Label your data with an offline AI copilot
Vailabel Studio is a local-first desktop studio for image, video, and multi-modal annotation. Detect, segment, and QA your labels with on-device AI — your data never leaves your machine.
- Free & open source
- Windows · macOS · Linux
- No account required
Annotations · 12
Everything you need to label faster
A focused, native annotation studio — not a browser tab. Built for speed, privacy, and real ML workflows.
Every annotation tool
Bounding boxes, polygons, points, lines, circles, free-draw, and SAM smart-segment — each with a single-key shortcut.
Offline AI copilot
Ask it to detect, segment, suggest labels, or QA your work. Local ONNX models, human-in-the-loop, zero cloud calls.
Export anywhere
One click to LabelMe, COCO, YOLO (detection & segmentation), and Pascal VOC — ready for any training pipeline.
Local-first & private
Projects live in a local SQLite database on your machine. Nothing is uploaded unless you choose to.
Bring your own cloud
Optionally connect S3, Azure Blob, or Google Cloud Storage. Credentials are kept in your OS keychain.
Video & multi-modal
Frame-by-frame video labeling with object tracking, plus a multi-modal architecture spanning image, video, text & audio.
An AI that labels with you
A chat copilot that sees the current image and takes labeling actions — running entirely on-device. It proposes; you approve. Nothing leaves your machine.
Detect
“Find all the cars” → bounding boxes from a local YOLO model.
Segment
Click an object → a clean polygon mask via MobileSAM.
Suggest labels
“What should I label here?” → one-click label chips.
QA review
“What did I miss?” → findings you approve or reject.
Fits the stack you already have
From first label to training-ready dataset — without forcing a new format or a cloud account on you.
Project types
Pick a task and the right tools light up.
Export formats
Train with the tools you already use.
Storage
Local by default, cloud when you want it.
See it in action
Watch the AI-assisted annotation workflow end to end.
Shipped, building, and next
An honest view of where the studio is today and where it's headed.
Shipped
Full annotation toolset
Box, polygon, point, line, circle, free-draw
AI copilot
Detect, segment, suggest & QA labels
YOLO + MobileSAM
Local ONNX inference, optional CUDA
Multi-format export
COCO, YOLO, YOLO-Seg, VOC, LabelMe
Cloud storage
S3, Azure Blob & GCS buckets
Video annotation
Frame-by-frame with object tracking
In progress
Florence-2 engine
Captioning, OCR & open-vocab tasks
SAM 2
Higher-quality interactive segmentation
Dataset intelligence
Deeper quality & outlier insights
Conversational copilot
Multi-turn labeling dialogue
Planned
Grounding DINO
Open-vocabulary detection
Text & audio editors
NER, relations, ASR, segments
OCR as a task
First-class text recognition
Team collaboration
Multi-user projects
Frequently asked questions
Everything you need to know about labeling data with Vailabel Studio.
Is Vailabel Studio free and open source?
Yes. Vailabel Studio is a free, open-source data labeling tool. You can download it at no cost for Windows, macOS, and Linux, and the full source code is available on GitHub under a permissive license.
Does it work offline, and is my data private?
Yes. Vailabel Studio is local-first: your images, videos, and annotations are stored on your own machine in a local SQLite database. The AI copilot runs on-device, so labeling works fully offline and your data never leaves your computer unless you choose to sync it to your own cloud bucket.
What types of annotation does it support?
It supports bounding boxes, polygons, points, lines, circles, and free-draw shapes, plus SAM-powered smart segmentation. Beyond images you can label video frame-by-frame and work with multi-modal data including text and audio.
Which export formats can I use to train my models?
You can export datasets to COCO, YOLO, YOLO-Seg, Pascal VOC, and LabelMe JSON — so the labels you create drop straight into the training pipeline you already use.
Is Vailabel Studio a good alternative to Label Studio, CVAT, or Roboflow?
It's a strong alternative if you want a desktop, local-first annotation tool with a built-in offline AI copilot. Unlike browser-based or cloud-hosted tools, Vailabel Studio keeps your data on your machine, requires no account, and runs auto-labeling and QA on-device.
What does the offline AI copilot do?
The copilot uses local models to detect objects, segment masks, suggest labels, and QA your existing annotations — keeping a human in the loop while removing the repetitive work. Because it runs locally there are no cloud calls or per-label costs.
Which platforms does Vailabel Studio run on?
Vailabel Studio is a cross-platform desktop app for Windows, macOS, and Linux. No account or internet connection is required to start labeling.
Start labeling in minutes
Download Vailabel Studio for free and put an offline AI copilot to work on your dataset today.