- High-quality labeled datasets are crucial for training AI models to make accurate predictions and decisions.
- Data annotation companies offer scalable, expert services that improve AI model training efficiency with notable reductions in time and costs.
- Experienced annotation companies ensure precise labeling, helping businesses overcome in-house limitations and achieve faster AI deployment.
AI models thrive on high-quality data, but many businesses struggle with challenges like poorly labeled datasets, limited in-house expertise, and steep annotation costs. Without precise training data, AI systems fail to recognize patterns, make informed decisions, and produce reliable results — ultimately limiting their effectiveness.
By outsourcing annotation, businesses can accelerate model training and boost AI performance without the operational burden. Let’s take a look at the top data annotation companies to hire in 2025, the services they offer, and how to choose the best partner for your AI/ML project.
Table of Contents
1. SunTec.AI
- Location: Laguna Beach, CA, USA
- Average hourly rate: Inquire
- Expertise: Image, Video, and Text Annotation, AI and Chatbot Training Data, Data Entry Services
- Notable clients: NTT, Expedia, Line@
SunTec.AI is a leading data annotation company specializing in image, text, and video annotation to help businesses train high-performing AI models.
With over 25 years of experience and a 99% accuracy rate, they provide scalable, high-quality annotation services backed by ISO certifications and HIPAA-compliant security measures. Their human-in-the-loop approach ensures high-quality labeled data for industries like automotive, healthcare, retail, finance, and more.
One of their clients, a UK-based auto insurance provider, needed precisely labeled vehicle damage images to enhance their AI-powered claims assessment system. The challenge was to differentiate actual damage from shadows, reflections, and poor lighting conditions across 3,000+ images.
SunTec.AI’s team used advanced annotation tools, image processing techniques, and a multi-step QA process to ensure precise damage labeling. As a result, the insurer saw a 40% improvement in damage detection accuracy and 30% faster claims processing, reducing fraud and speeding up customer payouts. SunTec.AI’s expertise in handling complex annotation challenges with precision and scalability makes them a strong partner for AI-driven businesses seeking reliable, high-quality training data.
2. Label Your Data
- Location: Wilmington, DE, USA
- Average hourly rate: Inquire
- Expertise: Labeling Text & Documents, Medical Imaging, 3D Point Cloud, Image Video, Audio, GIS, LLM Fine Tuning, Data Generation, Collection, and Entry
- Notable clients: Yale, The George Washington University, Miami University, ABB
Label Your Data is a trusted data annotation provider specializing in text, image, video, and 3D point cloud annotation. With ISO/IEC 27001:2013 and PCI DSS Level 1 certifications, they ensure secure and compliant data labeling, making them a reliable choice for businesses handling sensitive AI training data.
Known for speed and precision, Label Your Data has delivered 3,000+ annotations in five days, maintaining 90-95% accuracy through semi-automated quality checks. Their adaptive workflows and dedicated teams allow businesses to scale annotation projects effortlessly. Companies like Yale, ABB, and The George Washington University trust their expertise for AI model development.
For businesses seeking fast, high-quality, and secure data annotation, Label Your Data stands out as a scalable and efficient partner.
3. Remote Labeler
- Location: Kyiv, Ukraine
- Average hourly rate: $15/hour
- Expertise: Image, Video, Text, and Audio Annotation
- Industries: Healthcare, Biotech, Education, and more
Remote Labeler helps businesses scale data annotation with speed and accuracy, offering image, video, text, and audio labeling across industries like biotech, healthcare, and education.
With a team of 300+ expert annotators, they provide flexible staffing models, whether companies need full-time specialists, part-time support, or fully managed annotation services. Their 98% accuracy rate and 100% data security compliance ensure high-quality, reliable AI training data.
When a biotechnology research firm in South Korea needed precise drug patent image annotation, Remote Labeler stepped in. The project required annotators with a chemistry background to correctly identify reactions and atomic structures. Using CVAT tools, specialized annotators, and a cross-checking process, they ensured flawless labeling while maintaining fast turnaround times.
In just two weeks, Remote Labeler successfully annotated 20,000 PDF files, improving the client’s AI-driven research capabilities. With their expert workforce, flexible staffing, and commitment to precision, they are a go-to partner for businesses needing scalable, high-quality data annotation services.
