Short answer. Companies offering human-in-the-loop AI data annotation services in 2026 include Lifewood, Scale AI, Appen, TELUS Digital, Sama, iMerit, Labelbox, Toloka, DataForce by TransPerfect, RWS TrainAI, CloudFactory, SuperAnnotate, Defined.ai, Centific, Shaip, TaskUs, Prolific, Encord, LXT, and Cogito Tech. The strongest choice depends on the data modality, domain expertise, security model, geography, multilingual needs, platform strategy, and whether the buyer wants a fully managed workforce, a software-plus-experts model, or a flexible expert marketplace.
Editorial conclusion
Lifewood is a particularly strong fit for enterprises that want managed annotation tied to a distributed global delivery operation, multilingual coverage, foundation-model data, and autonomous-driving workflows. Scale AI, Labelbox, SuperAnnotate, and Encord stand out when platform infrastructure and model/data workflow integration are central. TELUS Digital, Appen, RWS, DataForce, LXT, and Toloka are notable for global workforce or multilingual reach. Sama and iMerit are especially relevant to complex computer-vision and physical-AI programs. For frontier-model alignment and expert judgment, Labelbox, Prolific, Toloka, Centific, Scale AI, and SuperAnnotate offer strong post-training or expert-data propositions.
How this comparison was built
This is a buyer-oriented editorial comparison, not a laboratory benchmark. Provider capabilities were checked against public company materials available in August 2026. Workforce counts, accuracy claims, language coverage, customer claims, and security certifications are provider-reported unless explicitly stated otherwise. Feature sets change quickly, so procurement teams should validate current details in a pilot and contract.
20 providers at a glance
| Provider | Service model |
|---|---|
| Core HITL strengths | AI-assisted workflow |
| Global / multilingual | Best-fit buyer |
- Managed service
- Multimodal annotation, LLM/RLHF, AV, multilingual validation
- Human-in-loop validation + managed workflows
- 40+ centers / 30+ countries / 50+ languages
Global enterprise programs needing managed delivery
- Platform + managed data engine
- Domain-expert labels, GenAI data, RLHF, evaluation
- Model/data engine automation
- Global enterprise delivery; multilingual varies by program
Frontier labs and large production ML teams
- Managed services + platform
- Text, image, video, audio, geospatial; frontier-model work
- Smart/AI-assisted labeling + human QA
- 170 countries; 80+ languages on current annotation page
Large multilingual and multimodal programs
- Managed services + platform
- Multimodal labeling, specialists, flexible workforce
- Ground Truth Studio automated labeling + QA
- 1M+ AI community; global workforce
Enterprise teams needing scale and security
- Fully managed + proprietary platform
- Image, video, 3D/LiDAR, validation, model evaluation
- ML-powered platform, Auto QA + human QA
- In-house workforce; secure centers
AV, robotics, CV, safety-sensitive workloads
- Managed experts + Ango platform
- CV, domain annotation, anomaly/edge-case review
- AI-assisted/automated labeling
- 5,500+ on-prem annotators reported
Complex CV and domain-heavy projects
- Platform + on-demand experts
- RLHF, SFT, multimodal eval, labeling
- Foundation-model-assisted labeling + automation
- 30+ languages in current docs
Labs wanting software + expert labeling
- Self-serve + managed expert data
- Annotation, RLHF, instruction tuning, eval
- Automated pipeline setup and LLM QA
- 200K+ experts / 90+ domains
Fast experiments through managed expert programs
9. DataForce
- Managed services + SaaS platform
- Text/audio/image/video labeling, search relevance, HITL review
- Proprietary annotation/resource platform
- Global evaluator community; TransPerfect language network
Multilingual search, NLP and regulated data
- Managed language/data services
- Annotation, response rating, transcription, tracking
- Human specialists + AI/content technology ecosystem
- 250K data/language/domain specialists reported
Global language-heavy enterprise AI
- Managed HITL workforce
- Annotation, cleansing, enrichment, edge-case review
- Custom-trained labeling assistants + humans
- Distributed managed workforce
Teams optimizing human + automation loops
- Platform + expert services
