21. August 2025
In today‘s day and age, video and image data aren’t just content. It represents digital records of our lives. From city streets to in-vehicle cameras and retail environments, every frame captured can contain Personally Identifiable Information (PII). This makes video and image data one of the most sensitive data types in modern enterprises.
With the rise of privacy regulations around the world, such as GDPR (European Union), CCPA (California, USA), CSL/PIS (China), PIPA (South Korea),and APPI (Japan), protecting individual privacy is a critical strategic step and a legal requirement. And as privacy regulations evolve, so does the demand for robust, adaptable privacy technology.
At brighter AI, we have spent the last seven years leading the field of video and image anonymization, helping organizations around the world protect identities without compromising on data utility or innovation. We know that every organization operates differently, and there is no one-size-fits-all approach to compliance.
Which deployment is the right fit for you: brighter Redact Online, Enterprise, or Edge?
Each deployment option offers unique advantages tailored to your specific privacy, performance, and infrastructure goals. Here is how to choose:
- brighter Redact Online
- brighter Redact Enterprise
- brighter Redact Edge
Use case 1 – brighter Redact Online
For teams looking to anonymize large workloads with zero infrastructure management, brighter Redact Online is the go-to solution. Our Kubernetes cluster – running on Microsoft Azure – combines horizontal scalability with enterprise-grade security and is ready to use through our REST API.
Key outcomes:
- Improved compliance with privacy legislations: TISAX-ready architecture, with hardened security, and strict data retention policies.
- Accelerate your data processing: Upload, redact, and download – no maintenance
- Integrate at scale: Use our REST API via plain HTTP calls or our Python redact-client.
brighter Redact Online automatically scales depending on your data load, spinning up hundreds of Azure nodes to reach thousands of frames per second. Your teams get high throughput without managing a Kubernetes cluster and the corresponding maintenance.
You can try brighter Redact Online with our user-friendly web app. Check it out today: portal.brighter.ai
Click here for more information on brighter Redact Online
Use case 2 – brighter Redact Enterprise:
For enterprises where the data needs to remain on their infrastructure, brighter Redact Enterprise gives you full control. Whether you orchestrate your workloads in a private data center or a cloud provider, our solution adapts to your infrastructure.
We provide two kinds of deployment options for on-premises, which you can choose according to your needs. We help you to scale by:
Cluster on AWS EKS
If you expect to process hundreds of hours of video daily and need elastic scalability, the cluster on AWS EKS is the best option for you. It has the following features:
- Customizable Throughput Modes:
- High-efficiency mode can handle up to one hundred 15 GB videos in parallel, offering approximately 500 frames per second on up to 150 machines
- High-throughput mode processes up to three hundred 15 GB videos in parallel at thousands of frames per second on up to 400 machines, relying on on-demand instances for maximum stability.
- Privacy by Design: Architecture provides a solid security posture, which provides significant throughput for large-scale anonymization
Single-machine setup using Docker Compose
If you prefer a simpler approach or work in a secure, isolated setting, Docker Compose on a single machine offers a powerful yet contained solution.
- Anonymize even without internet access
- Direct control over data: This setup deploys the entire anonymization pipeline (pre-processing, deep-learning inference, and post-processing) behind a REST API, giving you direct control over incoming data.
Deciding between two on-premise strategies depends on the volume of the data you want to anonymize, as well as the available budget for meeting your privacy compliance.
Click here for more information on brighter Redact On-Premise
Use case 3 – brighter Redact Edge:
When privacy can’t wait, brighter Redact Edge enables real-time anonymization directly on the data-generating device. Whether it is a vehicle, a factory camera, or an IoT system. Designed for speed, low latency, and full autonomy, it’s the ideal solution for edge computing environments.
Key outcomes:
- On-Camera Redaction: brighter Redact Edge provides on-device (camera) redaction, ensuring video and image data is anonymized at its point of origin. This effectively minimizes privacy risks.
- Works without an internet connection: Our edge solution works even without an internet connection, giving a speed of 25 FPS, and approximately 4 cameras can run on one device
- Custom Deployment: brighter Redact Edge can be deployed natively and as a container. For the native option, there is no container overhead, and the device hardware is directly accessed.
- Optimised for industry devices: brighter Redact Edge is fully functional for both x86 and ARM architectures and is speed-optimized for NVIDIA devices, which allows achieving real-time frame rates for any application requiring immediate anonymization.
Click here for more information on brighter Redact Edge
Every enterprise has its specific needs and requirements; we offer three distinct deployment models to support your privacy strategy: whether you work in the cloud, run infrastructure on-premise, or need real-time on-device anonymization at the edge. We anonymize, wherever your data lives. With us, your teams can scale Personally Identifiable Information (PII) protection: securely, intelligently, and in full alignment with regulatory standards.
To learn more about sizing, licensing, and cost, we invite you to reach out to our sales team at sales@brighter.ai or just fill in our contact form. We will help you select and tailor the right anonymization architecture for your specific needs, ensuring you protect sensitive information without compromising on performance.
