Maintain visibility of device, recipe and model versions

VISION AI
VisionOps
Edge deployment, model operations and continual learning — Manages device, recipe, model and deployment versions so approved releases, rollback and performance review can be operated consistently.
P0 · concept validationSeparate approval, deployment and rollback responsibilities
Create an operating feedback loop for error samples and drift
COMPONENTS
Components
- Device registry
- Model and recipe registry
- Deployment policy
- Monitoring and rollback
INTEGRATION
Integration
- Industrial edge nodes
- Quality database
- Identity and access management
- Ticketing system
DELIVERABLES
Deliverables
- Deployment policy
- Device and model asset inventory
- Recovery procedure
- Operations report template
VALIDATION ITEMS
What must be validated before specifications
Performance, specifications and schedule are confirmed only after validating the actual samples and site conditions.
- 01Target device count
- 02Network segmentation
- 03Approval authority
- 04Log retention
- 05Update window
RELATED
Related solutions
Keep existing cameras and equipment while connecting inspection, deployment, data and reporting in one loop.
InspectAI
Low-data hybrid AI visual inspection
Combines rule-based logic and Hybrid AI to validate defect decisions while preserving evidence, dataset lineage and production operating criteria.
Learn more
Fusion3D
2D/3D, thermal and spectral sensor-fusion inspection
Combines complementary sensors to distinguish shape, material and thermal characteristics that a single sensing method cannot reliably separate.
Learn moreDataForge
Synthetic defects, assisted labeling and dataset management
Supports rare-defect development while preserving the source, label, usage rights and training lineage of manufacturing datasets.
Learn moreVisionOps
Validate feasibility with actual samples and site conditions
Product status and specifications are stated in the proposal based on validation and supply conditions.