# Best Data Labeling Software - Page 6 ## How Many Data Labeling Software Products Does G2 Track? **Total Products under this Category:** 116 ### Category Stats (Aug 2026) - **Average Rating:** 4.49/5 (↓0.01 vs Jul 2026) The average rating of products in this category, based on all submitted ratings - **Top Trending Product:** Datature (+0.08%) - Among all products in this category, Datature recorded the largest rating increase compared to last month _Last updated: August 07, 2026_ ## How Does G2 Rank Data Labeling Software Products? **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 1,800+ Authentic Reviews - 116+ Products - Unbiased Rankings G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category. ## G2 Grid® for Data Labeling Software ![G2 Grid® for Data Labeling Software plotting products by satisfaction and market presence](https://www.g2.com/categories/data-labeling/grids.png?focus%5B%5D=128515&focus%5B%5D=125020&focus%5B%5D=168222&focus%5B%5D=78925&focus%5B%5D=87452&focus%5B%5D=126287&focus%5B%5D=125450&focus%5B%5D=142739) Highlighted products: SuperAnnotate, Roboflow, Encord, Labelbox, Amazon Sagemaker Ground Truth, V7 Darwin, Datasaur, and Sama. Underlying data: [Grid® JSON](https://www.g2.com/categories/data-labeling/grids.json?focus%5B%5D=superannotate&focus%5B%5D=roboflow&focus%5B%5D=encord&focus%5B%5D=labelbox&focus%5B%5D=amazon-sagemaker-ground-truth&focus%5B%5D=v7-darwin&focus%5B%5D=datasaur&focus%5B%5D=sama) **Sponsored** ### Amazon SageMaker Amazon SageMaker is a fully managed service that enables data scientists and developers to build, train, and deploy machine learning (ML) models at scale. It provides a comprehensive suite of tools and infrastructure, streamlining the entire ML workflow from data preparation to model deployment. With SageMaker, users can quickly connect to training data, select and optimize algorithms, and deploy models in a secure and scalable environment. Key Features and Functionality: - Integrated Development Environments (IDEs): SageMaker offers a unified, web-based interface with built-in IDEs, including JupyterLab and RStudio, facilitating seamless development and collaboration. - Pre-built Algorithms and Frameworks: It includes a selection of optimized ML algorithms and supports popular frameworks like TensorFlow, PyTorch, and Apache MXNet, allowing flexibility in model development. - Automated Model Tuning: SageMaker can automatically tune models to achieve optimal accuracy, reducing the time and effort required for manual adjustments. - Scalable Training and Deployment: The service manages the underlying infrastructure, enabling efficient training of models on large datasets and deploying them across auto-scaling clusters for high availability. - MLOps and Governance: SageMaker provides tools for monitoring, debugging, and managing ML models, ensuring robust operations and compliance with enterprise security standards. Primary Value and Problem Solved: Amazon SageMaker addresses the complexity and resource-intensive nature of developing and deploying ML models. By offering a fully managed environment with integrated tools and scalable infrastructure, it accelerates the ML lifecycle, reduces operational overhead, and enables organizations to derive insights and value from their data more efficiently. This empowers businesses to innovate rapidly and implement AI solutions without the need for extensive in-house expertise or infrastructure management. [Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list_llm&secure%5Bcategory_id%5D=2361&secure%5Bchosen_at%5D=2026-08-15T05%3A12%3A08Z&secure%5Bdisplayable_resource_id%5D=2361&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=2361&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=52115&secure%5Bresource_id%5D=2361&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fdata-labeling%3Fpage%3D6&secure%5Btoken%5D=9fa1789c95655f58b122a23a47f078e50c779af46f1bd83a91fc20483919c3f7&secure%5Burl%5D=https%3A%2F%2Faws.amazon.com%2Fsagemaker%2F%3Ftrk%3De054ba95-b51d-4594-98bc-aa0239b1797a%26sc_channel%3Ddisplay%2Bads&secure%5Burl_type%5D=custom_url) ### [Foresight Training Data](https://www.g2.com/products/foresight-training-data/reviews) Lightning Rod Labs is the data engine behind the next generation of AI models and products, giving builders the tools to transform messy, real-world data into model-ready training datasets. Teams use Foresight Data to automatically generate label datasets from both