Labelbox / labelbox.com
AI-powered training data platform for creating, managing, and curating labelled datasets with AI-assisted annotation, quality management, and foundation model evaluation for machine learning teams.
Pricing
Free
Free plan
Yes
Category
Developer Tools
Platforms
3
Free plan
Yes
API access
Yes
Open source
No
Platforms
3
Labelbox is the leading AI training data platform providing infrastructure for creating, managing, and curating labelled datasets — the foundation of ML model training. As AI development scales, training data quality and management becomes a critical bottleneck.
AI-assisted labelling uses model predictions to pre-label data that human annotators review and correct — dramatically reducing per-label human time for image segmentation, object detection, and NLP annotation tasks.
Label quality management provides workflows for annotation review, inter-annotator agreement measurement, and label error detection — systematic quality management that determines downstream model accuracy.
Catalog provides searchable, versioned storage for labelled datasets — enabling teams to find, subset, and audit training data across projects. For ML teams with large growing datasets, systematic data management prevents drift and audit failures.
Foundation model evaluation tests how models perform on specific tasks before and after fine-tuning — standardised evaluation frameworks that quantify model quality improvements.
With customers including Databricks, Volvo, and Recursion, Labelbox validates across technology, automotive, and pharmaceutical AI development.
Labelbox AI runs as ml platform software built around image and text workflows. Users typically start with a prompt, upload, or connected data source, and the underlying model handles the heavy lifting before returning a result you can refine or export. It's available on web, python, and api, with API access for teams that want to embed it into their own products.
The capabilities that matter most for teams evaluating Labelbox AI.
Model pre-annotations that humans review and correct — reducing annotation time while maintaining accuracy for image, video, text, and NLP labelling tasks.
Annotation review workflows, inter-annotator agreement measurement, and label error detection — systematic quality assurance ensuring training data that produces accurate ML models.
Image, video, text, audio, and LiDAR labelling in one platform — covering the full range of data modalities required for modern AI model training.
Free plan (5K data rows). Starter $500/month. Business custom. Enterprise custom. 14-day trial.
Model
Freemium
Starting price
Free
Free trial
No
Scale AI (covered) provides enterprise training data at larger scale. Snorkel AI (rank 640) provides programmatic labelling. V7 Labs provides computer vision annotation. Roboflow (covered) provides computer vision dataset management.
A side-by-side look at the closest alternative in this category.
Key facts about model providers, platforms, and team support.
Model Provider
Labelbox
Platforms
Web, Python, API
Deployment
SaaS
Integrations
Google Cloud, AWS, Azure, Databricks, API
Team Collaboration
Yes
Launch Year
2022
Compliance signals and data-handling notes as reported by the vendor.
SOC 2 Type II. ISO 27001. GDPR compliant. HIPAA eligible. Enterprise data handling agreements.
Training data and annotation work processed on Labelbox's infrastructure. Review data handling for sensitive training datasets including personal or proprietary data.
Editorial Verdict
Labelbox is the best AI training data platform for ML teams wanting model-assisted labelling, quality management, and multi-modal training dataset curation across the full range of AI modalities.
Last verified July 24, 2026.
Free plan (5K data rows). Starter $500/month. Business custom. Enterprise custom. 14-day trial.
Enterprise pricing only. Contact sales for custom quotes. Scale Donovan for government and defence is separately priced.
SOC 2 Type II. ISO 27001. GDPR compliant. HIPAA eligible. Enterprise data handling agreements.
SOC 2 Type II certified. Government division operates under appropriate clearance frameworks. Enterprise includes comprehensive security and compliance documentation.
Training data and annotation work processed on Labelbox's infrastructure. Review data handling for sensitive training datasets including personal or proprietary data.
Scale AI processes potentially sensitive training data under enterprise data handling agreements. Review Scale AI's data security documentation for specific compliance requirements.
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