The Open Hardware-Agnostic Alternative to Hanwha Vision Blaze
Hanwha Vision ties cutting-edge analytics to their proprietary camera hardware and Wisenet WAVE ecosystem. Sentinel delivers high-accuracy multi-camera tracking and trajectory intelligence across any camera brand you already own.
Break free from camera-bound compute limits. Run enterprise-grade foundation vision models across your entire mixed camera fleet.
Sentinel vs Hanwha Vision (Blaze / WAVE) at a Glance
Architectural comparison for defense, homeland security, and mission-critical enterprise teams.
| Capability | SENTINEL | HANWHA VISION (BLAZE / WAVE) |
|---|---|---|
| Camera Independence | ✓100% agnostic: Works with Hanwha, Axis, Bosch, Pelco, Dahua, Hikvision, or generic ONVIF | ✕Advanced AI and Blaze analytics require specific Hanwha Vision camera series or WAVE appliances |
| Compute Power & Model Depth | ✓Server-grade GPU deep learning backbones with high-dimensional feature embeddings | ✕Constrained by low-wattage on-camera SoCs with limited neural capacity and coarse classifications |
| Cross-Camera Spatial Tracking | ✓Native multi-camera persistent re-ID tracking subjects across non-overlapping campus cameras | ✕Primarily single-camera edge detections; limited cross-camera spatial correlation without add-on servers |
| Deployment Flexibility | ✓Containerized edge server, tactical ruggedized node, or sovereign datacenter (100% air-gapped) | ✕Tied to Hanwha appliance firmware ecosystems and Wisenet NVR management structures |
| Continuous AI Updates | ✓Instant model weight updates and retrainable custom classifiers without camera firmware re-flashing | ✕Updates dependent on camera firmware release cycles and hardware SoC obsolescence |
| Integration & VMS Neutrality | ✓Works natively with Milestone, Genetec, Network Optix, Hanwha WAVE, or custom C2 platforms | ✕Optimized primarily for Hanwha Wisenet WAVE with reduced capabilities on third-party VMS platforms |
See Sentinel Live in Action
Watch how Sentinel delivers real-time multi-camera persistent tracking across live streams with sub-second alert dispatch.
Why Operators Are Migrating from Hanwha Vision (Blaze / WAVE) to Sentinel
Server-Grade Deep Learning vs. Constrained On-Camera Chips
Sentinel offloads heavy video inference to dedicated edge GPU servers (NVIDIA RTX / A-Series). This unlocks full-scale deep metric learning models that accurately distinguish targets through rain, shadows, low lighting, and perspective distortion with near-zero false alarms.
Hanwha Blaze and on-camera analytics run on low-power embedded camera chipsets. Due to tight thermal and power limits, on-camera models must compromise on network depth, leading to frequent misclassifications during poor weather or crowded scenes.
Global Multi-Camera Intelligence vs. Single-Lens Silos
A security threat rarely stays in front of one camera. Sentinel correlates feature embeddings across your entire camera topology, building a unified spatial journey of individuals and vehicles across the facility in real time.
On-camera analytics operate in silos: Camera A detects an intruder, but has no innate awareness when that same intruder reappears 30 seconds later on Camera B. Operators must manually trace paths across separate camera logs.
Preserve Your Existing Multi-Vendor Camera Investments
You do not need to replace your existing cameras with new Hanwha units to get world-class AI. Sentinel transforms any existing RTSP/ONVIF camera stream into a state-of-the-art intelligent sensor overnight.
Adopting Hanwha’s latest AI vision features typically requires a capital expenditure cycle to purchase new Hanwha AI-series cameras, driving up project budgets significantly.
Frequently Asked Questions: Sentinel vs Hanwha Vision (Blaze / WAVE)
Can Sentinel ingest feeds from our existing Hanwha cameras?
Yes! Sentinel works exceptionally well with existing Hanwha cameras, ingesting standard RTSP or ONVIF streams and elevating them with multi-camera tracking that goes beyond on-camera firmware capabilities.
Do we need to replace our Wisenet WAVE VMS to use Sentinel?
No. Sentinel operates harmoniously with Hanwha WAVE, Milestone, Genetec, or any standard VMS, pushing real-time metadata, bookmarks, and automated PTZ coordinates directly into your existing video feeds.
What is the advantage of server-side GPU AI over camera-edge AI?
Edge GPU servers can run neural networks that are orders of magnitude larger and more sophisticated than camera chipsets. This yields much higher re-identification accuracy, deeper attribute extraction, and zero performance loss during heavy scene activity.
Is Sentinel 100% compliant with NDAA regulations?
Yes. Sentinel software deploys on NDAA-compliant and TAA-compliant server hardware with zero outbound dependencies, making it suitable for US federal, defence, and critical national infrastructure installations.
Ready to evaluate Sentinel on your camera streams?
Deploy Sentinel on a 30-day sovereign on-premise pilot. Connect up to 50 existing RTSP feeds with zero hardware lock-in.