Real-time face redaction is the process of automatically detecting and obscuring faces in video or images as the content is captured or processed, so identities are protected without losing the broader context of the scene.

Our solution uses AI-based facial intelligence to:

• Detect faces instantly, even in low-light and high-motion environments.
• Blur or mask only facial features, so body language, surroundings, and other visual cues remain visible.
• Run on the edge, meaning data is processed locally instead of being sent to the cloud, which helps strengthen privacy and data control.

This approach helps organizations maintain the integrity of their visual data while meeting privacy expectations and regulatory requirements.

The solution is designed to fit into existing environments with minimal disruption and without major hardware changes.

Key integration and infrastructure points include:

• OS and platform support: Works with Ubuntu, Windows, and cross-platform Linux systems.
• Architecture-agnostic core: Built in high-speed C, so it can run efficiently across different hardware architectures.
• SDK plug-in architectures: You can integrate via SDKs and plug-ins, making it easier to add redaction into current video platforms or analytics tools.
• Edge-ready and low-power design: The lightweight architecture is built to run on existing IT infrastructure, helping you avoid costly hardware overhauls or additional staff.
• Media format support: Handles common video formats like MP4, AVI, MOV, MPEG and image formats like BMP, JPEG, PNG, TIFF.

In practice, this means you can add real-time face redaction as a layer within your current video workflows rather than replacing your entire stack.

Real-time face redaction helps any organization that needs to balance visual insight with privacy, especially where trust and compliance are priorities.

Common use cases include:

• Smart cities and infrastructure: Protect citizen privacy in public spaces and transit networks while still monitoring activity and safety.
• Public safety and law enforcement: Support FOIA and public records requests by masking identities in evidence, body camera footage, and drone video.
• Healthcare: Maintain strict patient and staff confidentiality in clinical areas and training facilities—especially important in close-knit or culturally sensitive communities.
• Education, hospitality, and entertainment: Keep children, students, and visitors safe and anonymous across campuses, theme parks, and recreational spaces.
• Fleet, logistics, and automotive services: Protect driver and customer identities during operational oversight in service bays and vehicle cabins.

Across these sectors, organizations can build community trust by showing they take privacy seriously while still capturing the data they need to operate and improve services.