brighter Redact Edge by brighter AI

brighter Redact Edge ensures privacy by anonymizing sensitive data directly at the Data Collection Point, whether it is in-vehicle or on-camera. It instantly redacts sensitive information and ensures that only secure, GDPR-compliant data is transmitted.

Trusted by the leading enterprises:

Key Features

Privacy-compliant data transmission

Easy to integrate with current hardware and software

Real-time anonymization without an Internet connection

Economical solution with unrestricted access to blurring functionalities

Using Docker, offline and also with direct native integration

Compatible with all the common hardware: Nvidia, Asus, ARM, and Intel

Why Do You Need brighter Redact?

Anonymization at the Data Collection Point (DCP)

Easy Integration

Offline Installation

Instant Redaction

Proven Compliance

Available on all major platforms and engines:

Our technology is compatible with all major platforms and engines, including NVIDIA, Asus, ARM, and Intel.

Kion uses video to increase the safety of their heavy machinery like forklifts.

Kion implements the brighter Redact solution to protect privacy for autonomous forklifts by anonymizing faces and license plates.

Details: Kion’s autonomous forklift ADAS system uses a deduplication strategy to remove similar images in a stream, which requires optimizing each frame individually rather than processing videos. This ensures each image is independently anonymized, maintaining compliance and privacy standards.

Solution/Service: The brighter Redact solution employs DNAT (Deep Natural Anonymization Technology) and Precision Blur to anonymize faces and license plates with the highest accuracy rate in the industry. Personally Identifiable Information (PII)/Sensitive information, including faces of employees and license plates, is anonymized in real-time.

Deployment: Kion first examined scalable OP deployment, received onboarding, and now considers OP deployment adequate for its operational requirements.

Data Type: Each frame is processed on its own due to the need for de-duplication, preventing the use of video processing.

Data Resolution: Resolutions are 640×480 and 960x, with a possibility of future enhancements. Tens of thousands of images are processed daily, divided between DNAT and blur according to operational demands.

Outcome: brighter Redact by brighter AI allows Kion’s autonomous forklifts to function within strict privacy regulations by consistently anonymizing faces and license plates in each frame. With high-performance hardware, Kion achieves real-time anonymization and compliance, minimizing regulatory risks and protecting personal data in image streams.

With BVG expanding its tram network in Berlin, new driver training relies on tram route videos that capture road conditions. brighter Redact by brighter AI provides on-device anonymization of passengers’ faces and license plates, ensuring privacy compliance without transferring sensitive data off the train.

To efficiently train new drivers while managing a tight schedule and limited vehicle resources, BVG utilizes tram route videos to record road conditions. Anonymization of passengers and vehicle plates is essential to comply with GDPR

Challenges

GDPR Compliance: Training videos capture sensitive personal data, including passengers and vehicle plates, making it essential to anonymize data to avoid GDPR fines and reputation damage.

Hardware Requirements: The solution requires compact, lightweight hardware with encrypted storage for secure, anonymized video storage.

Solution:

brighter Redact by brighter AI powered by Precision Blur, which is implemented on LAT-provided recording technology to anonymize personal data. With real-time anonymization directly on the tram’s workstation, the solution prevents sensitive data from leaving the tram, maintaining BVG’s compliance with privacy regulations and streamlining training efficiency.

Outcome:

By using brighter Redact, BVG meets GDPR compliance requirements, enhances resource efficiency, and supports operational improvements. Precision Blur minimizes storage and processing demands while ensuring secure, real-time anonymization onboard.

DB S-Bahn Stuttgart and brighter AI: Anonymized passenger analysis for capacity measurement

To prevent trains from overcrowding, plan passenger capacities optimally, and manage passenger flows intelligently, Deutsche Bahn piloted automated passenger density analysis for the first time on 27 April 2020 in Stuttgart. brighter Redact by brighter AI ensures that privacy is maintained by anonymizing at the point of collection either inside or next to the camera. This cutting-edge technology makes it possible to use the existing camera infrastructure of the trains in a data protection-compliant way.

brighter Redact by brighter AI ensures that privacy is maintained by anonymizing at the point of collection either inside or next to the camera. It runs independently on the train’s on-board computer, anonymizing individual images on the edge without modifying existing systems. Temporarily stored onboard, anonymized images are securely transmitted over a TLS-encrypted network to ISO27001-certified servers in Germany, where automated algorithms classify seats as free or occupied. Managed under a privacy-by-design framework, the system provides periodic seat occupancy snapshots (covering 63% of seats) to optimize seat availability and operational efficiency without real-time data processing.