our synthetic image recognition technology is trained using 3D digital models of SKUs in a wide range of virtual scenes with varying product placements and lighting conditions. As such, we are able to deliver more robust image recognition giving CPGs more accurate and reliable results than traditional image recognition technology.

ZIA's product detection accuracy is consistently high, and it stays that way. This is because our image recognition technology is trained using synthetic data, allowing it to learn faster from a larger and more diverse data pool than real data can. In addition, if and when the accuracy is observed to start declining, new synthetic data can be generated automatically, and the model retrained so that its performance is brought back to production levels. As such, this eliminates the drop-off in accuracy that traditional image recognition is prone to.

With synthetic image recognition, you can achieve +95% product detection accuracy from the outset and increase to above 98% for specific categories.


Synthetic image recognition makes scaling product catalogues across multiple locations incredibly easy and efficient. With our cloud-based catalogues, you can quickly upload new SKUs and respond to changing market needs without compromising time-to-market or accuracy. Our streamlined catalogues also make it easy to scale cost-effectively, allowing you to stay ahead of the competition.


The problem with traditional image recognition is that it is an entirely reactive process. For example, an FMA can only provide CPGs with data analysis once an SKU has already hit store shelves. This is because the product has yet to be photographed and uploaded to an FMAs image recognition solution. With synthetic image recognition, however, you no longer need real imagery. Instead, you can enjoy day-one support for currently unreleased SKUs by uploading in-production packaging labels to ZIA.

At Neurolabs, we understand that many FMAs and SFAs already employ end-to-end solutions for image recognition, making switching to a new solution rather time-consuming and financially unviable. As such, we have developed our state-of-the-art technology to serve as an intuitive “plug&play” upgrade that can slot alongside any existing solutions and analytics software currently in use.

Our solution is designed with efficiency and practicality at the forefront, allowing you to improve your image recognition solution without overhauling your existing software or entire infrastructure.

We are dedicated to making sure that integrating ZIA is as straightforward and efficient as possible. We work with FMAs and SFAs on behalf of CPG companies to make our synthetic IR part of their existing product, allowing CPGs to reap the benefits of a modern, automated solution without having to worry about complex technical details.

With ZIA, FMAs and SFAs can quickly and easily integrate synthetic IR into their existing system without laborious onboarding and time-consuming data labelling. This means field reps can continue using their current solution while our API can be connected to business intelligence and data visualisation tools to help FMAs and CPGs track KPIs and other product-related insights.

Prepare for the future of Retail Shelf Auditing with Synthetic image recognition by Neurolabs

Whether you’re looking for accurate and reliable image recognition, optimised shelf execution, aiming to streamline your onboarding procedure, or seeking a faster shelf auditing delivery time, we are here to help.

Synthetic image recognition is the future of Retail Shelf Execution. Check out our new ebook to learn more about how this groundbreaking technology can enhance your workflow and, most importantly, keep your business ahead of the competition.

The Future of Retail Shelf Auditing Ebook - Download eBook

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.


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