Anastig Studio · private preview

The dataset-to-model workspace for visual AI.

Anastig Studio brings together datasets, annotation, preprocessing, augmentation, export, and model orchestration in one workspace. Annotation is only one module.

Studio modules

Everything from image to inference.

Each module is independent. Start with annotation and export; connect training workers and deployment later.

Beta

Dataset Manager

Upload, version, tag, split, and manage your visual AI datasets.

Open module
Available

Annotation Studio

Bounding boxes, classification, keypoints, and polygon annotation.

Open module
Beta

Preprocessing

Resize, crop, grayscale, tile, and pad your images for training.

Open module
Beta

Augmentation

Configure flips, rotations, blur, noise, and mosaic augmentation.

Open module
Available

Export Center

Export YOLO, COCO JSON, classification CSV, and dataset.yaml.

Open module
Coming soon

Training

Connect GPU workers and launch model training jobs.

On the roadmap
Coming soon

Deployment

Deploy to APIs, edge devices, Docker, and embedded hardware.

On the roadmap
Coming soon

Evaluation

mAP, precision/recall, confusion matrices, and model comparison.

On the roadmap
Coming soon

Workflows

Build multi-step visual AI pipelines with a visual canvas.

On the roadmap
Design principles

Built to stay out of your way.

Canvas work stays in the browser

Annotation, export, validation, and label operations run entirely in your browser. No server round-trips while you draw.

GPU stays external

Training and inference never run on the web server. Connect your own GPU workers or use cloud workers when ready.

Data stays in your boundary

Images stay in your browser in demo mode. In production, your data lives in your tenant and is never used to train shared models.

Start with annotation. Scale from there.

Open the demo to annotate your own images now, or request a pilot to scope a complete dataset-to-model workflow.