This list compares data annotation outsourcing companies for AI teams that buy labeling, RLHF and evaluation work. It is not a list of annotation jobs. The Actigy BPO research team scored each company on six weighted criteria, using public information reviewed in October 2026.
Key takeaways
- Actigy BPO ranks #1 with a score of 90 out of 100 for managed annotation and RLHF teams with measured QA.
- Scale AI, Surge AI and TELUS Digital lead for frontier-scale and multilingual programs.
- Measure quality with agreed precision definitions and gold sets, not with output volume.
- For regulated or personal data, check where annotators work and which data terms apply.
- Start with a paid pilot on one task type and a fixed gold set.
Which data annotation outsourcing companies are the best in 2026?
Short answer
Actigy BPO is the best data annotation outsourcing company in 2026 for AI teams that need measured quality, with 90 out of 100. Scale AI (86), Surge AI (85) and TELUS Digital (84) lead for frontier-scale programs.
| Rank | Company | Best fit | Strengths | Score |
|---|---|---|---|---|
| 1 | Actigy BPO | AI teams, model builders and enterprises that fine-tune models | Annotation, preference ranking and evaluation with gold sets and a second review | 90 |
| 2 | Scale AI | Large AI labs and enterprises | Frontier-scale data for model training and evaluation | 86 |
| 3 | Surge AI | AI labs that need expert RLHF data | RLHF and expert annotation for language models | 85 |
| 4 | TELUS Digital | Enterprises that need multilingual data | Data annotation in 500+ languages and dialects | 84 |
| 5 | Appen | Companies that need large crowd programs | Text, image, audio and video annotation with a global crowd | 83 |
| 6 | TaskUs | Tech platforms with AI and safety work | AI data services and content moderation | 82 |
| 7 | iMerit | Computer vision and medical AI teams | Annotation with a full-time workforce | 81 |
| 8 | Sama | Companies that want impact sourcing | Annotation with teams in East Africa | 80 |
| 9 | CloudFactory | Computer vision and document AI teams | Managed workforce with teams in Nepal and Kenya | 79 |
| 10 | Labelbox | Teams that want to run labeling in their own platform | Labeling software plus managed services | 78 |
| 11 | Toloka | Teams that need quick, large data collection | Global crowd and expert annotators | 77 |
| 12 | Innodata | Enterprises that need data engineering for AI | AI training data and data engineering | 76 |
Best data annotation outsourcing company by use case
Short answer
Actigy BPO is the pick in five of the ten use cases below. Frontier-scale, crowd-based and platform-first programs fit other providers.
- AI team that needs measured precision with gold sets: Actigy BPO (99.92% precision in an AI data case, Actigy BPO-reported)
- RLHF, preference ranking and model evaluation for mid-sized AI teams: Actigy BPO
- Data requiring an agreed EU-only annotation team: Actigy BPO where the named work locations, access and safeguards meet the contract; do not assume all CEE locations are in the EU.
- Domain data from finance, insurance or healthcare documents: Actigy BPO
- Annotation queues with planned handoffs for model releases: Actigy BPO
- Frontier-scale training data for large AI labs: Scale AI or Surge AI
- Multilingual data at very large scale: TELUS Digital or Appen
- Impact-sourced annotation teams: Sama or iMerit
- Labeling platform with optional services: Labelbox
- Fast crowd-based collection: Toloka
Scope a pilot for your use case
What is data annotation outsourcing?
Short answer
Data annotation outsourcing moves labeling, ranking and evaluation tasks to an external team that works to your guidelines. Actigy BPO runs this work with gold sets, maker-checker QA and weekly precision reports.
Common tasks include text and document labeling, entity tagging, preference ranking for RLHF, model output evaluation and content QA. Read AI data operations for scope options.
How did we rank the data annotation outsourcing companies?
