Labelbox
Active learning tools software
Data labeling software
Data science and machine learning platforms
MLOps platforms
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
Take the quiz to check if Labelbox and its alternatives fit your requirements.
Pay-as-you-go
Free Trial unavailable
Free version
Small
Medium
Large
- Information technology and software
- Healthcare and life sciences
- Banking and insurance
What is Labelbox
Labelbox is a data labeling and training data management platform used to create and manage labeled datasets for machine learning. It supports annotation workflows for modalities such as images, video, text, and geospatial data, with tools for quality control and workforce management. The product is used by ML teams and data operations groups to run labeling projects, integrate model-assisted labeling, and manage dataset versions and review processes. It differentiates through an end-to-end labeling workflow that combines annotation tooling, project management, and programmatic integration via APIs/SDKs.
Broad annotation modality support
Labelbox supports multiple data types and common annotation tasks, including computer vision and text-oriented labeling workflows. This helps teams standardize labeling operations across different ML projects without adopting separate tools per modality. It also reduces operational overhead when datasets evolve from one modality to another (e.g., images to video).
Workflow and QA controls
The platform includes review queues, role-based access, and configurable quality processes to manage annotators and reviewers. These controls help teams enforce consistency and track labeling progress across large projects. For organizations running ongoing labeling operations, the built-in project management features reduce reliance on external ticketing or spreadsheet-based tracking.
Model-assisted labeling integration
Labelbox provides mechanisms to incorporate model predictions into labeling workflows to speed up annotation and focus human effort on uncertain or high-value samples. This aligns with active learning-style iteration where labels and models improve together over time. Programmatic access (APIs/SDKs) supports integration into ML pipelines and internal tooling.
Not a full MLOps suite
While it integrates with ML pipelines, Labelbox primarily centers on labeling operations rather than end-to-end model lifecycle management. Teams typically still need separate systems for experiment tracking, feature management, model registry, and deployment orchestration. Buyers evaluating it as an MLOps platform should validate which lifecycle components are covered versus handled by other tools.
Cost and scaling considerations
At high data volumes or with large labeling workforces, total cost can increase due to platform usage and operational requirements. Organizations should model costs across storage, annotation throughput, and review cycles rather than only per-project estimates. Procurement often requires aligning labeling budgets with ongoing model iteration cadence.
Workflow setup requires expertise
Configuring taxonomies, instructions, QA processes, and model-assisted labeling effectively can require experienced data operations and ML input. Poorly designed labeling schemas or review policies can lead to inconsistent labels and rework. Teams may need time to operationalize best practices before realizing efficiency gains.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Free | $0.00 — 500 LBUs free each month | Access to core products (Catalog, Annotate, Model); limits: up to 30 users per organization, up to 50 projects; community support; cannot add data/labels after 500 LBU/month consumed. |
| Starter | $0.10 per LBU (fixed rate) | Usage-based billing at $0.10 per Labelbox Unit (LBU); unlimited users and projects; access to model-assisted labeling and core features; Foundry and other add-ons (inference, labeling services, SSO, HIPAA) incur additional charges. |
| Enterprise | Custom pricing (contact sales) | Unlimited scale and enterprise entitlements (multiple workspaces, advanced security/compliance, dedicated support, SLAs, volume/contract discounts); add-ons and inference fees may apply. |
Seller details
Labelbox, Inc.
San Francisco, CA, USA
2017
Private
https://labelbox.com
https://x.com/labelbox
https://www.linkedin.com/company/labelbox/
