The process of data annotation and labeling plays a critical role in the supervised training of large language models and other types of data-driven machine-learning models. Since data annotation is both time- and resource-intensive, AI developers often outsource it to specialized providers. In this piece, we will walk you through the top data labeling companies worldwide in 2025.
Best Data Labeling & Annotation Companies 2025
- Cogito TechAppenTELUS InternationalTaskUsiMeritCloudFactorySuperAnnotateAnolytics
1. Cogito Tech
Cogito Tech is a leading data solutions provider specializing in data labeling and annotation services. The company provides a wide range of data annotations for applications across computer vision and natural language processing (NLP) services to train AI and machine learning models. Its solutions extend to fine-tuning generative AI models, such as large language models (LLMs), using techniques such as Reinforcement Learning from Human Feedback (RLHF).
Key Features
Headquartered in Levittown, New York (US), Cogito Tech is the only DAL company to have been recognized in The Financial Times’ ranking as one of the Fastest-Growing Companies in the US (2024 and 2025) and in Everest Group’s Data Annotation and Labeling (DAL) Solutions for AI/ML PEAK Matrix® Assessment 2024.
- Skilled Workforce: Cogito Tech employs subject matter experts from diverse fields to benchmark and validate data across industries while leading annotation projects.Supported Data: The company provides data annotation services across multiple modalities—images, text, audio, and video—to support multimodal AI.Extensive Experience: With over a decade of experience, Cogito Tech has successfully delivered more than 5,000 projects for leading LLM and other AI/ML builders, creating over 30 million AI elements with 13 million person-hours of work.Data Security: Cogito Tech strictly adheres to data regulations including GDPR, CCPA, HIPAA, CFR 21 Part 11, and evolving AI laws such as the EU AI Act, Executive Order on Artificial Intelligence. Its DataSum certification framework brings greater transparency and ethics to AI data sourcing through comprehensive audit trails and metadata insights.Scalability: Cogito’s globally distributed team operates 24/7 and can scale to meet any project’s needs on time.Industries Supported: The company provides customized data annotation services to various industries, such as automotive, healthcare, finance, retail, and geospatial sectors.AI Innovation Hubs: Cogito Tech’s AI Innovation Hubs combine SME-led data annotation, efficient workflow management, and strategic partnership to deliver high-quality training data solutions across AI/ML development, including LLMs, robotics, and agentic AI.
2. Appen
One of the leading data annotation companies, Appen provides diverse, high-quality datasets for building AI and ML in various industries. Headquartered in Sydney, Australia, Appen is a publicly traded company with operations in the US, China, and the Philippines. The platform has been used in thousands of projects, processing and labeling billions of units of data.
Key Features
- Global Workforce: Appen boasts a large, diverse global workforce that includes specialists speaking over 200 languages across continents, delivering culturally relevant and accurate datasets.Comprehensive Annotation Services: Offers end-to-end training data solutions across text, image, audio, video, and point-cloud data for AI applications.Scalable and Flexible Solutions: Executes projects of all sizes in a time-bound manner, making it an ideal platform for companies seeking scalable annotation services.AI-Driven Efficiency: Uses cutting-edge AI tools to enhance labeling accuracy and accelerate workflows.
By using state-of-the-art tools and technologies, Appen provides large-scale and high-quality datasets for applications like NLP, computer vision, LLM, and autonomous systems.
3. TELUS International
TELUS International provides data annotation services for companies around the world. It is a Vancouver, Canada-based IT services company and DAL platform that supports multiple data modalities, including text, audio, video, images, sensor data, and geo-location data.
- Extensive Experience: With more than two decades of experience in AI-related projects, the platform supports more than 100 languages and claims to have delivered more than two billion labels annually.Specialized Global Workforce: Brings together a team of labelers, linguists, and domain experts from different demographics, skills, and expertise for collecting and annotating representative data.AI-Assisted Labeling and Auditing: TELUS’ Ground Truth Studio provides advanced data annotation, featuring automated labeling, project management, and configurable workflows.Supported Data Type and Method: Supports image, video, audio, text, and 3D point cloud datasets and methods, including bounding boxes, cuboids, polylines, and landmarks.
