Two flagship AI products — plus deep industry solutions across the sectors that matter most.
AI-Powered Edge Surveillance
See everything. Miss nothing. Intelligent vision that processes at the edge — detecting threats, anomalies, and events in real time, without sending raw video to the cloud.
vSecure transforms standard IP cameras into intelligent edge agents. Instead of recording and uploading footage, the system processes video locally — identifying people, vehicles, objects, and behaviours the moment they appear, triggering alerts and actions in milliseconds. Raw video never leaves the premises.
Perimeter intrusion detection for warehouses, factories, and campuses
Crowd density monitoring and flow analysis in public spaces
Unauthorised access detection in restricted zones
PPE compliance and unsafe behaviour detection on manufacturing floors
Retail footfall analytics and queue management
Real-time object, person, and vehicle detection — no cloud roundtrip
Behaviour recognition — loitering, tailgating, fallen person detection
License plate recognition and vehicle classification (LPR)
Privacy-preserving — raw footage never leaves the premises
Works with existing CCTV via RTSP — no rip-and-replace needed
Distributed AI Fleet Management
One platform. Every edge. Deploy, manage, and orchestrate AI workloads across hundreds of devices — from a single unified control plane, at any scale.
vEdge Orchestrator is Vivega AI's core platform for managing distributed AI deployments at scale. Whether you have 10 devices or 10,000, it handles model deployment, health monitoring, workload scheduling, and over-the-air updates — so your entire edge fleet stays intelligent, current, and fully observable from one place.
Multi-site retail AI — in-store analytics synced across all branches
Industrial IoT — AI inference coordination across factory floor sensors
Smart city infrastructure — traffic cameras, environmental sensors, kiosks
Healthcare — edge AI on medical imaging devices across hospital networks
Telecom edge nodes running inference close to end users
Unified dashboard — monitor all nodes for health, load, and connectivity
OTA model updates with staged rollout, canary testing, and one-click rollback
Intelligent workload scheduling based on compute capacity and priority
Auto failover and self-healing — offline nodes reroute automatically
RBAC, audit logs, and encrypted pipelines for enterprise compliance
Compatible Hardware
Intelligent Licence Plate Recognition
Reads every Indian plate. Misses nothing. An agentic ALPR system purpose-built for India — all state codes, BH series, commercial formats — delivers structured results in milliseconds via any existing IP camera.
vALPR Agent combines a deep-learning vehicle detection engine with an OCR recognition layer and a validation module that cross-checks readings against Indian plate formats and state codes. The agentic layer manages confidence thresholds, triggers re-reads on low-confidence results, and returns structured JSON — plate text, bounding box, confidence score, and alternate candidate readings — ready to plug into access control, toll, parking, or fleet management systems.
Gated community and apartment complex access control
Smart parking — automated entry, exit, and billing
Toll plaza automation and throughput analytics
Fleet management — vehicle in/out logging and reports
Traffic enforcement and stolen vehicle watchlist alerts
Built for Indian plates — all state codes, BH series, commercial and private formats
Handles low light, rain, motion blur, partial occlusion, and angled shots
Confidence score + alternate candidate readings per image
REST API — single endpoint, multipart/form-data, JSON response
Edge deployable — Jetson Nano, x86 server, or cloud VM
End-to-End Computer Vision MLOps
From raw images to deployed models — in one platform. Label datasets, auto-detect with YOLOv8, extract text with OCR, export in any training format, and manage deployments. The full computer vision lifecycle, without the tool sprawl.
Vivega Vision Platform replaces the fragmented workflow of separate labeling tools, training scripts, and model registries. Teams upload raw image datasets, use the canvas-based labeling tool to draw bounding boxes, then let the AI auto-suggest boxes and pre-fill OCR text. Annotated data exports in YOLO, COCO, Pascal VOC, or PaddleOCR format — ready for immediate training. From there, training runs are tracked, models versioned, and deployments managed through the same interface.
Dataset Manager — upload images or ZIP archives, organise into projects
Canvas Labeling Tool — draw bboxes, multi-class, OCR text per box
Auto-Detection — YOLOv8 pre-fills boxes; EasyOCR pre-fills text
Training Pipeline — track experiments, compare runs, version models
Deployment Manager — serve models as APIs, monitor uptime and requests
YOLO — normalised cx cy bw bh, one .txt per image
COCO JSON — single annotations file with pixel coordinates
Pascal VOC XML — one XML per image, classic framework support
PaddleOCR — cropped images + Label.txt + rec_gt.txt for OCR training