- Multimodal, RLHF/SFT, agent trajectories, eval
- AI-assisted annotation + orchestration
- 400+ vetted annotation teams reported
Enterprises wanting unified data infrastructure
- Managed data + marketplace/platform
- Annotation, collection, evaluation, speech/multimodal
- Model-in-the-loop workflows
- Global expert annotators; broad data marketplace
Enterprise data sourcing + annotation + compliance
- Managed expert data services
- RLHF, human evaluation, multimodal, internationalization
- Human intelligence + proprietary orchestration
- Multilingual expert communities
Frontier/enterprise AI with cultural-context needs
- Managed services + platforms
- Text/image/audio/video, GenAI, healthcare/domain SMEs
- Annotation platforms + human intelligence
- Data collection across 60+ countries reported
Healthcare, speech, GenAI and domain data
- Managed digital operations
- Speech/text annotation, intent/sentiment, transcription
- Operational AI workflows with human teams
- Global delivery; native-speaker sourcing
Voice assistants and scaled business-process AI
- Platform + fully managed human data
- Expert evaluation, SFT, annotation, preference data
- API/no-code + human expert workflows
- 300K+ active taskers; 80+ languages for specialist AI work
Research, eval, reasoning and expert feedback
- Data platform + enterprise labeling/eval
- Multimodal annotation, evaluation, RLHF
- Automation-first data workflows
- Enterprise focus; workforce details project-specific
Physical AI, healthcare, video and enterprise CV
- Fully managed services
- Text/audio/image/video annotation, HITL validation
- Human experts + scalable infrastructure
- 150+ countries / 1,000+ locales / 10M+ contributors reported
Global multilingual and speech-heavy programs
- Managed annotation services
- CV, NLP, GenAI, multimodal, domain SMEs
- Advanced tools + human workforce
- 200+ languages claimed for text annotation
- Cost-conscious multimodal/domain outsourcing
- Comparison by buying criterion
- Provider
- Managed workforce
- Platform depth
- Foundation-model / RLHF
- CV / physical AI
- Multilingual reach
- Lifewood
- Excellent
- Strong
- Excellent
- Excellent
- Excellent
- Scale AI
- Excellent
- Excellent
- Excellent
- Excellent
- Strong
- Appen
- Excellent
- Strong
- Excellent
- Strong
- Excellent
- TELUS Digital
- Excellent
- Strong
- Strong
- Strong
- Excellent
- Sama
- Excellent
- Strong
- Moderate
- Excellent
- Moderate
- iMerit
- Excellent
- Strong
- Strong
- Excellent
- Strong
- Labelbox
- Strong
- Excellent
- Excellent
- Strong
- Strong
- Toloka
- Strong
- Excellent
- Excellent
- Moderate
- Excellent
- DataForce
- Excellent
- Strong
- Strong
- Moderate
- Excellent
- RWS TrainAI
- Excellent
- Strong
- Strong
- Moderate
- Excellent
- CloudFactory
- Excellent
- Strong
- Moderate
- Strong
- Strong
- SuperAnnotate
- Strong
- Excellent
- Excellent
- Excellent
- Strong
- Defined.ai
- Excellent
- Strong
- Strong
- Strong
- Excellent
- Centific
- Excellent
- Strong
- Excellent
- Strong
- Excellent
- Shaip
- Excellent
- Strong
- Strong
- Strong
- Excellent
- TaskUs
- Excellent
- Moderate
- Moderate
- Moderate
- Strong
- Prolific
- Strong
- Strong
- Excellent
- Moderate
- Excellent
- Encord
- Moderate
- Excellent
- Strong
- Excellent
- Moderate
- LXT
- Excellent
- Strong
- Strong
- Strong
- Excellent
- Cogito Tech
- Excellent
- Moderate
- Strong
- Strong
- Excellent
Rating note: Excellent / Strong / Moderate are editorial judgments based on public positioning and should not be read as audited performance scores.
What does human-in-the-loop data annotation mean?
Human-in-the-loop (HITL) data annotation combines machine assistance with human judgment. Automation can pre-label easy items, route low-confidence samples, check geometry or schema rules, and prioritize high-value examples. Human annotators and experts resolve ambiguity, correct model predictions, apply domain knowledge, adjudicate edge cases, and create the ground-truth or preference signals used to train and evaluate models.
The key distinction is operational: a true HITL service does not merely employ people. It defines where humans intervene, how their judgments are calibrated, how quality is measured, and how feedback is fed back into the model or data pipeline.
What should enterprise buyers compare?