4. Femote
- Location: Newark, Delaware, USA
- Average hourly rate: $20/hour
- Expertise: Data Annotation, Data Entry & Cleaning, Data Auditing, Data Annotation Training, Consultancy
- Notable clients: City Detect, Tinga, Tundra, Quest Innovation Lab
Femote is a social impact startup that combines data annotation expertise with economic empowerment. Specializing in data annotation, entry, auditing, and consultancy, they provide high-quality AI training datasets while supporting skilled female professionals from Africa. Their team of over 50 annotators and 20 virtual assistants ensures accurate, timely, and scalable services for businesses building machine learning models or managing data-heavy operations.
Beyond precision, Femote is committed to affordability and flexibility, offering businesses cost-effective outsourcing solutions so they can focus on core AI development.
With a responsive support team and a track record of working with City Detect, Tinga, Tundra, and Quest Innovation Lab, they are a trusted partner for companies needing reliable, human-driven data annotation.
5. Aya Data
- Location: London, UK
- Average hourly rate: $5/hour
- Expertise: Data Annotation Overview, Computer Vision, Natural Language Processing, 3D Annotation
- Notable clients: Label Box, V7 Labs, Alegion
Aya Data is a global AI consulting firm specializing in data annotation, computer vision, NLP, and 3D annotation. With operations across Africa, Europe, and Asia, they bring together top global talent to deliver high-quality, cost-effective AI training data. Their end-to-end solutions go beyond annotation, covering data collection, model development, and AI deployment to support businesses in healthcare, retail, utilities, agriculture, and geospatial technology.
Committed to affordability, security, and quality, Aya Data adheres to ISO, GDPR, HIPAA, and SOC2 standards, ensuring compliance and reliability for AI-driven companies. They have worked with industry leaders like Label Box, V7 Labs, and Alegion, offering scalable AI solutions backed by a team of expert data annotators and AI specialists.
With a strong focus on innovation and collaboration, Aya Data helps businesses develop, optimize, and deploy AI models with precision and efficiency.
6. Infosearch BPO
- Location: Gopalapuram, Chennai, India
- Average hourly rate: Inquire
- Expertise: Bounding Box, Polygon, Cuboid, Geospatial, and Video Annotation, Semantic Segmentation, Autonomous Vehicle, Image Labeling/Tagging
- Notable clients: Bic, CAT, Toshiba Machine, Nippon Paint, Red Bull, University of Washington
Infosearch BPO is a trusted outsourcing provider with nearly two decades of experience in data annotation and AI training data services. They work with global brands like Bic, CAT, and Red Bull, delivering high-precision labeled data for autonomous vehicles, geospatial mapping, and image recognition.
Known for their scalability and accuracy, Infosearch BPO ensures secure, high-quality annotation solutions backed by an ISO 9001:2015 certification. Their team of 400+ professionals provides cost-effective, expert-driven labeling services, making them a reliable partner for businesses needing AI-ready datasets at scale.
7. oworkers
- Location: London, United Kingdom
- Average hourly rate: $4/hour
- Expertise: Image, Video, Audio, and Text Annotation
- Notable clients: Xerox, Amazon, Bosch, TBWA, Wavestone
oworkers is a multilingual BPO company specializing in data annotation, data processing, and content moderation services. With delivery centers in Bulgaria, Egypt, and Madagascar, they offer services in over 25 languages, ensuring flexibility and scalability for diverse business needs.
Their commitment to quality is reflected in their ISO 27001 and GDPR compliance, ensuring data security and adherence to international standards. Over the past decade, oworkers has built a reputation for excellence, serving notable clients like Xerox, Amazon, and Bosch.
By leveraging a skilled in-house workforce and advanced AI tools, oworkers delivers cost-effective solutions tailored to enhance operational efficiency and support the growth of businesses worldwide.
