Real-World Proven Data Generation for Perfectly Labelled Training Datasets

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Labelled Data

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for ML

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Large Datasets Available

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“Lack and quality of real data are truly painful problems in the Computer Vision industry. Synthetic data, as an emerging field, has the potential to fix that in an unprecedented way.”


Lead AI Engineer at Hudl

Accelerate your model development with pixel-perfect virtual synthetic data

Synthetic Data combines advanced ML techniques and Computer-Generated Imagery (CGI) models to create large sets of perfectly labelled data that is optimised for Computer Vision models by design.

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Pixel perfect labels even for parts not visible to human eye.

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Highly diverse data that is purpose built to train modern Neural Network models.

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Millions of images specifically generated for your use case in hours at low cost.

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100% compliance with GDPR, HIPAA privacy laws because Synthetic Data is computer generated.


Product Recognition in Supermarkets

Uvesco Group, a leading grocery chain in Spain, used the Neurolabs Platform to develop Object Recognition models that identify products on their store shelves. In this way, Uvesco is now able to gain real-time on-shelf visibility, resulting in reduced empty shelves, improved replenishment processes and increased planogram compliance rates with its suppliers. Synthetic data allows Uvesco to build robust product recognition models that work under different environment conditions in a fraction of the time it would require using traditional Computer Vision approaches.


"Before Neurolabs, we didn’t have real-time visibility of the shelves and this often would cause gaps in the products on the shelves, meaning they would not be available to our clients. Thanks to the synthetic technology that Neurolabs provides we were able in a few weeks to have real-time awareness of our shelves."


Head of Digital Transformation & Innovation, GRUPO UVESCO, Spain

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Food Recognition in Canteens

Advantech, a leading brand in automation in Europe, developed a cashierless checkout solution for business canteens. Advantech automation engineers used the Neurolabs Platform to train state-of-the-art Object Recognition algorithms to automatically detect food items on customers' plates. Synthetic data allows Advantech to avoid the cold-start problem and deal with new products in the menu, resulting in highly accurate and robust food recognition models.

"The advantage of this automated checkout solution is that it allows our canteen staff, so far involved in serving and collecting, to focus on meeting other customer needs, monitoring the process of replacing traditional cashiers with the cashless solution and measuring its impact, at least in the first months after implementation."



Contact Us

For partnerships, demos, platform enquires, press, job positions…or any other request, please feel free to get in touch directly by sending us a message. We’ll get back to you in less than 24h, we promise!