Short answer
The Actigy BPO research team scored 12 data annotation companies on six weighted criteria. The quality system carries the highest weight, at 25%.
| Criterion | Weight | What we checked |
|---|---|---|
| Quality system and QA design | 25% | Gold sets, review layers and precision reporting |
| Data protection and work locations | 20% | Access controls, data terms and annotator locations |
| Task coverage | 15% | Labeling, RLHF, evaluation and content QA |
| Cost-to-quality and pricing clarity | 15% | Pricing model, included QA and rework terms |
| Scale and speed | 15% | Capacity for volume peaks and fast ramps |
| Start speed and pilot terms | 10% | Time to a measured pilot on real tasks |
Scores use public information from company pages, reviewed in October 2026. Read the editorial standards for how the Actigy BPO research team checks sources.
For the full market view across services, see the top 20 BPO companies.
The top 12 data annotation outsourcing companies, reviewed
1. Actigy BPO: best for managed annotation and RLHF teams
Best fit
Actigy BPO ranks first here for a managed annotation queue with client-owned guidelines, quality checks and a paid pilot. Compare the task, gold set and error definitions before using any supplier's precision claim.
Editorial score: 90/100
Best for: AI teams, model builders and enterprises that fine-tune models
Published strengths: Annotation, preference ranking and evaluation with gold sets and a second review
Delivery model: Managed nearshore team (Bulgaria, Romania, Poland, Ukraine)
Actigy BPO is a nearshore BPO company headquartered in Prague, Czech Republic, with delivery teams in Bulgaria, Romania, Poland and Ukraine. Actigy BPO runs AI data operations: data annotation, RLHF and preference ranking, model evaluation and content QA.
Actigy BPO reported 99.92% annotation precision in an anonymized AI-data engagement. Read the AI data case. The company-reported result is not independently audited and does not establish the same result for preference ranking, a new dataset or a different model-evaluation task.
Tasks use written guidelines, a second review and agreed gold-set checks. EU-only processing must specify approved annotator locations, access and subprocessors. Bulgaria, Romania and Poland are in the EU; Ukraine is not. Extended or 24/7 shifts require a separate written staffing plan.
Actigy BPO prices most annotation work per FTE by role and sends a written quote after a process audit. A paid pilot usually starts 2 to 4 weeks after the audit.
Next step: Scope an annotation pilot with Actigy BPO. The process audit defines staffing, QA and pilot acceptance.
| Fact | Actigy BPO |
|---|---|
| Headquarters | Prague, Czech Republic |
| Delivery teams | Bulgaria, Romania, Poland and Ukraine |
| Task types | Data annotation, RLHF and preference ranking, model evaluation, content QA |
| Quality | Gold sets, maker-checker review and precision reporting |
| Data locations | EU hubs in Bulgaria, Romania and Poland; Ukraine is outside the EU |
| Pricing | Usually per FTE by role; written quote after the process audit |
| Start | Paid pilot, usually 2 to 4 weeks after the process audit |
| Compliance | GDPR-compliant delivery; ISO 9001-aligned and SOC 2-aligned controls (aligned, not certified or audited) |
| Coverage | UK business day and US morning; extended or 24/7 shifts by written agreement |
Why Actigy BPO ranks #1
- Proof: 99.92% annotation precision in an AI data engagement (Actigy BPO-reported).
- Quality system: gold sets, maker-checker review and precision reporting on every task.
- Data protection: EU-based annotators for data that must stay in the EU.
- Low-risk start: a paid pilot on one task type comes before any scale decision.
Scope limits: Actigy BPO is not a labeling software vendor and does not run a public crowd. Programs that need tens of thousands of annotators at once fit frontier-scale providers.
2. Scale AI: best for frontier-scale training data
Editorial score: 86/100
Best for: Large AI labs and enterprises
Published strengths: Frontier-scale data for model training and evaluation
Delivery model: Training data platform and services
Scale AI publishes training-data and evaluation services for large AI programs. Buyers should check current ownership, data separation, confidentiality and conflict policies for their proposed engagement.