Top Data Annotation Companies Compared
| Company | Hourly Rate | Expertise | Key Strength / Differentiator |
| SunTec.AI | Inquire | Image, Video, Text Annotation, AI Training Data | 25+ years experience, 99% accuracy, ISO-certified |
| Label Your Data | Inquire | Text, Medical Imaging, 3D Point Cloud, GIS | 3,000+ annotations in 5 days, 90-95% accuracy |
| Remote Labeler | $15/hour | Image, Video, Text, Audio Annotation | 98% accuracy, flexible staffing models |
| Femote | $20/hour | Data Annotation, Entry, Auditing, Consultancy | Social impact-driven, employs skilled African women |
| Aya Data | $5/hour | Computer Vision, NLP, 3D Annotation | Global AI solutions, ISO, GDPR, HIPAA compliance |
| Infosearch BPO | Inquire | Bounding Box, Polygon, Semantic Segmentation | 400+ professionals, ISO 9001:2015 certified |
| oworkers | $4/hour | Image, Video, Audio, Text Annotation | Multilingual annotation, 25+ languages |
How To Choose the Right Data Annotation Company
Selecting the right data annotation partner is a strategic decision that directly impacts the performance and reliability of your AI models. Here are the key factors to consider before making a choice:
- Data security and compliance
- Annotation quality and accuracy metrics
- Scalability and speed
- Industry expertise and AI tools
- Pricing transparency and models
Data Security and Compliance
If your project involves sensitive or proprietary data, security should be a top priority. A trustworthy provider must follow global data protection regulations and have strict measures in place to safeguard your datasets.
- Ensure the provider complies with GDPR, HIPAA, or SOC 2 to meet industry security standards.
- Look for ISO 27001 or SOC 2 certification as proof of secure data handling.
- Verify that they implement access controls, encryption protocols, and NDAs to prevent data breaches.
Annotation Quality and Accuracy Metrics
AI models are only as good as the data they are trained on, making annotation quality a non-negotiable factor. Even minor inaccuracies can lead to biased models and poor performance in real-world applications.
- Choose providers that guarantee 98%-99% accuracy in their annotations.
- Ask about their quality control process, including multi-tier QA, human review, and automated validation.
- Look for vendors with domain experts who understand industry-specific nuances, ensuring more precise labeling.
Scalability and Speed
AI projects often require large-scale datasets with quick turnaround times. The right provider should be able to scale seamlessly without compromising quality.
- Opt for a company that offers on-demand workforce scaling to match your project’s evolving needs.
- Ensure they can handle high-volume annotation tasks efficiently without bottlenecks.
- Look for providers with clear SLAs (Service Level Agreements) that define expected turnaround times.
Industry Expertise and AI Tools
Not all annotation providers offer the same services. Some cater to specific industries and have deep expertise in handling specialized datasets. The right company should have experience in your field and access to advanced AI-assisted tools to improve efficiency.
- Check if they have proven experience in your industry (e.g., healthcare, autonomous driving, NLP, finance).
- Look for companies using AI-assisted annotation tools to streamline and enhance labeling accuracy.
- Ensure they are flexible and can work with your preferred annotation platforms and formats.
Pricing Transparency and Models (Hourly, Per Task, Project-Based)
Unexpected costs can derail your budget, so it’s essential to partner with a provider that offers clear and flexible pricing. Understanding their pricing model will help you estimate costs more accurately and avoid hidden fees.
- Ask whether they charge hourly, per task, or on a project basis, depending on your needs.
- Look for volume-based pricing options if your project requires large-scale data annotation.
- Consider providers offering trial projects or free pilots to assess quality before committing.
Best Data Annotation Companies: Final Thoughts
The success of any AI model hinges on the quality of its training data. No matter how advanced your algorithms are, poorly labeled datasets will lead to unreliable outputs, wasted resources, and failed deployments.
If you’re ready to invest in high-quality training data that drives real AI performance, explore these trusted data annotation agencies and find the right fit for your project.
Data Annotation Companies: FAQs
1. What is a data annotation company?
A data annotation company provides precisely labeled datasets for training AI and machine learning models. They specialize in image, video, text, and audio annotation, ensuring AI systems can recognize patterns, make decisions, and improve accuracy.
2. How do I know if I need to outsource data annotation?
If your team lacks the time, expertise, or resources to handle large-scale, high-accuracy labeling, outsourcing is the best option. Professional annotation companies provide scalability, quality assurance, and faster turnaround times, helping AI projects move forward efficiently.
3. What’s the difference between manual and automated data annotation?
Manual annotation is performed by human experts, ensuring high accuracy and handling complex datasets. Automated annotation uses AI-assisted tools for speed and efficiency but may require human validation to maintain quality. The best providers use a hybrid approach to balance speed and precision.
