Protect every identity in public.

Towards realizing our mission, we are providing the most advanced solutions to protect personally identifiable information in camera data. Anonymizing images and videos is crucial to comply with increasing privacy regulations like GDPR, CCPA, APPI and CSL. At the same time, data quantity and quality are the backbone of new innovations powered by analytics and machine learning. With our solutions, there is no trade-off and the future of sustainable, consumer-centered innovation comes one step closer.

Face Anonymization

With increasing capabilities of facial recognition technology, large datasets from CCTV, automotive or smartphone cameras carry substantial risk. brighter AI provides Precision Blur, the most advanced face redaction solution, and Deep Natural Anonymization. With this solution, synthetic face overlays protect individuals from face recognition. At the same time, the data is still usable for analytics and machine learning.

License Plate Anonymization

brighter AI provides license plate redaction and artificial overlays that appear natural. Maintaining a natural appearance is crucial in use cases that involve machine learning, for example for the development of autonomous vehicles or ADAS functions. In these use cases, Deep Natural Anonymization has no adverse impact on neural networks.


Integrate seamlessly
(on-premise, cloud, edge)

Accelerate data

Empower data

Protect identities against
automatic recognition

Comply with regulations
(e.g. GDPR, CCPA)

Enable analytics & AI
(natural anonymization)

Why Deep Natural Anonymization?

By replacing faces and license plates with natural-looking overlays, Deep Natural Anonymization is the only privacy solution for videos compatible with analytics and machine learning.

Award-winning technology

“Europe’s Hottest
AI Startup”
by Nvidia
“Most Innovative
ADAS Technology”
by Automotive Tech.AD
German Digital Award
“The Spark”
by Handelsblatt and McKinsey

Compatibility with machine learning

“Brighter AI’s natural anonymization solution has no adverse impact on the performance of our machine learning models.”

AV Development Lead, Automotive Tier 1

Training with the Original Data vs. Deep Natural Anonymization Technology (DNAT); Cityscapes Validation Dataset

Original 0.307
DNAT 0.307
0 0.1 0.2 0.3

Mean Average Precision (IoU = 0.50 : 0.95)

Instance Segmentation with Mask-RCNN

“The technology makes data collection in public compliant according to privacy regulations worldwide, such as GDPR in Europe, CSL in China and the upcoming CCPA in the US.” The Washington Post, March 21st, 2019
“Brighter AI has solved a fundamental problem of using and storing image and video data in compliance with data protection regulations.” Handelsblatt, November 23rd, 2019
“Brighter AI, a spin-off from the electronics specialist Hella, for example, was able to secure a multi-million investment with its anonymization software for camera images, which is in demand in the automotive industry.” WirtschaftsWoche, January 14th, 2020
“The best 10 AI startups in Germany – Brighter AI uses neural networks to generate artificial faces and license plates that are not recognizable as fake.” Business Insider, June 22nd, 2019