public sources and their own proprietary data. Eliminating manual annotation and accelerating AI workflows from prototyping to deployment. From AI startups to Enterprise research teams, builders rely on Lightning Rod Labs to turn complex, unstructured data into a durable competitive advantage. We’re making training data as automated, scalable, and adaptive as the models and products it powers. #### Who Is the Company Behind Foresight Training Data? - **Seller:** [Lightning Rod Labs](https://www.g2.com/sellers/lightning-rod-labs) - **HQ Location:** New York City, US - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=d88cb78c659e09ac7efb23bd4bc290f803394384c15c9ad5b584b8b750b517e7&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Flightningrod%2F&secure%5Burl_type%5D=linkedin_company_website) 6 employees on LinkedIn® ### [Frekil](https://www.g2.com/products/frekil/reviews) Accelerate Real World Evidence Generation from months to minutes for internal hypothesis testing from your own data #### Who Is the Company Behind Frekil? - **Seller:** [Frekil](https://www.g2.com/sellers/frekil) - **Year Founded:** 2026 - **HQ Location:** San-Francisco, US - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=83faff224ca9fa87ee044da7f1d7729622336ed8a75906015b57d5bf972fd2ba&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Ffrekil%2F&secure%5Burl_type%5D=linkedin_company_website) 3 employees on LinkedIn® ### [Getmarkup](https://www.g2.com/products/getmarkup/reviews) GetMarkup is an advanced online annotation tool designed to transform unstructured text into structured data, facilitating natural language processing (NLP) and machine learning (ML) applications. By leveraging the capabilities of GPT-4, it streamlines the annotation process, offering predictive suggestions that enhance workflow efficiency and reduce manual effort. Key Features and Functionality: - AI-Powered Annotations: Utilizes GPT-4 to provide predictive annotation suggestions, accelerating the data structuring process. - Ontology Integration: Supports both standard and custom ontologies, enabling precise and context-aware annotations. - User-Friendly Interface: Designed with an intuitive interface, making it accessible to users with varying levels of technical expertise. - Scalability: Offers flexible pricing plans to accommodate projects of all sizes, from individual users to large organizations. - Data Security: Implements industry-standard encryption protocols and strict access controls to ensure data privacy and security. Primary Value and Problem Solved: GetMarkup addresses the challenge of converting unstructured text into structured data, a critical step in NLP and ML projects. By automating and enhancing the annotation process, it significantly reduces the time and effort required for data preparation, leading to more efficient project workflows and improved model accuracy. Its integration with various ontologies ensures that annotations are contextually relevant, thereby enhancing the quality of the structured data produced. #### Who Is the Company Behind Getmarkup? - **Seller:** [Markup](https://www.g2.com/sellers/markup-8f4a3328-b326-4829-b3a6-18f2e38fb22d) - **HQ Location:** N/A - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=7886df2ed926834e5eb248c77dcfa8e5c815d3ab1f0fe3132ced0dba45868834&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2FNo-Linkedin-Presence-Added-Intentionally-By-DataOps&secure%5Burl_type%5D=linkedin_company_website) 1 employees on LinkedIn® ### [Humanloop](https://www.g2.com/products/humanloop/reviews) Humanloop is the LLM evals platform for enterprises. Teams at Gusto, Vanta and Duolingo use Humanloop to ship reliable AI products. We enable you to adopt best practices for prompt management, evaluation and observability. #### Who Is the Company Behind Humanloop? - **Seller:** [Humanloop](https://www.g2.com/sellers/humanloop) - **Year Founded:** 2020 - **HQ Location:** London, GB - **Twitter:** @humanloop 9,707 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=e5785e37ae22cff53f31038e802d83ec114613fbbbcdc3984df3349be88abc5e&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fhumanloop%2F&secure%5Burl_type%5D=linkedin_company_website) 13 employees on LinkedIn® ### [Intellabel](https://www.g2.com/products/intellabel/reviews) Intellabel is an end-to-end AI data platform that takes computer vision and multimodal teams from raw data to production-ready models in one workspace. It unifies data labeling, dataset