4. TaskUs
TaskUs provides a broad range of data annotation services for computer vision, NLP, and LLM projects. Founded in 2008, the company has a large number of permanent employees and gig workers for data labeling tasks.
Key Features:
- Scalable Solutions: Provides scalable data annotation services with ease for small to large-scale project requirements.Global Workforce: Has a network of highly qualified and well-trained annotators from more than 50 countries .Data Security: Ensures full compliance with relevant data regulations like GDPR, HIPAA, and evolving AI laws such as the EU AI Act for handling sensitive data.Comprehensive Services: Offers data collection, curation, and labeling services, including image, video, audio, and text labeling, as well as generative AI fine-tuning and evaluation.Automation: Leverages AI-enabled platforms to enhance productivity, streamline workflows, improve management, and strengthen security.
5. iMerit
iMerit is an India-based DAL platform that provides a full suite of data annotation and model fine-tuning services by combining automation, subject matter experts, and analytics. Its global workforce boasts ethical sourcing and accurate data annotations.
Features:
- Skilled Workforce: Employs a skilled team of human domain experts and annotators to supervise projects, leveraging their industry experience to create solutions that meet unique project needs.Best-in-Class Tooling: Uses advanced annotation tools for image, text, audio, video, and 3D point cloud data.Multiple Annotation Methods: Supports diverse annotation techniques, such as bounding boxes, polygons, keypoint, semantic segmentation, classification, and text extraction for AI model training across industries like agriculture, automotive, medical, and more.Integration: Its integrated plugins for labeling automation streamline and accelerate the process of data preparation.
6. CloudFactory
CloudFactory is one of the leading players in DAL, known for providing quality training data by leveraging a combination of AI technology and human expertise. Founded in Nepal in 2010, the company claims to have serviced over 700 clients to develop high-performing models and introduce groundbreaking AI solutions.
Features
- AI-Powered Automation: Leverages automation to enhance the quality, speed, and scale of the data annotation process.Custom Workflows: Offers flexible annotation processes to align with clients AI initiatives and unique use case needs.Security and Confidentiality: Meets regulatory requirements by adhering to international standards like ISO 9001:2015, ISO 27001, SOC 2, HIPAA, and GDPR to ensure data integrity and compliance with industry regulations.Experienced Workforce: The team has extensive experience working with AI, backed by 8M hours of data annotation and model fine-tuning.
7. SuperAnnotate
SuperAnnotate’s AI-enabled annotation combined with manual services focuses on industries such as autonomous driving and healthcare, providing quality assurance features for labeling accuracy.
Key Features
- Collaboration: Its single collaboration hub allows all individuals involved in a project to work together, eliminating the need to switch between multiple tools.Enterprise-Grade Security and Compliance: Ensures data protection and regulatory adherence through SOC 2 Type II, ISO/IEC 27001:2022, and compliance with GDPR, CCPA, and HIPAA.Easy to Use: Offers a user-friendly interface.Supported Labeling Methods: Provides tools for object detection, sentiment analysis, categorization, segmentation, object tracking, and speech recognition.
8. Anolytics
Anolytics.ai specializes in data annotation and labeling for training AI models, with a focus on computer vision systems.
- Data Security: Complies with GDPR, SOC 2, and HIPAA data standards to ensure data security and privacy.Supported Data Types: Includes image, text, audio, video, and DICOM formats.Labeling Methods: Uses bounding boxes, cuboids, lines, points, polygons, segmentation, and tools for NLP.Fine-Tuning: SME-led teams provide domain-specific instruction and fine-tuning datasets for LLMs.
Conclusion
With the rapid evolution of AI, selecting the right training data provider is crucial and requires due diligence. Companies building AI models must compare different features such as accuracy, talent or domain experts, scalability, compliance and ethics, and cost to make an informed decision. As AI permeates every aspect of life, data transparency and ethics have become more pressing, directly impacting the trustworthiness, fairness and accountability of AI systems.
This reinforces the need to collaborate with a DAL platform that addresses these challenges through a structured framework for AI data labeling, such as Cogito Tech’s DataSum.
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