„Garbage in - garbage out“ - an A.I. solution can only be as good as the training data. We create consistently high image quality even for complex scenarios at unlimited scale.
Next to data collection, arguably the most time consuming tasks in A.I. projects are data classification and labelling - especially if a high level of accuracy is required. Our data is pre-labelled by nature with pixel-level precision.
We recreate natural diversity, cover edge cases and rare events to solve highly specific challenges and avoid the bias problems of real-life datasets. Our data offers full flexibility in image perspectives, environmental conditions and camera specifications.
We avoid spending the valuable time of A.I. teams with months of data preparation. Most synthetic datasets can be created within days and model performance can be consistently improved.
Protecting personal data is one of the major benefits of using synthetic data. It is fully GDPR/CCPS compliant and contains no personally identifiable information or has other proprietary limitations.
Did you know that training of a single A.I. model consumes so much energy that the CO2 emission footprint is equivalent to the total lifetime value of several cars? With synthetic data, high model performance can be achieved with far less data - reducing the need for massive computing power.