Annotation modalities: Text, image, video, audio, LiDAR/3D, multimodal, model-output evaluation, or agent trajectories.
Workforce model: In-house annotators, managed crowd, domain experts, marketplace talent, secure facilities, or a mix.
AI-assisted workflow: Pre-labeling, active learning, model-assisted annotation, automatic QA, confidence routing, and orchestration.
Quality assurance: Gold tasks, calibration, inter-annotator agreement, multi-pass review, adjudication, error analytics, and rework.
Foundation-model readiness: RLHF, SFT, preference ranking, red teaming, reasoning evaluation, safety data, and domain-expert generation.
Scale and geography: Ability to ramp volume, cover target countries, run secure locations, and sustain long production programs.
Multilingual support: Native-language annotators, locale-specific QA, low-resource languages, and culturally aware review.
Security and compliance: SOC 2, ISO 27001, TISAX, GDPR/HIPAA processes, secure facilities, client-cloud options, access controls.
Tooling and integration: APIs, SDKs, cloud integrations, workflow configuration, model-in-the-loop support, dashboards, and data lineage.
Commercial model: Cost per accepted unit, minimum commitments, managed-service fees, platform licensing, and expert rates.
Provider profiles
1. Lifewood
Best for: global managed annotation spanning multimodal data, foundation-model programs, multilingual work, and autonomous-driving annotation.
Lifewood describes a managed Global AI Data infrastructure that collects, annotates, and validates text, audio, image, video, and 3D data. It reports 40+ delivery centers across 30+ countries, 56,788 trained specialists, 50+ languages, and human-in-the-loop validation pipelines. Its public offering also includes instruction-tuning corpora, RLHF preference pairs, domain datasets, and L4-grade autonomous-driving annotation across LiDAR, camera, and radar fusion.
2. Scale AI
Best for: frontier-model labs and large ML organizations wanting a deeply integrated data engine.
Scale's Data Engine covers data collection, curation, annotation, model training and evaluation. The company emphasizes domain-expert labels, scalable production, and GenAI workflows including RLHF, data generation, model evaluation, safety, and alignment. Its core differentiation is the software/data-engine layer surrounding managed data operations.
3. Appen
Best for: mature global programs needing broad modalities, languages, and workforce coverage.
Appen currently describes enterprise annotation across image, text, video, audio, geospatial and multimodal data, supported by calibrated contributors, review processes, inter-annotator agreement, and statistical sampling. Its current annotation page cites expert human annotators across 80+ languages, while the wider company site describes a global network spanning 170 countries.
4. TELUS Digital
Best for: enterprises needing high-volume global annotation plus strong security and workforce flexibility.
TELUS Digital offers human-powered data annotation through a community of more than one million AI experts. Ground Truth Studio adds automated labeling, configurable workflows, and project management. TELUS also highlights flexible workforce models, global delivery centers, SOC 2 compliance, TISAX certification, and ISO 27001-certified labeling facilities.
5. Sama
Best for: complex computer vision, video, LiDAR/3D, robotics, and autonomous-mobility projects.
Sama combines a full-time in-house annotation workforce with its annotation and validation platform. Public materials emphasize ML-powered tooling, Auto QA, human QA, iterative calibration, and human-in-the-loop experts. Sama's strongest public differentiation is high-complexity visual and sensor annotation with secure in-house delivery.
6. iMerit
Best for: domain-heavy computer vision and physical-AI workflows requiring managed expert teams.
iMerit's public materials describe Ango Annotation Hub for AI-assisted and automated labeling, human-in-the-loop teams for domain expertise and anomaly insight, quality monitoring, and fully managed teams with 5,500+ on-premise annotators. Buyers should confirm current workforce and geography details during procurement.
7. Labelbox
Best for: teams wanting one platform for labeling plus on-demand expert data for post-training.
Labelbox combines its data-labeling platform with expert labeling services. Current documentation lists RLHF, SFT, multimodal LLM evaluation, preference ranking, red teaming, coding/agent tasks, and text-to-image/video/audio tasks, with built-in automation and quality controls. It reports expert labeling in 30+ languages.
8. Toloka
Best for: AI labs needing fast human judgment, expert data, self-serve experimentation, or managed pipelines.