management, model training, and MLOps, so teams stop stitching separate tools together. AI pre-labels your data while humans verify the rest, cutting annotation time while keeping quality high. Clients ship accurate AI models faster, with full visibility and control across the entire AI lifecycle #### Who Is the Company Behind Intellabel? - **Seller:** [Intellabel](https://www.g2.com/sellers/intellabel) - **Company Website:** intellabel.com - **Year Founded:** 2019 - **HQ Location:** Bangalore, IN - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=752e3af6deb86074e4cd7fdf7841f02fff4f658552f5c4b1db8ea0925856b208&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fintellabel%2F&secure%5Burl_type%5D=linkedin_company_website) 81 employees on LinkedIn® ### [Isahit](https://www.g2.com/products/isahit/reviews) Isahit is an ethical on-demand workforce management platform that specializes in scaling AI and data projects through human-in-the-loop processes. By providing services such as data labeling, natural language processing, image and video annotation, and data processing, Isahit ensures high-quality, bias-free AI development. The platform uniquely combines technological expertise with social impact by empowering women in developing countries, offering them flexible digital work opportunities and bridging the digital divide. Key Features and Functionality: - Data Labeling and Annotation: Offers comprehensive services in image, video, and text annotation to train AI models effectively. - Natural Language Processing (NLP): Provides tools for tasks like named entity recognition and text classification, enhancing language model capabilities. - Data Processing Services: Assists with tasks such as data entry, cleaning, and management, streamlining back-office operations. - Human-in-the-Loop (HITL) Integration: Ensures AI models are fine-tuned with human oversight, improving accuracy and reducing biases. - Ethical Workforce Management: Empowers women across multiple continents by offering flexible, remote digital work opportunities, promoting social inclusion and financial independence. Primary Value and User Solutions: Isahit addresses the critical need for high-quality, unbiased data in AI development by integrating human expertise into the data processing pipeline. This approach not only enhances the accuracy and fairness of AI models but also provides scalable solutions for businesses across various sectors, including automotive, healthcare, finance, and e-commerce. Additionally, by focusing on ethical outsourcing, Isahit contributes to social impact by creating meaningful employment opportunities for women in developing countries, thereby fostering economic empowerment and bridging the digital divide. #### Who Is the Company Behind Isahit? - **Seller:** [Isahit](https://www.g2.com/sellers/isahit) - **Year Founded:** 2017 - **HQ Location:** Paris, FR - **LinkedIn® Page:** [fr.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=b9783718b66b49ce66a97b6612a7286ca43d886802ec4b09955105b9e8049943&secure%5Burl%5D=https%3A%2F%2Ffr.linkedin.com%2Fcompany%2Fisahit&secure%5Burl_type%5D=linkedin_company_website) 285 employees on LinkedIn® ### [KawniX](https://www.g2.com/products/kawnix/reviews) KawniX is an AI-powered platform specializing in geospatial data annotation and satellite image processing. It enables businesses and organizations to transform raw satellite imagery into actionable insights, facilitating informed decision-making across various industries. Key Features and Functionality: - Automated Label Suggestions: Utilizes artificial intelligence to propose boundaries, objects, or features based on prior annotations, significantly reducing the time required for large dataset labeling. - Support for Various Annotation Types: Offers flexibility with bounding boxes, polygons, segmentation masks, and classification tags to meet diverse project needs. - Cloudless Satellite Imagery Access: Provides clear, cloud-free satellite images updated every five days, ensuring annotations are based on current and accurate data. - User-Friendly Interface: Operates directly in the browser, allowing users to access and analyze spatial datasets through simple natural language queries. - Seamless Workflow Integration: Facilitates collaboration across departments, enabling teams to annotate and analyze images efficiently. Primary Value and Solutions Provided: KawniX addresses the challenge of converting complex satellite