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Deep Clean UltraEdge SharpenStabilizationDenoiseMotion Smoothing
AI & automationReady to pilotBuilt by Professional ServicesLast updated 29 July 2026
AI Video Quality EnhancementLegacy catalogue restored to a standard viewers accept today
A rights-cleared archive that cannot be published because the picture quality embarrasses the platform is money that has already been spent but cannot be earned back. This POC runs legacy VOD assets through an AI pipeline that upscales resolution, raises framerate and removes noise and artefacts, so dormant catalogue becomes streamable inventory without re-licensing.
4K Upscale60 FPSDeep Clean UltraAudio Denoise
Try the demo
Original
Upscaled
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Bewitched S01E01 I Darrin Take This Witch Samantha
Drag the slider to compare.
The problem this solves
Broadcasters and rights holders are sitting on catalogues that were shot and mastered to a standard that no longer matches viewer expectations. Audiences have been conditioned by modern streaming to expect sharp, fluid playback; footage that was acceptable at SD or early HD reads as broken on today's screens. The result is a large portion of cleared, owned, cost-sunk content that cannot be placed on a platform without damaging the platform's quality perception.
Re-shooting is not an option. New licensing for replacement content costs more than the archive is worth. Traditional upscaling tools produce visible artefacts because they apply fixed filters rather than learned models. The gap between what the archive contains and what a modern platform can publish has, until recently, had no affordable solution.
Who this is for
This is relevant if you are:
Broadcaster
A broadcaster with a historical archive of SD or early-HD content that is cleared for streaming but unpublished because picture quality no longer meets platform standards
Rights holder
A rights holder whose licensed catalogue includes older footage that licensees are declining to use or paying reduced fees for due to visual quality
How it works
- 1The source asset is ingested and analysed: resolution, framerate, codec and noise profile are detected automatically to select the appropriate enhancement chain.
- 2Deep Clean runs first - noise, compression artefacts and blur are removed from each frame before upscaling begins, so the upscaler works on clean signal rather than amplifying defects.
- 3The upscaler uses a learned super-resolution model to increase resolution towards HD or 4K. Regular mode prioritises throughput; Ultra mode runs additional passes for maximum quality.
- 4Motion Smoothing raises the effective framerate, interpolating intermediate frames to produce fluid playback at up to 60 FPS without the stutter associated with traditional frame-doubling.
- 5The enhanced asset is encoded and delivered in the configured output format (MP4, MOV or MKV, H.264 or H.265) at the target resolution, ready for ingest into the platform's existing delivery pipeline.
Upscale
Resolution Enhancement
Convert low-res footage to HD or 4K. Regular mode for faster turnaround, Ultra for maximum quality.
Deep Clean
Artefact Removal
Removes noise, compression artefacts and blur. Pairs with Upscale on heavily degraded material, where either operation alone leaves visible damage.
Motion Smoothing
Framerate Increase
Increase FPS for fluid playback - achieve smooth 60 FPS output without stutter or interpolation artefacts.
Slow Motion
Frame Interpolation
Natural slow-motion up to 10x without stutter or artefacts, using learned frame interpolation rather than frame repetition.
Edge Sharpen
Detail Recovery
Crisper edges and fine detail with adjustable intensity, recovering definition lost in older codecs.
Stabilization
Camera Shake Correction
Motion correction for shaky handheld footage. A safe zoom is applied automatically where the shake is severe, which trims the frame slightly.
Dust Buster
Film Scan Restoration
Automatic removal of dirt and scratch artefacts from 35 mm, 16 mm and 8 mm film scans.
De-interlace
Interlaced Source Conversion
Convert interlaced sources such as 480i to progressive, removing comb artefacts before upscaling.
Denoise
Low-Light Cleanup
Clean night and low-light shots where noise accumulates in shadow regions.
Audio Denoise
Voice Isolation
Isolate voice and remove background noise from the audio track alongside the visual restoration pass.
What makes it different
Standard upscaling tools apply fixed filters designed to produce acceptable output across a wide range of content. This pipeline uses learned models trained on broadcast-grade material, which means the enhancement decisions are content-aware rather than content-agnostic. Deep Clean runs before upscaling rather than after, so the resolution model works from clean signal. The pipeline is also modular: individual enhancement steps can be combined or omitted depending on the source material, rather than applying a single preset to everything.
Current status & next steps
Ready to pilotReviewed 29 July 2026
AI Video Quality Enhancement is ready to pilot. The demo on this page runs against a set of prepared clip pairs and lets you drag the slider to compare original and enhanced output side by side.
Enhancement is not a real-time process: how long a job takes depends on source duration, the operations selected and the quality mode, and Ultra mode costs significantly more time than Regular, so the quality-versus-throughput trade-off has to be settled per project. Stabilisation applies a safe zoom when correcting severe shake, which trims the effective frame area slightly. Output is H.264 or H.265 in MP4, MOV or MKV; other containers and codecs are not supported yet. Resolution can be set to any target, but upscaling improves technical quality metrics rather than recovering detail the camera never captured.
The next step is a pilot against customer archive material: real footage, real enhancement settings, real delivery targets.
Want to restore your legacy catalogue?
Bring us a sample of your toughest footage and tell us the target platform. We will run it through the pipeline and show you the output before any commitment.