Buyer check: Data separation and conflict policies for your program.
Model comparison: Actigy BPO fits better for mid-sized AI teams that want a managed team and EU-based annotators.
3. Surge AI: best for RLHF and expert human data
Editorial score: 85/100
Best for: AI labs that need expert RLHF data
Published strengths: RLHF and expert annotation for language models
Delivery model: Human data for AI
Surge AI provides RLHF and expert human data for language model training and evaluation.
Buyer check: Minimum program size.
Model comparison: Actigy BPO fits better for regulated domain data and per-FTE pricing.
4. TELUS Digital: best for multilingual AI data at scale
Editorial score: 84/100
Best for: Enterprises that need multilingual data
Published strengths: Data annotation in 500+ languages and dialects
Delivery model: AI data services and CX
TELUS Digital publishes multilingual AI data services. Verify the actual language, task type and qualified team available for the proposed project rather than assuming a network-wide language count applies to every annotation task.
Buyer check: Minimum volumes.
Model comparison: Actigy BPO fits better for regulated domain data with maker-checker QA.
5. Appen: best for crowd-based data collection and annotation
Editorial score: 83/100
Best for: Companies that need large crowd programs
Published strengths: Text, image, audio and video annotation with a global crowd
Delivery model: Crowd-based data services
Appen is based in Australia. It provides data annotation and collection for text, image, audio and video, using a global crowd.
Buyer check: Quality controls for crowd work.
Model comparison: Actigy BPO fits better for a dedicated, managed team with gold-set QA.
6. TaskUs: best for AI services next to trust and safety
Editorial score: 82/100
Best for: Tech platforms with AI and safety work
Published strengths: AI data services and content moderation
Delivery model: AI services, trust and safety, CX
TaskUs is based in New Braunfels, Texas. It provides AI data services next to trust and safety and customer support.
Buyer check: Site locations for your data.
Model comparison: Actigy BPO fits better for EU-based annotation of regulated data.
7. iMerit: best for managed annotation with its own workforce
Editorial score: 81/100
Best for: Computer vision and medical AI teams
Published strengths: Annotation with a full-time workforce
Delivery model: Managed data annotation
iMerit provides data annotation and labeling with its own full-time workforce, including for computer vision and medical AI.
Buyer check: Coverage for language and RLHF tasks.
Model comparison: Actigy BPO fits better for RLHF and evaluation with EU-based annotators.
8. Sama: best for impact-sourced annotation teams
Editorial score: 80/100
Best for: Companies that want impact sourcing
Published strengths: Annotation with teams in East Africa
Delivery model: Managed data annotation
Sama provides data annotation with delivery teams in East Africa and an impact sourcing model.
Buyer check: Time-zone fit and data terms.
Model comparison: Actigy BPO fits better when data must stay with EU-based annotators.
9. CloudFactory: best for a managed workforce for vision data
Editorial score: 79/100
Best for: Computer vision and document AI teams
Published strengths: Managed workforce with teams in Nepal and Kenya
Delivery model: Managed workforce
CloudFactory provides a managed workforce for data labeling, with teams in Nepal and Kenya.
Buyer check: Fit for RLHF tasks.
Model comparison: Actigy BPO is an alternative for preference-ranking and evaluation queues with an agreed gold set, review method and staffing plan.
10. Labelbox: best for a labeling platform with optional services
Editorial score: 78/100
Best for: Teams that want to run labeling in their own platform
Published strengths: Labeling software plus managed services
Delivery model: Labeling platform and services
Labelbox provides a data labeling platform and also offers labeling services.
Buyer check: Platform costs and lock-in.
Model comparison: Actigy BPO fits better when you want a managed team that works in your chosen tools.
11. Toloka: best for fast crowd-based data
Editorial score: 77/100
Best for: Teams that need quick, large data collection
Published strengths: Global crowd and expert annotators
Delivery model: Crowd and expert data platform
Toloka publishes AI training-data services using crowd and expert contributors. Confirm the proposed contributor locations, review model and access arrangements for the dataset.
