Image annotation software compared plan by plan

If you are choosing image annotation software for a team, you need two things: a clear list of what you get on each plan, and a way to judge any tool against your own data. This page gives you both. The capability table shows ImageLabeling plan by plan, and the checklist below it works for evaluating any option, including ours.

Label my image See pricing

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Image annotation software capabilities per plan

Every plan is a subscription and the yearly price is half the monthly one. Full terms are on the pricing page.

Capability	Starter	Team	Business	Enterprise
Price per month	49 USD	149 USD	499 USD	1,499 USD
Price per month, billed yearly	24 USD	74 USD	249 USD	749 USD
Seats	3	10	30	unlimited
AI pre-labeled images per month	1,000	3,500	12,000	35,000
Stored images	10,000	100,000	1,000,000	5,000,000
Annotation types	boxes, polygons, points, classes	adds segmentation masks, attributes	adds keypoint skeletons, custom schemas	everything
Dataset versions	3	unlimited	unlimited	unlimited
Review and QA	single reviewer	full workflow, consensus	adds QA score per labeler	same as Business
API and webhooks	none	API	API and webhooks	API and webhooks, higher rate limits
SSO and audit log	none	none	Google and Microsoft SSO, audit log	SAML SSO, audit log, DPA, 99.9 percent uptime SLA, invoicing
Managed labeling	none	none	monthly retainer	monthly retainer, priority matching
Export formats	COCO, YOLO, Pascal VOC, CSV	same	same	same

ImageLabeling compared with the other ways to label images

Most vision teams weigh four options before they pick software. The table compares them on the points that decide cost, quality and control.

Our own vetted annotators work inside your workspace under your QA rules, see data annotation services.

Point	ImageLabeling	Labeling from scratch	Outsourced labeling vendor	Self-hosted open source tool
AI drafts	Boxes, masks and points drawn before a person looks	None, every object is drawn by hand	Depends on the vendor and is rarely visible to you	Possible after you set up and host a model yourself
QA trail	Who labeled, who approved and what changed, on every image	Whatever your team records by hand	Vendor reports, rarely per image	Basic review, an audit trail is up to you
Exports	COCO, YOLO, Pascal VOC and CSV on every plan	Whatever your own scripts write	Agreed per project	Common formats, often with plugins and scripts
Cost model	Flat monthly plan from 24 USD billed yearly	Labeler hours only	Price per image or per hour, quoted per project	Free license, paid in servers and engineer time
Data control	Images label your dataset only and never train third party models, export anytime	Full	Images leave your company for the vendor's workforce	Full, on your own servers

What to look for when choosing image annotation software

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A short trial on real images tells you more than any feature list. Before you commit, check these points with a batch from your own dataset.

Export that loads into your training code without a conversion script. Test COCO or YOLO on day one.
Import of the labels you already have, so earlier work is not lost.
AI drafts for your own classes, with confidence per object, so reviewers can focus.
A review step with comments, not just a status flag.
Dataset versions that freeze, compare and keep a stable split.
Pricing you can predict. Flat monthly plans are easier to budget than credits or per click meters.
Data terms in writing. Your images should not train someone else's models.

Costs that do not show on a pricing page

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The license is rarely the largest line. The larger ones are labeler hours, relabeling after a bad batch, and engineer time spent converting formats. Software that drafts labels well cuts labeler hours. Software with real review cuts relabeling. Software that exports clean COCO JSON or YOLO txt with data.yaml removes conversion work. Ask about each of these before comparing prices. Our reasoning on cost per labeled image is on the data annotation platform page.

Matching a plan to your team

Starter suits one ML engineer with a focused detection project. Team suits a startup vision team that needs masks, consensus and the API. Business suits a company with an in-house labeling team that needs QA scores, webhooks, SSO and an audit log. Enterprise suits large or regulated data programs that need SAML SSO, a DPA, an uptime SLA and invoicing. If your volume grows, moving up a plan is charged right away for the difference.

Where to read more before you decide

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Each capability in the table has a detailed page. Export behavior is explained on the YOLO labeling tool and COCO annotation tool pages, the editor on the image labeling tool page, and engineering features such as the API and versions on the computer vision annotation tool page.

FAQ

Is there a trial of the image annotation software?

There is a free demo on the homepage: upload one image and see AI labels drawn on it in the real editor layout. Plans start at 24 USD per month billed yearly.

Can we switch plans later?

Yes. Moving up is charged right away for the difference. You can cancel anytime and access runs to the end of the paid period.

Does every plan export to the same formats?

Yes. COCO JSON, YOLO txt with data.yaml, Pascal VOC XML and CSV are on every plan.

Is manual labeling limited?

Manual labeling is not metered. You label as much as your stored image limit allows, and only AI pre-labels count toward the monthly AI quota.

Test it on a batch from your own dataset

Create your account, upload a batch and run the checklist above against real results.