Overview

Label Studio is a flexible annotation tool for teams preparing machine-learning data across text, images, audio, video, time series, and multimodal projects. It suits practitioners who want to shape their own labeling workflow and connect it to models; the trade-off is that advanced automation and enterprise controls sit above the free community edition.

Its configurable interface, templates, data management, and import and export tools make it useful across varied projects rather than tied to one annotation format. Custom ML backends can supply predictions, and the broad integration range can connect annotation work to storage and machine-learning infrastructure.

Key features

Configurable labeling: Project templates and a configurable interface give teams room to adapt workflows to different data types. For image tasks, annotation options include rectangles, ellipses, keypoints, polygons, brush masks, and image classification.
Model-assisted work: Custom ML backends can provide predictions to support labeling. That is useful when teams want model output alongside annotation, but automated active learning loops are reserved for Enterprise.
Import, export, and integration: Exports include JSON, JSON_MIN, CSV, TSV, COCO, Pascal VOC XML, YOLO, PNG, and NumPy. APIs, a Python SDK, and webhooks support programmatic management; integrations include Amazon S3, Google Cloud Storage, Azure Blob Storage, Databricks, Redis, and local storage, as well as foundation model APIs and ML frameworks.
Deployment and security: Installation options include pip, Docker, Ubuntu, source, and Anaconda, for on-premises or cloud use. The security documentation describes TLS for application component interactions and HTTPS with secured cookies in the web app. Enterprise adds SOC 2 and HIPAA compliance, SAML or LDAP single sign-on, and SCIM 2.0 support.

Pricing

Community Edition — 0.00 USD per free. The open-source edition costs nothing and relies on community support through Slack and GitHub issues. It is the natural starting point for individuals and teams able to manage deployment and support themselves; it does not include the hosted service or Enterprise features.

Starter Cloud — 99.00 USD per month. The hosted service supports up to 12 users and includes a support portal. Each additional user costs $49 per month. This fits teams that want hosting and a defined support channel, though its user cap matters as a team grows.

Enterprise — custom pricing. Cloud or on-premises deployment, SAML or LDAP SSO, priority support with response-time SLAs, and automated active learning loops make this the option for organizations with deployment, identity, compliance, or support requirements beyond the lower tiers.

A free trial is available. Team collaboration and API access are supported, but no additional free-plan usage cap is stated.

Platforms

Label Studio supports API access, Linux, macOS, Windows, self-hosted deployment, and the web. The choice between self-managed installation and hosted Starter Cloud lets teams trade operational control for a managed service.

Who it's for

Choose Label Studio if your annotation work spans several media types, you need configurable workflows or programmatic integration, and you can select between self-hosting and hosted service. It is less compelling for a team seeking automated active learning, enterprise identity controls, or priority support without moving to custom-priced Enterprise.

Pros and cons

Pro: Broad data-type support and multiple image annotation methods suit varied labeling projects without restricting teams to one media type.
Pro: APIs, SDK, webhooks, and storage integrations support integration into an existing data workflow.
Pro: Open-source Community Edition gives technically capable users a free self-hosted route.
Con: Community support is through Slack and GitHub issues, rather than the dedicated portal offered with Starter Cloud.
Con: Automated active learning loops and enterprise identity and compliance capabilities require Enterprise, whose price is custom.
Con: Starter Cloud's 12-user ceiling and $49 monthly charge per additional user can make it less suitable for larger teams.

Alternatives

For a closer comparison, browse Image Annotation Software, AI Image Annotation Tools, Data Labeling Software, AI Data Labeling Tools, and Video Annotation Software.

Roboflow: Consider it when its free tier's 10 monthly credits, described as enough for about 30 model trainings or 80,000 inferences, better match your needs.
CVAT: Its free Community plan is described for personal use and small teams under an MIT license, making it a relevant alternative for that scale.
Labellerr: Its free Researcher plan is aimed at students and researchers, with one seat, one workspace, up to 10 projects, and 2,500 data credits.
Supervisely: Its Community plan provides 5 GB of storage, 10,000 files, and two members, a fit to consider when those stated limits suit the project.
Ultralytics Platform: Its free plan includes 100 GB storage, 10 GB per upload, and 100 models, useful to compare when those caps align with your work.
Pixano: A free alternative.
FiftyOne: A free alternative.
Labelbox: A freemium alternative with a free plan.

Verdict

Label Studio is a strong choice for teams that need adaptable, multi-type annotation and want to connect labeling with their own models and infrastructure. Its free open-source edition keeps entry costs low, but teams that need managed hosting can expect a per-user charge, while active-learning automation and enterprise controls bring custom pricing. Choose it for workflow breadth and deployment choice; look elsewhere if those paid-tier requirements are central and cost certainty is essential.

	Datavyu	Label Studio
Free plan	No	Yes
Free trial	No	Yes
Paid from	—	$99/mo
Open source	No	No
Platforms	Windows, macOS, Linux	api, Linux, macOS, self-hosted, Web, Windows
Free plan	Yes	Yes
Custom labels or fields	Yes	—
Dataset export	Yes	—

Datavyu vs Label Studio

Datavyu

Label Studio