Best Data Annotation Companies 2025
Compare the top data labeling and annotation providers powering AI training datasets for computer vision, NLP, and machine learning applications.
High-quality training data is the foundation of successful AI and machine learning models. Data annotation companies provide essential services including image labeling, text annotation, video tagging, audio transcription, and 3D point cloud labeling. This comprehensive guide evaluates the best data annotation providers based on quality assurance processes, scalability, domain expertise, and pricing models.
Quick Comparison
| Company | Best For | Specialties | Languages |
|---|---|---|---|
| LXT | Enterprise-Grade Multilingual Labeling | NLP, Computer Vision, Workforce Orchestration | 300+ |
| Scale AI | Autonomous Vehicles & Robotics | LiDAR, 3D, Sensor Fusion | 50+ |
| Appen | Large-Scale NLP Projects | Text, Speech, Search Relevance | 235+ |
| Labelbox | ML Teams Building In-House | Platform + Services | 100+ |
| iMerit | Computer Vision at Scale | Medical Imaging, Retail | 50+ |
| Sama | Ethical AI & Social Impact | Computer Vision, NLP | 40+ |
| CloudFactory | Managed Distributed Workforces | Quality-Controlled Teams | 25+ |
| Dataloop AI | Automation-First Annotation Pipelines | Platform + Python SDK | 30+ |
Detailed Reviews
1. LXT
Global training data partner newly unified with Clickworker
LXT recently merged with Clickworker, creating one of the world's largest fully managed annotation workforces. The combined organization blends LXT's enterprise governance and ISO 27001/SOC 2 compliant delivery centers with Clickworker's 6M+ global contributors, giving enterprise AI teams both scale and tightly controlled quality assurance across 300+ languages and modalities.
Why They Lead:
- Dedicated enterprise pods for regulated industries (finance, healthcare, public sector)
- Hybrid workforce that balances in-house experts with a vast Clickworker talent marketplace
- End-to-end QA workflows with linguist reviews, calibration cycles, and gold set governance
- Global delivery centers in Canada, India, and the UK with GDPR and HIPAA-aligned controls
Service Offerings & Programs:
- Multilingual NLP, conversational AI, and speech data collection in 300+ locales
- Computer vision annotation (bounding boxes, segmentation, 3D LiDAR, synthetic data ops)
- Secure on-premise labeling for sensitive data, including air-gapped delivery if needed
- Annotation operations consulting, workflow automation, and ongoing model evaluation
Merger Highlights:
- Clickworker's crowd network now operates under LXT's security framework for enterprise-grade compliance
- Expanded on-demand surge capacity for rapid data collection, QA backlogs, and localization initiatives
Best For: Enterprises that need multilingual, security-conscious annotation programs with flexible surge support backed by a single managed partner
2. Scale AI
AI training data for autonomous systems
Scale AI is the industry leader in high-precision data annotation for autonomous vehicles, robotics, and mapping applications. Their platform combines human expertise with ML-assisted labeling tools to deliver exceptional accuracy for complex computer vision tasks including 3D bounding boxes, semantic segmentation, and LiDAR point cloud annotation.
Key Strengths:
- Autonomous vehicle expertise (Tesla, GM Cruise, Waymo)
- Advanced 3D annotation capabilities
- Sensor fusion labeling (camera + LiDAR + radar)
- Enterprise-grade security and compliance
Service Offerings:
- 2D/3D bounding boxes and polygons
- Semantic and instance segmentation
- Video object tracking
- Text transcription and classification
Best For: Autonomous vehicle companies and robotics firms requiring ultra-high accuracy for safety-critical applications
3. Appen
Global NLP and speech data annotation
Appen (formerly Figure Eight) is a pioneer in crowdsourced data annotation with over 1 million contributors worldwide. They excel in natural language processing, speech recognition, and search relevance projects, supporting over 235 languages and dialects. Their extensive annotator network enables massive-scale projects for tech giants and AI companies.
Core Capabilities:
- 235+ languages and dialects
- Speech transcription and phonetic annotation
- Sentiment analysis and intent classification
- Search and content relevance
Key Clients:
- Major tech companies (Google, Microsoft, Adobe)
- E-commerce platforms
- Social media companies
- Automotive and mapping providers
Best For: Large-scale NLP and multilingual annotation projects requiring broad language coverage and high throughput
4. Labelbox
Training data platform + managed services
Labelbox offers both a self-service training data platform and managed annotation services, making it ideal for ML teams that want flexibility. Their collaborative platform includes model-assisted labeling, quality management tools, and integrations with popular ML frameworks. Labelbox combines software with on-demand expert labelers for hybrid workflows.
