• Labelbox is a data platform for AI teams, offering software and services for training data pipelines.
• It features tools for annotation, ontology management, model evaluation, and workflow automation.
• The platform utilizes a global network of domain experts, known as Alignerrs, for on-demand labeling and evaluation.
• Supports various data types including images, video, audio, text, and geospatial data.
• Enables tasks such as AI-assisted foundation model pre-labeling and human-centered evaluations.
• Provides stringent quality control methods, including rubrics, consensus, and benchmarking.
• Offers performance tracking through leaderboards and customizable workflows for labeling operations.
• Features fine-grained data row management for efficient scaling of labeling tasks.
Multi-modal annotation support across images, video, audio, text, geospatial formats
Ontology and feature schema management with nested classifications and object vs classification distinction
AI-assisted pre-labeling via foundation models and model-run integrations to speed up labeling
Customizable review workflows (benchmark, consensus, multi-step review) with audit trails
Batch-based queueing and priority management of data subsets instead of monolithic datasets
Data Rows tab for advanced filtering, status tracking, and managing large volumes of data rows
Model evaluation tools: leaderboards, error analysis, metrics across model runs, comparative diagnostics
Fully managed labeling services through Alignerrs — expert human workforce across domains and 30+ languages
Robust security, access control, role-based permissions; enterprise integrations (SSO, data governance)
Quality assurance via gold standard datasets, outlier detection, consensus, multi-tier review and feedback
How flexible is Labelbox’s labeling platform?
Labelbox supports a broad range of tasks and interfaces — from simple tag classification to complex multimodal or document tasks, with customizable templates and support for audio, video, HTML, etc., so both technical and non-technical users can operate.
Are there limits on task complexity?
No. Whether the task is small (image tagging) or large and complex (content analysis, algorithmic or document work), Labelbox can manage it, scaling resources and workflows appropriately.
What sets Labelbox’s labeling services apart?
The combination of a technical platform plus a vetted, expert workforce (Alignerrs), multi-language capability, and rigorous quality control makes Labelbox’s offerings more accurate, consistent, and tailored than many basic outsourcing options.
Is there API access and integration?
Yes. Labelbox provides SDKs and APIs; you can programmatically create features, manage ontologies, run model-assisted workflows, retrieve results, and integrate with other data sources to streamline your pipeline.
How is data quality ensured at scale?
Via multifaceted quality assurance: consensus labeling, gold-standard benchmarks, multi-step review workflows, error detection (via model vs ground truth), audit logs, and ongoing feedback with expert reviewers.