imagery into usable data by combining AI-driven automation with human accuracy. This approach accelerates the annotation process, enhances data precision, and supports various applications, including: - Agriculture: Monitoring crop health, irrigation, and soil conditions through annotated satellite images. - Urban Planning: Mapping infrastructure and modeling traffic flow with accurately labeled geospatial data. - Environmental Protection: Tracking land use and monitoring ecosystems to prevent illegal activities. - Disaster Management: Assessing damage and coordinating recovery efforts using annotated imagery. By streamlining the geospatial data annotation process, KawniX empowers organizations to make data-driven decisions with confidence and efficiency. #### Who Is the Company Behind KawniX? - **Seller:** [KawniX](https://www.g2.com/sellers/kawnix) - **HQ Location:** N/A - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=7886df2ed926834e5eb248c77dcfa8e5c815d3ab1f0fe3132ced0dba45868834&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2FNo-Linkedin-Presence-Added-Intentionally-By-DataOps&secure%5Burl_type%5D=linkedin_company_website) 1 employees on LinkedIn® ### [Kognic](https://www.g2.com/products/kognic/reviews) Kognic is the leader in autonomy data annotation, delivering the world's most productive platform for multi-modal sensor-fusion data. Purpose-built for cameras, LiDAR, radar, and temporal streams, Kognic helps autonomy teams accelerate development with premium quality and high-throughput workflows. Our unique advantage combines three elements: People — domain experts and a scalable global workforce operating under strict ethical standards; Platform — designed to minimize human effort, integrate automation, and optimize productivity; Processes — proven workflows for quality assurance, scale, and predictability. Together, this makes Kognic the price leader in autonomy data annotation — no one delivers more annotated autonomy data per dollar. Trusted by enterprise customers across the U.S., Europe, China, and Japan, Kognic has delivered over 100 million annotations with full ISO, SOC2, and TISAX certifications. We support flexible deployment models — cloud (SaaS), on-premise, or hybrid — and seamlessly integrate with customer ML pipelines, cloud storage (AWS, Azure, GCP), and frameworks like PyTorch and TensorFlow. From bounding boxes to trajectory evaluation, intent judging, and clip curation, Kognic adapts workflows to meet emerging autonomy needs. We evolve with the frontier of Physical AI, ensuring customers get the most annotated autonomy data for their budget. #### Who Is the Company Behind Kognic? - **Seller:** [Kognic](https://www.g2.com/sellers/kognic) - **Year Founded:** 2018 - **HQ Location:** Gothenburg, SE - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=9b11c6a3afd09c05dacff0b7bd22589f2abad0e047eab64dd9e5077186000bd6&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fkognic%2F&secure%5Burl_type%5D=linkedin_company_website) 107 employees on LinkedIn® ### [Label AI's Aria](https://www.g2.com/products/label-ai-s-aria/reviews) Aria, developed by Label AI, is an advanced data annotation platform that integrates AI-driven automation with client-in-the-loop customization. This combination significantly enhances the speed, scalability, and accuracy of processing perception data, all while reducing traditional annotation costs. Key Features and Functionality: - AI-Powered Annotation: Utilizes cutting-edge AI algorithms to automate or semi-automate labeling tasks, improving both the speed and precision of data annotation. - Client in the Loop: Allows clients to actively participate in the annotation process, ensuring outcomes are personalized and aligned with specific project objectives, fostering collaboration and customization. - Visual Project Control: Provides tools to visualize the data production process, moving away from opaque operations. Features include one-click workflow positioning and real-time online acceptance. - Bidirectional Data Output Capability: Supports JSON-MASK bi-directional data export in panoramic semantics split mode, enabling structured data output in two different formats from a single annotation effort. - Full Data Format Adaptation: Supports a wide range of data formats, including images (JPEG, GIF, PNG, BMP), point cloud data (PCD, BIN, PLY), and videos. Export capabilities include formats such as JSON, XML, CSV, and XLS. - Customizable Workflows: