AI lifecycle management — the "Learn" engine in Perceive → Learn → Act
With an AI model, keeping it smart over time is harder than building it. We automate data collection, labeling, training, deployment, and monitoring as one, so on-site staff operate models themselves — no AI experts needed.
Even after a model is deployed, defect patterns on the floor keep changing. Without MLOps, people have to chase every change themselves.
Without a system for collecting and storing inspection images, securing retraining data is difficult.
Relying on outside vendors or manual work consumes excessive time and cost.
Without version control, rollback is difficult — so teams end up avoiding updates altogether.
Without real-time monitoring, defects are noticed only after they have already left the floor.
The dashboard shows which model's performance is slipping and what needs to be trained.
Automatic training on weekends while the factory is idle; deployed before the line starts Monday morning.
Your on-site staff can see, decide, and act — no AI experts required.
It shifts to a subscription-based operating structure that optimizes as data accumulates.
An enterprise solution that manages the entire AI model lifecycle — from data to monitoring — on a single platform.
We solve every challenge of operating AI models.
Trains and deploys models automatically on nights and weekends. Schedule at any time with no production line stoppage; after training completes, models are validated and deployed automatically.
Tracks and manages the history of every AI model. Supports per-model performance comparison, instant rollback to previous versions when problems occur, and training data traceability.
See the AI model performance of your entire factory at a glance on a unified dashboard. Monitor inspection results and performance metrics in real time, with instant alerts on anomaly detection.
Automatically detects model performance degradation. Tracks key metrics such as accuracy and recall, alerts your team when values fall below thresholds, and automatically suggests retraining data.
Automatically label new data with previously trained models, dramatically reducing manual labeling time.
Manage every AI vision solution on the floor — 2D/3D vision, OCR, Cobot inspection, and more — on a single unified platform.
Cognex and Keyence sell vision equipment. EnablerAI delivers the operating system (MLOps) that keeps your models evolving.
| Category | Cognex | Keyence | Domestic SI | EnablerAI ★ |
|---|---|---|---|---|
| Deep Learning | ViDi sold separately | Limited | Outsourced | ✓ Native |
| MLOps | ✕ | ✕ | ✕ | ✓ Built-in |
| Model Version Control | ✕ | ✕ | ✕ | ✓ Automatic |
| Scheduled Training & Deployment | ✕ | Partial | Partial | ✓ Automatic |
| Real-Time Monitoring | ✕ | Partial | Partial | ✓ Full |
| Zero-Teaching | ✕ | ✕ | ✕ | ✓ V2.0 |
MLOps plus 10 years on the manufacturing floor — few teams bring both together.
An SI vendor delivers and walks away; EnablerAI delivers and gets started. The longer it runs, the more factory data accumulates and the more advanced the model becomes.
Field inspection data is collected automatically every cycle.
EnablerAI MLOps manages training and deployment automatically.
Our core MQAI algorithm continuously advances the model.
The entire process is optimized, and the cycle begins again.
Six months in, the system holds data unique to that factory. A competitor coming in would have to start from scratch. Project → Subscription → Recurring Revenue.
Frequently asked questions about EnablerAI MLOps.
An MLOps operating system that turns field data into assets. See the dashboard for yourself in a demo.
