Tools that stay out of the way
Polygon, box, point, and classification workflows share one editor. Predictable shortcuts, clear object history, no mode surprises.
Label it right.
Ship it faster.
Synthmark keeps annotation, review, and export in one disciplined workspace — so training data doesn't pile up before it reaches the model.
4export formats
99.9%uptime SLA
<50mscanvas response
What's different
Built for the work, not the demo.
Interface density that holds up over long sessions. Every state is visible — nothing hides in a dropdown.
Review built into the dataset
Queue assignments, compare label versions, and keep acceptance criteria visible before work reaches training.
Exports your pipeline can use
COCO, YOLO, VOC, and custom JSON mappings shaped for training jobs — not one-off hand cleanup.
Made for production teams
Role controls, project activity, and performance views make it easier to coordinate labelers, reviewers, and ML leads.
How it works
Raw frames to training data. Four steps.
Each step has clear ownership, a review gate, and an audit trail that survives handoffs between labelers and ML engineers.
01
Import
Upload image batches and define label schemas in one step.
02
Assign
Route work to specialist labelers with clear instructions attached.
03
Review
Compare revisions, flag edge cases, and approve with context.
04
Export
Pull versioned, format-ready datasets directly into training runs.
42%
less correction time
for labeling teams
3.8×
review throughput
for QA leads
4
export formats
out of the box
0
format rewrites
before training
Annotation velocity only matters if the output is actually usable. Synthmark ties speed to quality with review gates at every stage.
Who it's for
One workspace. Everyone on the dataset.
Labeling Teams
Fast keyboard-led tools, visible instructions, and fewer mode surprises during long sessions.
42%
less correction time
Review Leads
Spot drift, compare revisions, and send focused feedback without leaving the project view.
3.8×
review throughput
ML Engineers
Traceable versions, clean exports, and dataset metrics that make training runs easier to explain.
0
format rewrites
Pricing
Start small. Scale when ready.
Priced around projects and collaborators — not vague API call quotas.
Pro
$28/user/month
For small teams that want private projects and review-ready exports.
- 10 projects
- 10,000 images per project
- All export formats (COCO, YOLO, VOC, JSON)
- Review queues & version history
- Email support
Team
$89/user/month
For production teams with compliance and scale needs.
- Unlimited projects & images
- Role-based access control
- Custom export templates
- SSO & audit logs
- Priority support & SLA
Want to inspect the workflow first? Open the real editor tryout →
Can Synthmark handle polygon segmentation and boxes in the same project?
Yes. Projects can combine annotation types with shared classes, attributes, review status, and export rules.
Does the platform include AI-assisted labeling?
Yes, but it is treated as an assistant inside a controlled workflow. Review states and human edits remain first-class.
Which export formats are supported?
Synthmark supports COCO, YOLO, VOC, and custom JSON exports for teams with internal training pipelines.
How does the review workflow work?
Each image has a status — pending, in review, or approved. Reviewers can compare annotation versions side by side and leave structured feedback before approval.
Your first project is ready in minutes.
Full annotation tools, review workflows, and ML-ready exports priced below common private-data annotation plans.