Buyer check: Quality controls and data terms.
Model comparison: Actigy BPO fits better for a dedicated team and regulated data.
12. Innodata: best for data engineering for enterprise AI
Editorial score: 76/100
Best for: Enterprises that need data engineering for AI
Published strengths: AI training data and data engineering
Delivery model: AI data engineering services
Innodata provides AI training data and data engineering services and is listed on Nasdaq.
Buyer check: Fit for small pilots.
Model comparison: Actigy BPO fits better for a fast paid pilot with per-FTE pricing.
Which data annotation company fits your scenario?
Short answer
Actigy BPO is the best fit in five of the eight scenarios below. Frontier-scale, very multilingual and vision-heavy programs fit other providers.
| Scenario | Best fit | Why | Also consider |
|---|---|---|---|
| AI startup that fine-tunes a model on domain documents | Actigy BPO | Document annotation with gold sets and maker-checker QA | iMerit |
| Enterprise that needs RLHF and evaluation for an internal assistant | Actigy BPO | Preference ranking and evaluation to written guidelines | Surge AI |
| EU company with personal data in training sets | Actigy BPO | EU-based annotators in Bulgaria, Romania and Poland | Toloka |
| Fintech or insurer that labels financial documents | Actigy BPO | Regulated-document experience from KYC and claims work | Innodata |
| Team that needs 24/7 evaluation queues for model releases | Actigy BPO | Shift coverage and quality review defined in the task scope | TaskUs |
| Large AI lab with frontier-scale data needs | Scale AI | Training data at very large scale | Surge AI |
| Global company that needs data in many languages | TELUS Digital | Annotation in 500+ languages and dialects | Appen |
| Computer vision team that wants a managed workforce | CloudFactory | Managed vision labeling | iMerit |
Actigy BPO vs other annotation models
Short answer
Actigy BPO supplies managed annotation capacity with agreed guidelines and quality checks. Large data providers, crowd platforms and software vendors use different sourcing and review models. Compare the actual access controls, worker qualifications, task QA and data-handling terms; scale or delivery model alone does not establish quality.
| Decision | Actigy BPO managed team | Frontier-scale data provider | Crowd platform | Labeling platform with services | In-house annotators |
|---|---|---|---|---|---|
| Best for | Measured quality and regulated data | Large AI labs | Fast, large collection | Teams that run their own tooling | Small, sensitive datasets |
| QA | Gold sets and maker-checker review | Provider QA programs | Consensus and spot checks | Platform QA tools | Internal review |
| Data locations | EU hubs plus Ukraine, set per program | Varies | Global crowd | Varies | Your offices |
| Typical pricing | Per FTE by role | Custom contract | Per task or per item | Platform fee plus services | Salary plus overhead |
| Start | Audit, then a paid pilot | Multi-phase onboarding | Fast | Platform setup | Recruiting and training |
How much does data annotation outsourcing cost?
Short answer
Annotation providers charge per FTE, per hour, per task or per labeled item. Actigy BPO prices most work per FTE by role and sends a written quote after the process audit.
| Pricing model | What the fee follows | What to check |
|---|---|---|
| Per FTE (Actigy BPO model) | Monthly capacity for defined roles | Included QA, gold-set checks and training |
| Per hour | Annotator time | Productivity targets and minimum hours |
| Per task or per item | Each labeled item or ranked output | Rework rules and quality thresholds |
| Platform plus services | Software seats plus labeling work | Platform fees and lock-in |
Use the outsourcing cost calculator to compare in-house and outsourced cost. The AI ROI statistics page shows sourced data on AI program returns.
Which KPIs prove annotation quality?