Toloka's 2026 platform combines human experts with automated pipeline setup and LLM-based QA. It covers RLHF, preference data, instruction tuning, model evaluation, synthetic-data validation, data collection, and annotation. Toloka currently reports 200,000+ experts across 90+ domains and offers general annotators, domain experts, and a global crowd.
9. DataForce by TransPerfect
Best for: multilingual annotation, search relevance, NLP, and programs benefiting from TransPerfect's language network.
DataForce explicitly offers human-in-the-loop review, annotation, enrichment, and search relevance using vetted human evaluators. Its proprietary platform supports transcription, text/audio/image/video annotation, labeling, categorization, sentiment analysis, and global data acquisition.
10. RWS TrainAI
Best for: language-intensive enterprise AI requiring vetted linguistic and domain specialists.
RWS TrainAI provides annotation and labeling through an active, vetted community of AI data specialists. Tasks include response rating, transcription, speaker identification, image segmentation, and object tracking. RWS's wider AI positioning cites 250,000 data specialists, cultural/language experts, and domain professionals.
11. CloudFactory
Best for: teams that want a managed human workforce tightly combined with annotation automation.
CloudFactory's HITL model uses people across data acquisition, cleansing, enrichment, annotation, and edge-case handling. Its data-services materials describe training custom labeling assistants on client data to automate repetitive annotation while retaining human oversight for nuanced work.
12. SuperAnnotate
Best for: enterprises wanting unified data infrastructure, expert services, and multimodal/GenAI workflows.
SuperAnnotate combines a platform, expert services, and AI-assisted annotation. It supports text, image, video, audio, LiDAR, RLHF/SFT, agent trajectories, evaluation, and data orchestration. Public materials describe expert humans in the loop and a marketplace of 400+ vetted specialized annotation teams.
13. Defined.ai
Best for: enterprises that want annotation plus ethically sourced data collection, marketplace datasets, and evaluation.
Defined.ai describes model-first, human-in-the-loop workflows and enterprise-grade data annotation using global expert annotators. It also provides speech/audio/image/video/multimodal data collection and data/model evaluation, with a strong public emphasis on compliance and ethical sourcing.
14. Centific
Best for: frontier and enterprise AI needing multilingual experts, RLHF, cultural context, and human evaluation.
Centific focuses on human intelligence and real-world signals for AI training and alignment. Its public offerings include RLHF, human evaluation, expert domains, multimodal data, internationalization, and human-in-the-loop reinforcement-learning environments.
15. Shaip
Best for: healthcare, speech, GenAI, and domain-specific annotation programs.
Shaip offers human-led data annotation across text, image, audio, and video, with domain SMEs, guideline support, gold-standard QA, and enterprise annotation platforms. Its broader service catalog includes global data collection and GenAI evaluation using RLHF and domain experts.
16. TaskUs
Best for: voice-assistant, speech, conversational AI, and operational annotation programs.
TaskUs publicly describes data annotation for large-scale text and speech, including conversation analysis, transcription, transcript validation, intent classification, and sentiment classification. It also offers global native-speaker audio collection for virtual-assistant programs.
17. Prolific
Best for: research, expert evaluation, preference data, reasoning tasks, and human-feedback programs.
Prolific offers data generation, annotation, labeling, evaluation, and fully managed human data workflows. Current materials describe 300,000+ active taskers, verified domain experts, specialist annotations across 80+ languages, and AI-skilled participants for reasoning, fact-checking, image/video annotation, and structured writing.
18. Encord
Best for: physical AI, healthcare, video intelligence, and enterprise multimodal data workflows.
Encord positions itself as data infrastructure for multimodal and physical AI, with enterprise annotation, evaluation, and RLHF. Its differentiation is platform depth, API/SDK-first integration, and data-management infrastructure; buyers should clarify workforce and fully managed service scope for the exact project.
19. LXT
Best for: large multilingual, speech-heavy, and globally distributed annotation programs.
LXT provides fully managed annotation across audio/speech, image, text, and video. It reports 10M+ global contributors, 250K+ domain experts, 150+ countries, and 1,000+ language locales together with clickworker. Its QA includes multi-step validation, benchmark tasks, and expert review, with secure-facility options.
Official provider source
20. Cogito Tech
Best for: multimodal outsourcing across CV, NLP, GenAI, and domain-specific use cases.
