Data feedback
Bring data back from event verification software within AIBox for the next training cycle.
Training data and model versions
Use event review data for training, then evaluate the results to select the next model version.
Automatic annotation
Automatic annotation creates draft labels. Training data versions are published after human review.
Image generation
Generate images for sample preparation. Check their suitability separately from performance on real test data.
Iterative CV and VLM training
Select a published data version and a base model, define a training target, and evaluate results on separate data.
Evaluating the training platform
Teams developing their own models can evaluate the platform directly, or start with event verification and then explore data feedback and training.
See the training workflowDefine before evaluation
- Target model and visual task
- Available data, annotations and generated sample sources
- Training resources, test set and version comparison method
- Model outputs, deployment scope and follow-up services
About training results
Does every training cycle improve performance?
Iterative training aims to refine models. Results depend on the task, data and training setup. Check changes on separate real test data before selecting a version.
How are annotations and generated images selected?
Check relevance and quality for the target task, and define review and data-splitting methods during the pilot.
Product enquiries
Tell us which product you need, your current equipment and the problem you want to solve.