See Everything. Miss Nothing.
ATLAS Vision deploys RT-DETR object detection, SAM segmentation, and DINO open-vocabulary grounding on your existing camera infrastructure — all running on-premises at vision.llewellynsystems.com. Your cameras start understanding what they see.
The Surveillance Paradox
$350 billion spent on cameras. Most of them are just recording, not understanding.
The average enterprise has hundreds of cameras generating terabytes of footage that humans will never review. The threat has already passed before anyone looks. The shoplifter has left. The quality defect has shipped. ATLAS Vision turns passive recording infrastructure into active intelligence — in real time.
Global video surveillance market
Projected 2026 market size
$350B+
Average review rate of recorded footage
Incidents caught in real time vs. post-hoc
<1%
Amazon Rekognition video analysis (per minute)
Adds up fast at scale — plus data sovereignty risk
$0.10/min
ATLAS Vision model
On-premises, no per-call billing, no cloud dependency
Flat rate
What ATLAS Vision Does
Six Vision Capabilities. One Platform.
Running on M4:9550. Production URL: vision.llewellynsystems.com. No waitlist.
Real-Time Object Detection
RT-DETR — Transformer-Based, Sub-100ms
RT-DETR (Real-Time Detection Transformer) runs on every frame with transformer-based precision. Unlike YOLO-family detectors, RT-DETR processes the full scene context before making predictions — dramatically reducing false positives in cluttered environments like retail floors, manufacturing lines, and multi-camera security arrays.
Semantic Segmentation
SAM — Segment Anything Model
Segment Anything Model (SAM) provides pixel-precise object boundaries — not just bounding boxes. When you need to know exactly where an object ends and the background begins — for inventory counting, quality inspection, or incident zone delineation — SAM delivers the precision that detection-only models cannot.
Open-Vocabulary Grounding
DINO — Describe What You Want to Find
DINO (Detection with Transformers) enables open-vocabulary detection — instead of detecting from a fixed class list, operators describe what they are looking for in natural language. No retraining. No model update. 'Person carrying a red bag near exit 3' surfaces immediately.
Face Recognition
Identity Matching Across Camera Networks
ATLAS Vision performs face recognition across multi-camera environments — matching identities against enrolled watch lists, authorized personnel databases, or known persons of interest registries. All processing happens on-premises. No biometric data transits to cloud providers.
Threat & Anomaly Detection
Behavioral Analysis Beyond Object Classes
Beyond detecting what an object is, ATLAS Vision detects what it is doing. Loitering detection, perimeter breach sequencing, crowd density escalation, and abandoned object alerts are all configured as behavioral rules — not just static presence checks.
Multi-Camera HUD
7-Node Datacenter — Unified Command View
A unified command HUD aggregates feeds from across your camera network, with per-feed detection overlays, alert queues, and scene snapshots — all routed through the 7-node Llewellyn Systems datacenter. No third-party cloud VMS required.
The Workflow
How It Works
Three steps. Existing cameras. Real-time intelligence.
Step 01
Connect
ATLAS Vision connects to existing RTSP camera streams over your network. No hardware replacement required. ONVIF-compatible cameras, IP cameras, and NVR outputs all work. The vision pipeline connects to what you already have.
Step 02
Detect
RT-DETR processes each frame in real time. SAM segments objects on demand. DINO grounds open-vocabulary queries against the live scene. Face recognition runs against enrolled databases simultaneously. All models execute on the M4 at port 9550.
Step 03
Act
Detections trigger configurable actions — webhook alerts, dashboard notifications, recording marks, access control signals, or API callbacks to your existing security or operations platform. Every detection is timestamped and logged.
Vision Stack — Running on M4 at Port 9550
RT-DETR
Object Detection
Transformer-based. Full scene context. Sub-100ms inference. 80-class COCO baseline + custom fine-tuned classes.
SAM
Segmentation
Segment Anything Model. Pixel-precise boundaries on any object, any scene. Zero-shot — no class list required.
DINO
Open-Vocab Grounding
Grounding DINO. Natural language queries against live camera feeds. Describe the anomaly, DINO finds it.
Competitive Analysis
ATLAS Vision vs. The Market
Every row is a factual comparison. No marketing language.
| Feature | ATLAS Vision | AWS Rekognition | Google Vision AI | Azure Computer Vision |
|---|---|---|---|---|
| Monthly Cost | Flat-rate seat | Per-image / per-min billing | Per-request billing | Per-request billing |
| Object Detection Model | RT-DETR (transformer) | Proprietary CNN | Proprietary CNN | Proprietary CNN |
| Semantic Segmentation | SAM (Segment Anything) | Limited | Limited | Limited |
| Open-Vocabulary Detection | Yes — DINO grounding | No — fixed classes | Partial | No — fixed classes |
| Data Sovereignty | 100% on-premises | AWS cloud only | Google cloud only | Azure cloud only |
| Real-Time RTSP Stream Support | Yes — native | Kinesis Video Streams required | No native streaming | Limited streaming |
| Biometric Data Handling | On-premises — never transmitted | AWS infrastructure | Google infrastructure | Azure infrastructure |
| Multi-Camera HUD | Yes — unified command view | No native HUD | No native HUD | No native HUD |
Cloud pricing data current as of Q1 2026 based on published rate cards. ATLAS Vision pricing reflects flat-rate on-premises deployment.
RT-DETR
Detection Model
Transformer-based, full scene context
7-Node
Datacenter Backbone
M4 + DL360 + 5 supporting nodes
100%
On-Premises Processing
No biometric data leaves your perimeter
3
Vision Architectures
RT-DETR + SAM + DINO running simultaneously
Biometric Data Never Leaves
Face templates, recognition matches, and identity logs are stored and processed on Llewellyn Systems infrastructure. Nothing is transmitted to AWS, Google, Microsoft, or any third-party cloud. This satisfies BIPA, CCPA, and emerging state-level biometric regulation.
Edge Deployment on 7-Node Datacenter
ATLAS Vision runs across a 7-node infrastructure: M4 as the primary inference server, DL360 for heavy segmentation workloads, and five supporting nodes for redundancy and load distribution. No single point of failure. No cloud dependency.
Detection Audit Logs
Every detection event, alert trigger, and operator action is timestamped and logged with session IDs. Available for physical security incident review, insurance claims, regulatory audits, and chain-of-custody documentation.
Get Access
Your Cameras Are Already There. Make Them Intelligent.
The live interface is running now at vision.llewellynsystems.com. Open it and see RT-DETR, SAM, and DINO processing a live feed in real time — no demo request required. For enterprise deployment discussions, contact us directly.
No account required for the live demo. Enterprise deployments include on-site integration support.
Frequently Asked Questions