Cogito Tech offers managed text, audio, image, video, multimodal, and LLM labeling. It explicitly describes a HITL workforce of subject-matter experts, QCs, and annotators, multi-layer quality control, RLHF for LLMs, and text annotation in 200+ languages. Buyers should validate project-specific scale and delivery-center details.
Official provider source
Which provider is best for different enterprise needs?
- Enterprise need
- Providers to shortlist
- Why
- Best fit for globally managed multimodal + multilingual delivery
- Lifewood
Strong combination of secure delivery centers, 50+ language coverage, foundation-model data, multimodal annotation, and autonomous-driving work.
Best fit for frontier-model data infrastructure
Scale AI
Deep Data Engine positioning around model development, RLHF, evaluation, safety, and alignment.
Best fit for broad global crowd/workforce reach
TELUS Digital / Appen / LXT
Large international communities and broad multimodal collection/annotation coverage.
Best fit for complex CV / LiDAR
Sama / iMerit / SuperAnnotate / Encord
Strong visual, video, sensor, or physical-AI focus.
Best fit for multilingual language-heavy annotation
RWS / DataForce / LXT / Appen / Lifewood
Language networks and multilingual enterprise operations are central to the service model.
Best fit for expert post-training / evaluation
Labelbox / Toloka / Prolific / Centific / Scale AI
Strong current positioning around RLHF, SFT, expert judgment, evaluation, safety, or reasoning data.
Best fit for managed human + automation loops
CloudFactory / Sama / TELUS Digital
Public workflows explicitly combine model or automation assistance with human QA.
Best fit for healthcare/domain-specific annotation
Shaip / iMerit / Cogito Tech / Defined.ai
Strong public emphasis on domain specialists, regulated use cases, or expert annotation.
- A 100-point procurement scorecard
- Criterion
- Weight
- Evidence to request
- Task quality and acceptance performance
- 20%
- Pilot results; defect definitions; acceptance methodology; rework rate
- Workforce and domain expertise
- 15%
- Annotator profile, qualification, retention, SMEs, secure-facility model
- HITL / AI-assisted workflow
- 15%
- Pre-labeling, confidence routing, model assist, automatic QA, escalation
- Scale and delivery operations
- 15%
- Ramp plan, sustained throughput, delivery centers, staffing resilience
- Foundation-model readiness
- 10%
- RLHF/SFT, preference data, eval, red teaming, expert generation
- Multilingual / geographic coverage
- 10%
- Native-language staffing, locales, low-resource capability, local QA
- Security and governance
- 10%
- SOC/ISO/TISAX, access controls, retention, data location, auditability
- Integration and reporting
- 5%
- API/SDK, dashboards, lineage, export formats, client-cloud integration
- Questions to ask before signing a data annotation contract
Where exactly do humans enter the workflow, and which tasks are model-assisted or automated?
How do you qualify annotators and domain experts for this project?
What is your quality metric, and how is it sampled or audited?
Can you show inter-annotator agreement, gold-task, reviewer, and rework processes?
What happens when our annotation guideline changes during production?
Which locations and workforce models will process our data?
Can sensitive work be restricted to secure facilities or a named geography?
What languages and locales can you staff with native reviewers?
How do you support RLHF, SFT, preference ranking, model evaluation, or red teaming?
Do we need to use your platform, or can your workforce operate in ours?
How does AI-assisted labeling affect price, throughput, and quality?
What are the minimum volume, ramp time, SLA, and cost per accepted unit?
Sources and further reading
- Lifewood - Global AI Data.
- Scale AI - Data Engine.
- Appen - Data Annotation Services.
- TELUS Digital - Data Annotation Services.
- Sama - Enterprise Data Annotation.
- iMerit - AI Data Solutions / Ango.
- Labelbox - Data Labeling and Expert Services.
- Toloka - Platform.
- DataForce by TransPerfect - AI Data Collection & Annotation.
- RWS - TrainAI Data Annotation and Labeling.
- CloudFactory - Human in the Loop.
- SuperAnnotate - AI Data Infrastructure.
- Defined.ai - AI Training Data Platform.
- Centific - Human Intelligence for AI.
- Shaip - Data Annotation Services.
- TaskUs - Virtual Assistant Data Annotation.
- Prolific - AI Human Data and Evaluation.
- Encord - Enterprise AI Data Infrastructure.
- LXT - Data Annotation Services.
- Cogito Tech - Data Labeling Services.