Synthetic Images – Generated data and annotations for deep learning.

Training data solutions

for high performance, reliable AI vision systems.

What are synthetic images?

Synthetic images are pictures generated using computer graphics, simulation methods and artificial intelligence (AI), to represent reality with high fidelity.

Captured reference image

Generated synthetic image

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Synthetic image data is
pre-annotated

Inconsistent labels and a resource intensive annotation process are a thing of the past.
With our method of generating synthetic images, you can completely skip the manual annotation process.
We deliver images with pixel precise labels, based on your computer vision task.

Why use synthetic data?

Save time, effort and costs

Our simple three-step process has helped customers save between 50-75% of their valuable project resources and reduced turnaround time.
If you or your customer are spending months to exhaustively capture and annotate image data, reconsider your data acquisition strategy - use on demand generated images.

No more biased datasets

Captured image datasets are more often than not biased, which limit the precision and reliability of your AI models.

Synthetic image generation is the ideal approach to create unique images of scenes and characteristics that are typically under-represented - such as defects, edge cases, objects in 360 degrees, environmental variables and others.

Overcome the constraints of real data

We solve this challenge with our synthetic image offering.
As an example in the area of defect detection, we offer synthetic images representing a variety of defects on various materials - cracks, scratches, blow-holes, discolorations to name a few.
Our ever growing library of domain specific features combined with the domain expert Q&A enables us to generate images with the finest degree of realism.

Limitations on real data due to privacy policies

How do you pre-train generic AI models for a particular use-case, when data re-use clauses in customer contracts are restrictive?

Since proprietary data is a source of competitive advantage for industrial organizations, synthetically generated data is the ideal alternative to train generic deep learning models.

Synthetic image data has come a long way and its use has proven to have a number of advantages, both technically and commercially.
Our customers report experiencing a smoother data acquisition process during challenging projects. Read more!

We have a solution for you.

Let us collaborate so your team can focus on solving machine vision challenges and achieve faster project turnaround times – we are a trusted partner, generating essential image data you need.

Robotic,Vision,Sensor,Camera,System,In,Intellegence,Factory,manufacturing,Industry,For

Machine vision system integrators

Professional,It,Programer,Working,In,Data,Center,On,Desktop,Computer

Machine vision software providers

Car,Factory,3d,Concept:,Automated,Robot,Arm,Assembly,Line,Manufacturing

Manufacturing and logistics companies

Learn more about how we can add value to your business

Unlimited possibilities in 3 simple steps

Scope and specification

In this phase, we collect the relevant information related to the problem statement, scope of work, boundary conditions and success criteria.

Review and refine

In this phase, we set up the data pipeline and provide an initial dataset for review and approval. Change requests are handled in this stage.

Dataset delivery

Voila! We generate the required dataset, that is ready for you to train or validate your deep learning model.

With a view to make our technology easily accessible to customers and to address privacy requirements, we are working towards offering a self-service, subscription based image generation tool in the near future.

To know more regarding our current offering and for questions regarding the self-service tool, please contact us.