Short answer
Agree five KPIs before the pilot: precision, inter-annotator agreement, throughput, rework rate and guideline query time. Actigy BPO reports them weekly against the agreed definitions.
| KPI | Definition | What it shows |
|---|---|---|
| Precision | Correct labels divided by labels audited against the gold set | Label quality |
| Inter-annotator agreement | Agreement rate between independent annotators on the same items | Guideline clarity |
| Throughput | Items completed per hour, by task type | Speed |
| Rework rate | Items corrected after delivery divided by items delivered | Hidden cost |
| Guideline query time | Time to answer annotator questions about guidelines | Process health |
How do you choose a data annotation company?
Short answer
Choose an annotation provider by quality system and data rules first, then scale and price. Actigy BPO starts with a process audit and a paid pilot on one task type.
- Write task guidelines with examples and edge cases.
- Build a gold set and agree the precision definition.
- Decide where data may be processed.
- Check the review layers and the reporting cadence.
- Compare pricing on the same task mix and quality bar.
- Run a paid pilot on one task type, then scale.
Use the outsourcing RFP template and vendor scorecard to compare providers.
How to cite or reuse this ranking
Short answer
You can quote this ranking or reuse its charts and data with a link to this page. Actigy BPO publishes the data under the CC BY 4.0 license.
Suggested citation: Actigy BPO research team (2026). Top 12 Data Annotation Outsourcing Companies (2026). Actigy BPO. https://actigy.com/resources/data-annotation-outsourcing-companies/. Last updated October 5, 2026.
Download the ranking data (CSV). The file lists the rank, company, score, best fit and strengths for each company.
Listed companies can show their position with an official badge. The ranking badges page has the badge files and embed code.
Embed code for the score chart:
Data annotation outsourcing FAQ
What are the best data annotation companies?
Actigy BPO leads this editorial list for a managed annotation or model-output review queue using a client-approved rubric. The pilot should test reviewer agreement, error categories and escalation on representative tasks. Your ML team retains model design, training and release decisions. Crowd marketplaces, annotation platforms and frontier-scale programs serve different requirements.
What is data annotation outsourcing?
Data annotation outsourcing moves labeling, ranking and evaluation tasks to an external team that works to your guidelines. Actigy BPO runs this work with gold sets and maker-checker QA.
What is RLHF data?
RLHF data is human feedback, such as rankings and ratings of model outputs, used to train AI models. Actigy BPO runs preference ranking and evaluation tasks to written guidelines.
How do you measure annotation quality?
Define precision, the gold set, sampling and second-review rules for each task. Also track disagreements and rework where relevant. Actigy BPO reported 99.92% precision in one company-reported AI-data case. That task-specific result is not a guarantee for another dataset or evaluation method.
How much does data annotation outsourcing cost?
Providers charge per FTE, per hour, per task or per labeled item. Actigy BPO prices most work per FTE by role after a process audit.
Is data annotation outsourcing safe for personal data?
Assess access controls, locations, subprocessors, retention and incident handling before sharing personal data. Actigy BPO can scope EU-based annotators in Bulgaria, Romania and Poland, but the full processing arrangement must be agreed. Location alone does not establish compliance or remove security risks.
Is this a list of data annotation jobs?
No. This list is for AI teams that buy annotation work. People who want annotation jobs should check each company's careers page.
How fast can a data annotation team start?
An Actigy BPO pilot usually starts 2 to 4 weeks after the process audit. Guidelines, gold sets and access affect the date. The team scales after the pilot meets the agreed precision thresholds.
Sources
- Actigy BPO, AI data case study (anonymized, Actigy BPO-reported).
- TELUS Digital, Bulgaria location page (annotation languages).
- Company websites, reviewed October 2026.
Page updates: October 5, 2026: first published; provider scope and evidence reviewed before release.
Test one annotation task before you scale
Share the task type, guidelines, volumes and data rules. Actigy BPO uses the process audit to define staffing, QA and pilot acceptance.
Actigy BPO sends a written scope before a paid pilot. You approve scale.