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The foundation of Visylix. A proprietary streaming engine built from scratch with native H.264/H.265 support. Not a wrapper around open-source libraries. Handles 1M+ concurrent connections, 5,000+ streams per node, with less than 2 GB memory per 1,000 streams. Multi-protocol support including GB28181. Full stack cold start in under 60 seconds.
Two ingestion modes to accommodate every camera, encoder, and deployment scenario. Visylix adapts to your infrastructure, not the other way around.
Cameras and encoders push streams directly to Visylix via RTMP, SRT, or WebRTC. Ideal for dynamic environments where devices initiate connections, such as mobile units, drones, and body-worn cameras.
Visylix pulls streams from cameras and NVRs over RTSP or other protocols. Best for fixed installations where the VMS manages the connection lifecycle and camera inventory.
Native support for six streaming protocols. Each protocol is purpose-built for specific latency, reliability, and compatibility requirements.
Industry-standard protocol for IP camera integration. Supports TCP and UDP transport with ONVIF compatibility.
Mature push-based protocol for encoders and broadcast equipment. Persistent TCP connections with low overhead.
Ultra-low-latency peer-to-peer streaming with custom DTLS and SRTP stack. Ideal for real-time monitoring and two-way communication.
Secure, reliable transport over unpredictable networks. AES-128/256 encryption with forward error correction for WAN delivery.
Apple Low-Latency HLS for web and mobile clients. Partial segments and preload hints minimize glass-to-glass delay.
Standard HTTP Live Streaming for maximum compatibility across browsers, smart TVs, and set-top boxes at scale.
China national standard for public safety video surveillance. Full SIP signaling with RTP media transport for government and municipal deployments.
Capture what matters, when it matters. From continuous 24/7 archival to intelligent event-triggered recording.
24/7 recording with configurable retention policies. Frames are written directly from the ingestion pipeline with zero re-encoding overhead.
Define recording windows by day of week, time range, and camera group. Supports recurring and one-time schedules with timezone awareness.
Recording starts and stops based on AI detection events, external API triggers, or sensor input. Pre-event and post-event buffers capture complete context.
Users or API consumers trigger recording manually for specific streams. Supports duration-limited and indefinite capture with real-time status updates.
Choose the right container format for your retention, playback, and distribution requirements.
Standard MPEG-4 Part 14 container for maximum playback compatibility. Moov atom is written progressively to prevent data loss on unexpected shutdown.
Long-term archival, export, and evidence management
Fragmented MP4 with independent segments for instant seek and parallel write. Each fragment is self-contained, enabling efficient cloud storage and CDN distribution.
Cloud-native storage, CDN delivery, and real-time playback
MPEG Transport Stream for high-resilience recording. Self-synchronizing packet structure ensures recoverability even after partial corruption or disk failure.
Critical infrastructure, disaster recovery, and broadcast workflows
Frames flow from ingestion to output without unnecessary memory copies, achieving maximum throughput with minimal CPU overhead.
Frames arrive via RTSP, RTMP, SRT, or WebRTC and are placed into shared memory buffers. No copy occurs during protocol demuxing.
The stream router maps each frame reference to subscribed consumers: recording, AI pipelines, and output protocols. Only pointers are forwarded.
AI models read frames directly from shared memory. Recording writes from the same buffer. No intermediate copies at any stage.
Output protocols (WebRTC, HLS, LL-HLS) read the original frame data for packaging and delivery. The frame is released only when all consumers finish.
A proprietary engine purpose-built for surveillance workloads. Every component is designed for maximum throughput, minimal latency, and predictable resource consumption.
Validated under sustained load testing. The engine scales horizontally across nodes while maintaining sub-second latency for every connected viewer.
Live monitoring via WebRTC delivers glass-to-glass latency under 500 milliseconds, enabling real-time decision-making for security operations.
H.264, H.265 (HEVC), AAC, G.711 (A-law/u-law), G.726, and Opus are processed natively. No external transcoding libraries or FFmpeg dependencies.
A single 8-core server handles 50+ simultaneous 1080p streams. The engine is built for dense deployment on commodity hardware.
Intelligently drops non-reference frames for slow subscribers while preserving keyframes. Viewers on constrained connections still see smooth video.
New viewers receive the latest Group of Pictures immediately. No waiting for the next keyframe, streams start playing within milliseconds of connection.
Detects camera codec capabilities and performs real-time H.265 to H.264 transcoding for browsers without HEVC support. Zero manual configuration.
G.711 and AAC audio are transcoded to Opus for WebRTC delivery with automatic sample rate conversion. Crystal-clear audio on every client.
Monitors CPU load in real-time and gracefully degrades at 70%, 85%, and 95% thresholds. The system never crashes under unexpected load spikes.
Per-stream GOP caches, write buffers, and connection buffers are all bounded to prevent out-of-memory conditions. Predictable resource consumption at scale.
Complete operational visibility from a single pane of glass. Monitor cameras, streams, AI detections, storage, and system health in real-time.
See online, offline, and connecting cameras at a glance. Instant visibility into your entire camera fleet from a single pane of glass.
Real-time viewer count per stream and total active connections across the platform. Know exactly who is watching what, when.
Live recording status with duration tracking and per-stream storage usage. Never lose track of what is being captured.
Real-time detection counts by AI model type. Monitor face recognitions, license plates, safety gear violations, and more as they happen.
CPU, memory, disk, and network throughput displayed in real-time. Full visibility into infrastructure health without leaving the dashboard.
Total used space, available capacity, and retention projections. Plan storage expansions before you run out of space.
Detection trends, viewer counts, and system metrics visualized over time. Spot patterns and anomalies in your surveillance data.
Month-over-month comparison of key metrics. Track growth, identify trends, and generate reports for stakeholders.
Drill into any individual camera for detailed analytics: uptime history, detection events, viewer patterns, and storage consumption.
Deploy, configure, monitor, and update your entire surveillance platform without leaving the browser. Built for operators who value simplicity.
Deploy the entire Visylix platform with a single curl command. From bare metal to fully operational in minutes, not hours.
The installer detects your hardware and automatically tunes database pools, worker threads, buffers, and connection limits for optimal performance.
Update the platform directly from the dashboard. Automatic rollback on failure ensures zero risk during upgrades.
Monitor the health of all internal services from a single view. Immediate alerts when any component requires attention.
Browse, filter, and download logs directly from the dashboard. No SSH access or terminal required for troubleshooting.
One-click download of all system logs with sensitive data automatically redacted. Share with support without security concerns.
The system detects available GPUs and configures AI inference pipelines automatically. Plug in a GPU and the engine uses it.
Database connection pools and worker threads scale dynamically based on CPU utilization. Resources are allocated where they are needed most.
Configurable low-disk alerts with automatic notification. Receive warnings at custom thresholds before storage runs out.
Learn how AI analytics, deployment options, and integration APIs build on top of the VMS Core Engine.