One video. Every device.
Every network.
What if the same video could serve every device, network and workflow without creating multiple versions of the same content?
A hierarchical approach enables a single video asset to support multiple delivery requirements more efficiently, reducing complexity across modern video workflows.
The challenge of delivering video everywhere
Modern video must support broadcast, streaming, social media, connected devices and AI workflows. Many organizations achieve this by creating multiple versions of the same content for different devices, networks and delivery requirements.
Broadcasters may simulcast HD and UHD feeds separately, while streaming and production environments generate additional renditions and proxies for different devices, bandwidth conditions and operational needs.
As video volumes continue to grow, this approach increases storage demands, processing workloads and operational complexity across modern visual systems.
Video now powers far more than traditional media delivery. From streaming platforms and connected devices to AI systems and real-time applications, duplication is becoming an infrastructure challenge rather than simply a media workflow issue.
“
The future of video is not about creating more copies of the same content. It is about making better use of every pixel.
Guido Meardi
CEO, V-Nova
Vision AI
Why it matters
80%
of global data traffic is visual
<1 %
of visual data is analysed by AI
80%
Up to 80% of Visual AI time is data preparation
50%
of Visual AI latency comes from moving data
>10%
of global energy growth driven by AI
70%
Up to 70% of GPU time is spent waiting for data, not processing it.
Why it matters
As video expands across devices, platforms, workflows and AI applications, delivering the right content in the right format becomes increasingly complex.
5–10
Video variants commonly created for a single asset across platforms and workflows
500 hours
Uploaded every minute
1B+
Cameras capturing visual data
15B+
Connected devices handling video
90%
Of AI data is visual
A more adaptable video architecture
Expanding infrastructure is not always practical or economical. Organizations increasingly need to deliver higher quality experiences while making better use of existing bandwidth, processing resources and delivery infrastructure.
As video supports an expanding range of devices, networks and workflows, the way visual information is structured becomes increasingly important.
A hierarchical approach structures visual information so the same video can adapt efficiently across multiple delivery requirements. Rather than creating and managing multiple independent versions of the same asset, organizations can support a wider range of devices, platforms and workflows within a single video architecture.
This provides a more scalable foundation for video delivery across broadcast, streaming, social media and connected systems while remaining compatible with existing codecs and workflows.
Built for modern video delivery
Modern video environments have diverse requirements, spanning broadcast television, streaming platforms, social media distribution, cloud production workflows, connected devices and AI powered applications.
Hierarchical and compute-aware technologies such as MPEG-5 LCEVC and SMPTE VC-6 provide a more efficient foundation for modern video workflows. By structuring, accessing and processing visual information more intelligently, they enable video to adapt efficiently across devices, networks and AI pipelines while remaining compatible with existing ecosystems.
This enables:
- More efficient delivery across devices, networks and platforms
- Faster AI processing and visual analysis workflows
- Reduced duplication across streaming, broadcast and production workflows
- Lower storage, processing and distribution overheads
- Simplified management of large-scale video operations
- Compatibility with existing codecs, delivery infrastructures and workflows
- Greater scalability as video volumes continue to grow.
Video use cases
As video scales across devices, platforms and networks, organizations need more efficient ways to deliver, manage and adapt visual content.
Faster and more accurate AI curation, training and inference on visual content
Accelerate vision workflows multi-fold, sidestep I/O and memory bottlenecks, and enable high-efficiency agentic vision.
Broadcast
Support scalable delivery of live and linear television while reducing operational complexity across modern broadcast workflows.
Pay TV and IPTV
Deliver HD, UHD and next-generation television services efficiently across satellite, cable and IP-based television networks.
Streaming platforms and CDN
Improve video efficiency across OTT services, adaptive streaming environments and content delivery networks.
Social media and UGC
Support delivery across multiple platforms, formats and screen sizes without creating excessive asset variations.
Social media cloud transcoding
LCEVC improves cloud ABR transcoding efficiency for UGC and social video, reducing bitrate, storage, and CDN costs while maintaining quality.
Scalable video messaging
Deliver better-quality video messaging at lower bitrates with LCEVC’s lightweight, backward-compatible enhancement layer.
Live sports and events
Deliver high-quality live video experiences to large audiences across broadcast, streaming and multi-platform environments.
