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LabelOp logoLabelOp

Annotation workflows
for teams shipping
vision models.

Upload, annotate, review, and export computer vision datasets
in one workspace.

Start freeSee pricing

No credit card required.

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How It Works

One workflow from upload to export.

Upload, label, review, export, and train without breaking the flow.

Workflow map

No handoffs between tools.

Upload

Bring media into one queue.

Validate & Split

Check structure and prep the split.

AI & Manual Labeling

Pre-label, then refine by hand.

Review

Approve before release.

Export

Package the dataset.

Train

Launch the next run.

Core Capabilities

Label, review, and ship from one place

AI Pre-label & Human Loop

Speed

Models pre-label in under a second; your team reviews each result.

Universal Format Export

Formats

Export to COCO, YOLO, Pascal VOC, LabelMe, CVAT, CSV, and JSONL.

Local & Cloud Inference

AI Engine

Run SAM2 segmentations in the browser, or connect managed GPU models.

Team Roles & QA Queues

Collaboration

Assign batch queues, set member permissions, and track live team stats.

Immutable Versioning

Control

Snapshot dataset states, freeze release tags, and keep full audit logs.

Platform features

Feature overview

Annotation workspace

Open any project image and annotate without leaving the review workflow.

  • Canvas, toolbar, gallery, and side panel stay together
  • Boxes, points, polygons, and SAM2 use the same workspace
  • Labels and saved annotations stay visible while labeling
  • Undo, redo, filters, and image navigation work on the same canvas
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Start free today.

Free Tier

Free Tier

$0forever

A managed hosted tier for individuals and small evaluations

Get started free
All features and limits
3 team members · 2 projects
10,000 images · 5 GB managed storage per project
Managed AI-assisted labeling: 500 runs per day
Unlimited local AI-assisted labeling
Unlimited review workflows
Unlimited export formats
3 version snapshots per project

Pro + optional packages

Pro

Coming soon
$49/month + tax

Higher managed limits with optional people and project packages

All features and limits
10 team members · 10 projects
20,000 images · 100 GB managed storage per project
Managed AI-assisted labeling: 25,000 runs per day
Unlimited local AI-assisted labeling
Unlimited review workflows
Unlimited export formats
Optional people and project packages
Add capacity only when you need it. Increases are immediate and prorated; decreases take effect next period after usage checks.
Compare Free Tier and Pro

Common questions, straight answers.

Which AI models are supported for batch labeling?

LabelOp supports managed cloud models and local offline models (such as SAM2) for pre-labeling. Run inference across a full dataset or an image range, with progress tracking and confidence controls.

How do I assign annotation tasks to team members?

Create assignments for single images or ranges, set priority (low, medium, high, urgent), add due dates and instructions, and track completion. Assignees see their tasks in a queue with status, priority, and project filters. Owners and reviewers monitor progress, view annotator metrics, and reassign work. Every annotation links to its assignment.

How does collaboration and review work?

Invite teammates with owner, reviewer, or annotator roles, assign tasks, and filter queues by status, split, or assignee. When email delivery is configured, the service emails the invitation; otherwise the owner shares the generated invitation link manually. Audit logs and review workflows keep quality checks traceable.

Can I train custom models using GPU compute?

Yes, by connecting your own Vast.ai account. LabelOp helps browse offers and monitor jobs, but does not provide or resell the GPU. Vast.ai terms, availability, quota, and charges apply to the project owner's credential.

Can I audit dataset versions and roll back changes?

Create named dataset version snapshots from the project team area, compare two versions to see what changed, and use audit logs for traceability. Snapshots capture annotation state so you can align training releases with a specific checkpoint.

What export formats and integrations do you support?

Export to COCO JSON, YOLO, Pascal VOC XML, LabelMe JSON, CSV, TSV, CVAT XML, or JSONL in a single click. Exports preserve annotation metadata, confidence scores, and creator information. You can filter exports by label, split, annotator, or date range.

Is my data private and secure?

The hosted service uses access controls, encrypted transport, and encrypted saved provider credentials. No system can promise absolute security. Browser-side models can reduce third-party transfer, but you remain responsible for your device, storage provider, sharing settings, and backups.

How does LabelOp handle large datasets?

Capacity depends on hosted platform guardrails, browser memory, and database limits. Free Tier and Pro publish concrete limits; optional Pro packages expand people or projects without changing import, annotation, file-safety, rate, or abuse limits.

Does LabelOp fund GPU usage?

No. LabelOp does not currently fund or resell GPU usage. You can connect a Vast.ai account and control provider-side budgets and limits yourself.