Introducing Human-in-the-loop Evaluation for Agentic AI Observability →
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Explore Label Studio Enterprise

Build models you can trust, faster

Label Studio Enterprise is designed for data science teams running ML/AI models in production, when quality and compliance are paramount.

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Trusted by the world's largest data science teams

Label Studio Enterprise trace review interface
LABEL STUDIO ENTERPRISE

The evaluation platform
for AI systems

Teams continually improving AI models need an operations platform around Label Studio. The sustained engineering investment required competes with the work of actually shipping models.

Label Studio Enterprise is the full platform: already built, already proven, and fully supported.

Data Models Humans
Full enterprise platform Open source version
Security
SOC 2 Type IIHIPAAOn-prem99.99% SLAActivity logs
TODO: Security

How do you connect securely and maintain compliance?

Automation
VersioningTestingCredentialsRoutingGuardrailsLineage
TODO: Automation

How can you integrate model annotations at scale with versioning, credentials, etc?

new Interface Agent
TODO: Coding interfaces
Label Studio
Quality Control
ReviewsAgreementGold tasks
TODO: Quality Assurance

When models and/or annotators disagree, how do you escalate for further review?

Access controls & auditing
SSORBACWorkspacesAudit log
TODO: Auth & Roles

Label Studio only has admin users. You need roles, permissions, and auditing.

Platform
DashboardsSnapshotsPerformanceModel tracking
TODO: Platform Ops, Upgrades, & Support

You manage infrastructure, upgrades, and operations on your own.

Support
SLAsEarly accessOnboarding
01

Quality control

Annotation quality is the single biggest determinant of model quality. OSS treats labeling as a single step; Enterprise treats it as a workflow.

  • Review workflows A structured annotator → reviewer → lead pipeline with approval steps.
  • Inter-annotator agreement scoring Cohen's kappa, agreement matrices, and consensus tooling are built in. (In OSS, you export and compute these yourself.)
  • Ground truth and benchmarks Designate gold tasks and measure annotator accuracy against them.
  • Consensus and adjudication Resolve disagreements without leaving Label Studio. (OSS supports overlapping annotations but doesn't offer workflows for resolving them.)
02

Team and access controls

OSS effectively treats every user as an admin. Label Studio Enterprise brings the RBAC needed for larger projects, especially with contractors or vendors are involved.

  • SSO Via SAML and OIDC.
  • Role-based access control A full set of roles for annotator, reviewer, manager, and admin with permissions tied to each role. Any role can be customized and you can also add new roles.
  • Project- and workspace-scoped access So internal and external users see only what they should.
  • Per-user task assignment and queues Rather than a shared task list.
  • Audit trail Keep track of who changed what and when (required for governed datasets).
03

Advanced automation to accelerate AI development

Using the Label Studio ML backend, you can stand up a Python services, wire any LLM or model, and surface predictions as pre-annotations.

But what happens after the first auto-labeling loop? Label Studio Enterprise turns all those connection points into a robust, managed system:

  • Prompts as a versioned, evaluable artifact Author and run prompts in the UI, evaluate against ground truth, A/B test, and manage provider credentials centrally rather than as env vars on someone's laptop.
  • Bulk prediction as a job Run a model across tens of thousands of tasks as a managed run with progress, retries, and results, not a script someone has to babysit.
  • Confidence-aware routing Automatically send low-confidence or high-disagreement predictions to human review and accept high-confidence ones over a threshold. The "smart queues" idea, actually wired up.
  • Guardrails on LLM output Schema validation against your labeling config, with retry and fallback when output doesn't conform.
  • Lineage and versioning Which model version and prompt produced which prediction, tracked over time.
  • Active learning loop closure Orchestration of who reviews next, when to retrain, and how to measure the lift.
04

End-to-end visibility into the work and the model

OSS shows you tasks. Enterprise shows you the program around the tasks.

  • Dashboards For throughput, agreement, reviewer activity, and project health.
  • Model performance tracking Against ground truth across versions, so "v2 regressed on this slice" is a query rather than a side project.
  • Snapshots That freeze a point-in-time view of labels and predictions for reproducibility and audits.
05

Security, compliance, and operations

We've engineered the hosted and on-prem versions of Label Studio Enterprise to meet demanding standards for data governance and security.

SOC 2 Type II Certified
HIPAA Certified
  • On-premises deployment available Option for teams that cannot send data to a vendor cloud.
  • 99.99% uptime SLA On the hosted offering.
  • Activity logs Suitable for compliance review.
  • Dedicated support With response SLAs, plus the fastest access to new features and fixes.
  • Performance at scale Data Manager and storage layers tuned for projects where OSS becomes sluggish.
Making the right choice

Should your team consider Label Studio Enterprise?

Label Studio will always be free and open source software. We even offer a hosted Starter version. But your team should consider Enterprise if:

  • Your data has compliance constraints (HIPAA, SOC 2) or has to live in regulated environments.
  • You have a larger team that includes vendors, contractors, or external annotators
  • You're past prototyping and ready to scale labeling and modeling to production volumes.
  • You'd rather ship models than build and maintain the surrounding tooling yourself.
See the full comparison

There's a version of Label Studio perfect for your team and projects.

A complete feature-by-feature breakdown lives on the pricing page.

Talk to us about Enterprise → Compare editions
FAQ

Frequently asked questions

Can we deploy Label Studio Enterprise in our own environment?
Yes. Enterprise is available as a managed cloud offering and as an on-premises deployment for teams that need to keep data inside their own infrastructure. The on-prem option is common in regulated industries and air-gapped environments.
We're already running the open source version. How hard is it to migrate?
Projects, labeling configurations, and annotated data move over without re-labeling. Most of the migration work is around mapping users into roles and workspaces — which is a new capability rather than a conversion. Our team helps plan and execute the migration as part of onboarding.
Can't we just build auto-labeling and review workflows on top of OSS ourselves?
You can build a lot of it. Teams routinely wire up an ML backend, sort the Data Manager by confidence metadata, and stand up basic review by convention. What's harder to replicate is the managed layer: prompt versioning and evaluation, confidence-aware routing, lineage tracking, agreement metrics, and the audit trail. That's where DIY tends to either stall or turn into a long-term internal platform project.
Are HIPAA and SOC 2 covered by default?
Enterprise is SOC 2 Type II certified and supports HIPAA workflows. Specific configuration and a Business Associate Agreement (BAA) are part of the onboarding process for HIPAA customers. The open source version makes no compliance claims.
How does pricing work?
Enterprise pricing is based on team size and deployment model. Visit the pricing page for the detailed comparison table and to start a conversation.