Vision AI spots damage and defects, and AOI re-checks cut false rejects for consistent quality.
AIWinOps Patented Vision AI Platform
Turn image data
into production-ready
vision AI
Annotate images, train models and deploy vision AI.
Manage every site from one platform.
Peak detection rate95%+
Annotation timeCut by up to90%
Deployment timeShortened by up to80%
* Actual results vary with data quality, model, and application environment.
AIWinOpsLIVE VISION WORKSPACE
WHY AIWinOps
Why Enterprises Choose AIWinOps
Prepare data, train models and manage deployment in one visual workspace.
VISUAL AI
Five AI Vision Tasks
Vision AI for a wide range of applications
Build classification, detection, segmentation and anomaly models in one place.
Classify ImagesImage Classification
Classify images and manage labels automatically.
Detect ObjectsObject Detection
Locate target objects precisely and identify their position and count in real time.
Segment ImagesImage Segmentation
Separate image regions in fine detail for more accurate contours and features.
Detect AnomaliesAnomaly Detection
Train on a small set of normal samples to find anomalies and defects automatically.
Generate DefectsDefect Generation
Generate more defect samples with AI to speed up model training and tuning.
USE CASES
Where AI Vision Fits in Your Operations
See AI vision at work in quality, safety and production.
Panel & Part Defects
Vision AI spots damage and defects, and AOI re-checks cut false rejects for consistent quality.
Detect missing PPE and restricted-area entry in real time to reduce safety incidents.
Recognize work steps and operator actions, and flag anomalies or missed steps in real time.
AI license plate recognition and traffic analysis show parking status and vehicle movement in real time.
Spot fabric defects and broken yarns in real time to keep defective goods from shipping and raise quality.
Detect rot, mold and bruising automatically to improve food quality and inspection efficiency.
CAPABILITIES
Advanced Features That Speed Up Model Building
Build better models with auto-annotation, defect generation and image search.
Smart Annotation
Six auto-annotation modes speed up labeling, from segmentation to video tracking.
Improve datasets with preprocessing, augmentation and generated defects.
Train and evaluate vision models without code.
Search images by similarity and retrieve matches by API.
Manage versions, deploy models and run batch inference.
AIWinOps WORKFLOW
From Data to Deployed Model with AIWinOps
Move from data preparation to a trained model in one workflow.
- 01Project Setup
Create a project and choose its vision task: classification, detection, segmentation or anomaly detection.Project Setup - Data Processing
- Data Annotation
- Model Training
- Model Validation
- Model Deployment
INTEGRATION
Putting AI Vision to Work on Site
AIWinOps × WinEdge
Connect image sources, models and on-site applications.
Industrial CamerasAOI EquipmentIPC CamerasImage Archives
Data Preparation
AI Auto-AnnotationData PreprocessingData Augmentation
Model Development
Image ClassificationObject DetectionImage SegmentationAnomaly DetectionDefect Generation
Model Management
Training & ValidationPerformance EvaluationVersion ManagementTeam Collaboration
Image Retrieval
Image DatabaseSearch by ImageBatch RetrievalAPI Service
Edge DeploymentReal-Time InferenceDevice IntegrationMulti-Site ControlData Backhaul / Live Monitoring
Defect InspectionSize MeasurementPart RecognitionSafety MonitoringProcess Monitoring
01
Vision Data Sources
Industrial Cameras
AOI Equipment
IPC Cameras
Image Archives
02
AIWinOpsVision AI Training Platform
Data Preparation
- AI Auto-Annotation
- Data Preprocessing
- Data Augmentation
Model Development
- Image Classification
- Object Detection
- Image Segmentation
- Anomaly Detection
- Defect Generation
Model Management
- Training & Validation
- Performance Evaluation
- Version Management
- Team Collaboration
Image Retrieval
- Image Database
- Search by Image
- Batch Retrieval
- API Service
03
WinEdgeReal-Time Edge Inference Platform
Edge Deployment
Real-Time Inference
Device Integration
Multi-Site Control
Data Backhaul / Live Monitoring
04
On-Site Applications
Defect Inspection
Size Measurement
Part Recognition
Safety Monitoring
Process Monitoring
DEPLOYMENT
On-Premises Architecture and Requirements
100% on-premises, with full control of your data and computing power
Software requirements
| Item | Version |
|---|---|
| Operating System | Ubuntu 22.04 LTS (64-bit) or later |
| NVIDIA GPU Driver | 535.154.05 or later |
| Docker Engine - Community | 20.10.17 or later |
Deployment architecture
- Flexible on-premises / private cloud deployment
- Data stays 100% on-site, under your control
- Multi-user collaboration and access control
- Hardware resource scheduling and quota management
Hardware requirements
| Item | Minimum | Recommended |
|---|---|---|
| CPU | 12-core Intel® Core™ i7-12700 processor | 20 cores / 40 threads or more, 2 × Intel® Xeon® Silver 4210 processors |
| GPU | NVIDIA GPU, 12GB VRAM, CUDA Compute Capability 7.5 | NVIDIA GPU, 16GB VRAM or more, CUDA Compute Capability 7.5 or higher |
| Memory | 64GB | 128GB or more |
| Storage | 512GB SSD + 1TB HDD | 1TB SSD + 4TB HDD or more |
| Ports | USB 2.0 / 3.0 (for security dongle) | |
Recommended compatible hardware
PRICING
Licensing Options That Fit Your Deployment
Choose the licensing model that fits your use case and budget.
Perpetual Plan
- Perpetual license
- Full GPU server configuration
- Private cloud / on-premises deployment
- Full control of your data
- Lifetime technical support
Best forLong-term use, sensitive data
Annual Plan
- Annual license
- Full GPU server configuration
- Private cloud / on-premises deployment
- Regular system updates
- Annual technical support
Best forFlexible budgets, phased needs
Annual Model Plan
- Annual license
- Full GPU server configuration
- Private cloud / on-premises deployment
- Includes SDK and API (licensed per computer)
Best forFlexible budgets, phased needs