AI Redaction · Transport

Keep up with demand for CCTV and incident data

As demand for footage increases, redaction becomes the bottleneck. AI Redact helps transport teams process and prepare content faster.

AI Redact processing station CCTV footage of commuters on stairs and an escalator, with multiple faces detected and queued for reviewer approval
10×

Throughput versus manual frame-by-frame review.

4

Media types in one workflow: video, audio, documents and images.

100%

Of masks reviewer-approved before export, with full audit trail.

How it works

Four steps, one supervised pass.

Step 1

Upload

Bring in CCTV footage, on-train audio, dashcam clips, incident reports or supporting documentation. All formats handled in one place.

Step 2

Detect

AI identifies faces, voices and personal data across your content automatically. No manual frame-by-frame work across hours of footage.

Step 3

Redact

Redaction is applied automatically across all detected items. Reviewers see every mask before anything is exported. Nothing leaves without approval.

Step 4

Approve

Teams review and confirm every redaction before sharing. The audit trail records who approved what and when, ready for SARs, BTP handovers and incident disclosure.

The reality in transport

Requests don't arrive as single files.

A typical transport disclosure involves multi-camera CCTV footage from platform and carriage, audio recordings, and supporting reports or documentation. Managing those across separate tools, often under a tight SAR or incident response deadline, makes redaction the bottleneck. Not the exception.

  • Multi-camera CCTV footage
  • Audio recordings
  • Reports and documentation

The process is manual, repetitive, and time-sensitive.

AI Redact video interface showing CCTV footage with faces detected and queued for redaction
AI Redact flexible deployment diagram showing CCTV, audio and document sources feeding into a single redaction workflow

Where AI Redact fits

Everything in one workflow.

AI Redact brings bulk redaction across video, audio and documents into a single process. It works alongside your existing CCTV, evidence and incident systems rather than replacing them. No platform lock-in, no separate tool per format.

  • Bulk redaction across formats
  • One process instead of multiple tools
  • Works alongside existing systems

What changes

Faster response times. Less fragmented work.

When detection is automated and review is consolidated, disclosure stops being the bottleneck. Your team spends time making decisions, not drawing masks across hours of footage.

  • Faster response times
  • Less fragmented work across tools
  • Greater consistency and control
AI Redact document redaction interface showing personal data identified and masked across an incident report

Redaction holding up response times?

There's a more efficient way to handle it. See AI Redact with transport scenarios.

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Frequently asked

What media types can AI Redact handle?
Video (faces in CCTV, dashcam and on-train cameras), audio (selective mute or beep on sensitive speech), documents (PDFs, scanned forms and images) and still images. The same review interface and audit trail covers all four media types in one workflow.
Is AI redaction accurate enough for disclosure?
AI handles detection; reviewers handle decisions. Every mask is presented for human approval before the redacted asset is exported, so the standard a disclosure has to meet is the one your reviewers apply, not the model's. The audit trail records who approved what and when, supporting chain-of-custody requirements for SARs, BTP handovers and incident documentation.
Can it handle multi-camera incidents?
Yes. Clips from multiple cameras covering the same incident can be merged into a single asset and redacted in one pass: platform, carriage and on-train footage handled together. This removes the need to manage separate clips through separate processes when preparing a disclosure package.
Does AI Redact need to replace existing systems?
No. AI Redact works independently of body-worn video, dashcam and CCTV systems. It runs as a standalone capability or alongside a wider Aetopia DAM rollout, sitting beside the incident and evidence tools your teams already use rather than replacing them.
How does AI-assisted redaction compare to manual redaction?
Manual frame-by-frame redaction by a trained reviewer covers roughly ten to fifteen minutes of footage per hour of work. AI handles the detection, leaving the reviewer to confirm or adjust masks rather than draw them from scratch. Throughput typically improves by an order of magnitude, with the same reviewer-approved quality and audit trail.
Aetopia AI Redact search results panel with a person selected and a Redact Original confirmation prompt

Human review stays in place

AI speeds up detection. Your team retains control.

Every mask is presented for approval before the redacted asset is exported. Playback controls, review tools and automatic saving keep long or complex multi-camera tasks moving without risk of lost work. The audit trail records who approved what and when: ready for SARs, BTP handovers and incident disclosure.