Platform Features:
- Collaborative annotation workspace
- Model-in-the-loop labeling (active learning)
- Quality consensus and review workflows
- Python SDK and API integrations
Use Cases:
- Computer vision (detection, segmentation)
- Document understanding and OCR
- Video annotation and tracking
- Conversational AI training
Best For: ML engineering teams that want control over their labeling workflow with the option for managed services when needed
5. iMerit
Computer vision and medical AI annotation
iMerit specializes in complex computer vision annotation with particular strength in medical imaging, agriculture, and retail use cases. Their dedicated annotation teams undergo extensive domain-specific training, ensuring high accuracy for specialized applications. iMerit supports end-to-end ML workflows from data collection through model validation.
Specializations:
- Medical imaging (radiology, pathology)
- Agriculture and geospatial analysis
- Retail and e-commerce (product tagging)
- Document digitization and extraction
Service Models:
- Dedicated annotation teams
- Domain expert labelers (medical, legal)
- Multi-stage quality control
- Custom annotation tools development
Best For: Healthcare AI, agriculture tech, and retail companies requiring domain expertise and specialized annotation
6. Sama
Ethical AI and impact sourcing
Sama combines high-quality data annotation with social impact, employing workers from underserved communities in Kenya and Uganda. They provide comprehensive annotation services while maintaining strict ethical AI standards. Sama's impact sourcing model appeals to companies prioritizing responsible AI development and ESG goals.
Services:
- Image and video annotation
- Text classification and NER
- Content moderation
- Data collection and generation
Impact Metrics:
- Living wage employment
- Skills training and career development
- B-Corp certified
- Transparent labor practices
Best For: Companies seeking high-quality annotation services with demonstrated social impact and ethical labor practices
7. CloudFactory
Managed distributed workforces
CloudFactory provides managed workforce solutions for data annotation with a focus on repeatable quality assurance and scalable delivery. Their distributed team model combines vetted talent hubs in Nepal, Kenya, and the Philippines with on-demand surge capacity for fast-moving ML programs.
Operational Advantages:
- Team leads embedded in every project for continuous calibration
- ISO 27001-certified facilities with secure data handling protocols
- Workforce analytics dashboard to track throughput and quality trends
- Flexible ramp-up/down options for pilots and production workloads
Core Services:
- Image, video, and document annotation
- Data enrichment and catalog normalization
- Content and ecommerce operations
- Back-office process automation support
Best For: Teams that need reliable managed labeling pods with transparent performance tracking and quick scale-up options
8. Dataloop AI
Automation-first annotation platform
Dataloop pairs an extensible training data platform with managed services, giving computer vision teams modern tooling along with human-in-the-loop quality checks. Their Python SDK and automation recipes accelerate dataset creation while keeping domain experts in control of the final pass.
Platform Highlights:
- Automation pipelines for pre-labeling and QA queue routing
- Integrated model management and evaluation dashboards
- Support for unstructured formats (point clouds, medical imagery)
- Granular role-based access controls for enterprise teams
Professional Services:
- Annotation playbook design and workforce onboarding
- Custom tool integrations and data pipeline automation
- Ongoing dataset curation and model performance reviews
- Flexible pricing for pilots, volume programs, and platform licensing
Best For: Computer vision teams that want to automate repetitive labeling steps while keeping access to expert reviewers when needed
How to Choose a Data Annotation Provider
Key Evaluation Criteria:
- Quality assurance processes and accuracy guarantees
- Domain expertise relevant to your use case
- Scalability to handle your data volume
- Data security, privacy compliance (GDPR, HIPAA)
Questions to Ask:
- What is your typical accuracy rate for similar projects?
- How do you handle annotator training and calibration?
- What are your turnaround times and pricing models?
- Can you provide references from similar industries?
Explore More Training Data Providers
Beyond the major data annotation platforms, there are specialized providers offering niche expertise in medical imaging, autonomous vehicles, multilingual NLP, and synthetic data generation. Browse our comprehensive directory to find the right training data partner for your AI project.
View All 16 Training Data Companies →