Broadcast
Support scalable delivery of live and linear television while reducing operational complexity across modern broadcast workflows.
Faster and More Accurate AI Curation, Training and Inference on Visual Content
Accelerate vision workflows multi-fold, side-step I/O / memory bottlenecks, and enable high-efficiency agentic vision.
Broadcast
Support scalable delivery of live and linear television while reducing operational complexity across modern broadcast workflows.
Pay TV and IPTV
Deliver HD, UHD and next-generation television services efficiently across satellite, cable and IP-based television networks.
Streaming platforms and CDN
Improve video efficiency across OTT services, adaptive streaming environments and content delivery networks.
Explore Video use cases
As video scales across devices, platforms and networks, organizations need more efficient ways to deliver, manage and adapt visual content.
Accelerate vision workflows multi-fold, side-step I/O / memory bottlenecks, and enable high-efficiency agentic vision.
Support scalable delivery of live and linear television while reducing operational complexity across modern broadcast workflows.
Deliver HD, UHD and next-generation television services efficiently across satellite, cable and IP-based television networks.
Improve video efficiency across OTT services, adaptive streaming environments and content delivery networks.
Support delivery across multiple platforms, formats and screen sizes without creating excessive asset variations.
Deliver high-quality live video experiences to large audiences across broadcast, streaming and multi-platform environments.
Related technologies
These use cases are enabled by V-Nova’s hierarchical and compute-aware visual technologies.
MPEG-5 LCEVC enhances existing codecs with higher efficiency, faster encoding, and lower compute for video and AI workflows.
SMPTE VC-6 structures visual data into a hierarchical format for AI pipelines and next-generation production, enabling native region-of-interest access and level-of-quality decoding.
Related technologies
These use cases are enabled by V-Nova’s hierarchical and compute-aware visual technologies.
Build High-Performance Vision AI Pipelines with NVIDIA CUDA-Accelerated VC-6
Discover how V-Nova’s SMPTE VC-6 accelerates vision AI with NVIDIA CUDA for faster inference, lower latency, and efficient data flow.
Related applications
The same visual infrastructure can solve challenges across multiple industries and applications. Explore how V-Nova’s technologies are transforming AI, industrial systems and immersive experiences.
FAQs
Why do image and video platforms create multiple versions of the same content?
Modern imaging and video workflows must support different devices, networks, resolutions, and workflows. Many organizations achieve this by creating multiple versions of the same content, increasing storage, processing, bandwidth, and operational complexity.
What is a hierarchical data architecture?
V-Nova’s hierarchical encoding architecture structures visual information so the same content can adapt efficiently across different devices, networks, and workflows. Rather than relying on multiple independent versions of the same content, it provides a more scalable foundation for modern video delivery.
How can video be delivered more efficiently across different devices and networks?
More efficient video delivery starts with how visual information is structured and processed. Hierarchical and compute-aware technologies help organizations reduce duplication, optimize delivery, and simplify video workflows while remaining compatible with existing infrastructure.
What is MPEG-5 LCEVC?
MPEG-5 LCEVC is an ISO standardized codec enhancement technology that improves video compression efficiency by encoding high-resolution detail into a distinct, very efficient, data layer. LCEVC enhances existing codecs to deliver higher video quality at lower bitrates while reducing encoding/decoding complexity and remaining compatible with existing video workflows.
What is SMPTE VC-6?
SMPTE VC-6 is a hierarchical, low-complexity image and video coding standard designed for efficient access, processing, and transport of visual data. It supports professional media, cloud production, medical imaging, machine vision, and other compute-aware visual workflows.
How can video infrastructure costs be reduced?
Improving compression efficiency, reducing unnecessary video variants, and simplifying delivery workflows can lower storage, processing, bandwidth, and operational costs while making better use of existing infrastructure.
Where can MPEG-5 LCEVC and SMPTE VC-6 be used?
Together, MPEG-5 LCEVC and SMPTE VC-6 support a wide range of video applications, including broadcast television, pay TV, streaming platforms, cloud production, social media distribution, connected devices, and AI-powered visual systems.
Why is imaging and video infrastructure becoming more complex?
Video must now support more devices, platforms, workflows, and applications than ever before. Growing video volumes, higher resolutions, fragmented device ecosystems, and emerging AI workloads are increasing the complexity of delivering and managing images and video at scale.
