GPU-accelerated, cloud-native monitoring that aggregates broadcast and streaming signal intelligence at scale — hundreds to thousands of concurrent streams, 135+ parameters each, on a single pane. Multi-tenant from the ground up; deploys cloud, VM or on-prem.
Health across hundreds of concurrent streams on one heat-map — worst-first, with no per-site tooling to maintain.
One heat-map to the whole fleet, then click through stream → metric → time range without switching tools.
Aggregate every site into a single view — the same monitoring grammar that runs at the edge, running in the cloud.
VisionCLOUD extends the VisionEDGE engine to cloud streaming infrastructure — GPU-first and cloud-native, monitoring hundreds to thousands of concurrent streams at 135+ parameters each. An adaptive analysis engine applies the right depth of analysis to every stream automatically — from sub-second transport health to per-segment perceptual quality to batch statistical trending.
It is multi-tenant from the ground up with strict per-tenant signal isolation, and deploys however the operation runs — Vela-managed cloud, private data center on Docker and Kubernetes, or hybrid, where a VEDGE–VCLOUD bridge relays on-prem VisionEDGE telemetry into the same console. Elastic auto-scaling adds or removes streams with zero downtime.
GPU-first analysis across transport, perceptual quality and statistics — applied at the depth each stream needs.
Real-time transport health, near-real-time perceptual quality and batch statistical analysis — auto-applied per stream by priority and conditions.
VMAF, SSIM and PSNR on every stream, with compression-artifact detection — blockiness, banding, blur and freeze.
Segment timing, manifest validation, bitrate variance, packet loss, jitter and latency across contribution and adaptive delivery.
Catches degradation before a threshold breaks — auto-baselined trending, cross-stream correlation and failure forecasting.
Hundreds of streams on one screen, worst-first; drill stream → metric → time range in seconds.
Natural-language query across the entire monitoring database — plain-English access to every stream and metric.
Role-based dashboards tailor the same fleet data to NOC, engineering and executive views; customizable dashboards and alert rules, REST API and webhooks throughout.
Deep analysis on every concurrent stream, with the adaptive analysis engine applying the right depth automatically.
Every supported delivery and contribution format ingested into one analysis pipeline.
Named surfaces give each desk the fleet view it needs — from a single heat-map to an executive scorecard.
Aggregate fleet status and KPIs across every tenant and stream group.
Real-time fleet-health visualization across the whole deployment.
Hundreds of streams on one screen, worst-first, click-through to any one.
NOC, engineering and executive views of the same underlying data.
Prioritized queue with routing to PagerDuty, Slack, email, SMS or webhook.
Retained quality and compliance evidence, exportable on schedule or demand.
VelaIQ sits across all of it — natural-language queries giving plain-English access to every stream and metric in the fleet.
Cloud-native containerized microservices — Vela-managed, private or hybrid.
Fits the streaming stack you already run.
VisionCLOUD sits between the station edge and the consumer edge — aggregating the fleet. Each Vision solution stands on its own; together they map the path the signal travels.
Monitoring where the chain begins.
Cloud-scale rollup across the fleet.
Verification at the point of delivery.
Capacity and reliability for fleet-scale streaming — hundreds to thousands of concurrent streams on one platform.
1,000+ concurrent streams at 135+ parameters each, monitored 24/7.
Shares the VisionEDGE monitoring grammar — on-prem and cloud reconciled in one console.
Engagements start with a signal. Point us at a representative set of streams and we run them through the audit pipeline — you see exactly what VisionCLOUD catches, before any commercial conversation.
info@vela.com · (727) 507-5300