Allows for the personalization of task parameters to align annotation tasks with precise project requirements, maximizing operational efficiency. - Quality Assurance: Incorporates built-in quality control mechanisms and rigorous processes to ensure the highest standards of accuracy and relevance in the annotated data. - Varied Data Types: Supports annotation across diverse data types, including text, images, video, documents, and audio, enabling seamless handling of different data forms. Primary Value and User Solutions: Aria addresses the challenges of traditional data annotation by offering a platform that combines AI automation with client collaboration. This approach not only accelerates the annotation process but also ensures that the data produced is accurate, relevant, and tailored to specific project needs. By supporting a wide array of data formats and providing customizable workflows, Aria offers flexibility and scalability, making it an ideal solution for enterprises seeking efficient and cost-effective data annotation services. #### Who Is the Company Behind Label AI's Aria? - **Seller:** [Labelai](https://www.g2.com/sellers/labelai) - **HQ Location:** San Francisco , US - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=fd13b0f421dfb07876202cf27b7713defd0cf37c857c574c183179d4a0c249cc&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Flabel-ai&secure%5Burl_type%5D=linkedin_company_website) 6 employees on LinkedIn® ### [Labelforce](https://www.g2.com/products/labelforce/reviews) Labelforce AI is a premier data labeling service provider with over a decade of experience in delivering high-quality, customized annotation solutions for artificial intelligence (AI) applications. Specializing in building fully managed data labeling teams, Labelforce AI caters to a diverse range of industries, including computer vision, generative AI, and custom solutions, ensuring that clients receive precise and scalable data annotation services tailored to their specific project requirements. Key Features and Functionality: - Fully Managed Teams: Labelforce AI handles the entire data annotation pipeline, from recruiting specialized data labelers to day-to-day management, allowing clients to focus on their core AI development tasks. - Expertise Across Domains: With a network of over 600 in-office data labeling specialists, Labelforce AI provides teams with the precise skill sets needed for unique projects, ensuring high-quality data for AI training. - Flexible Tooling: The company supports a wide range of data annotation tools, including both paid and open-source platforms, as well as custom tools, offering flexibility to integrate seamlessly into existing workflows. - Data Security: Labelforce AI maintains the highest level of data privacy and security by granting labelers access to clients' data labeling tools without directly handling the data, ensuring confidentiality and compliance. - Global Reach: Leveraging a global recruitment and payment infrastructure, Labelforce AI can hire labelers in nearly any country, providing clients with access to a diverse talent pool. Primary Value and Solutions Provided: Labelforce AI addresses the critical need for high-quality, accurately labeled data in AI model training. By offering customized, fully managed data labeling teams, the company enables clients to scale their AI initiatives efficiently without compromising on data quality. This approach ensures that AI models are trained with precise and reliable data, leading to improved performance and more accurate outcomes. Labelforce AI's commitment to flexibility, security, and expertise makes it a trusted partner for organizations seeking to enhance their AI capabilities through superior data annotation services. #### Who Is the Company Behind Labelforce? - **Seller:** [Labelforce](https://www.g2.com/sellers/labelforce) - **Year Founded:** 2020 - **HQ Location:** Singapore, SG - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=b2eae5ce4391829e778a9f6f09fd78cb1b921ba4c4518e98d5e37eaaf8fc8d98&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Flabelforce-ai%2F&secure%5Burl_type%5D=linkedin_company_website) 1 employees on LinkedIn® ### [Learning Spiral AI](https://www.g2.com/products/learning-spiral-ai/reviews) Learning Spiral AI is a trusted data annotation partner empowering AI and ML teams across the globe to build smarter, faster, and more accurate computer vision systems. With over 300+ skilled annotators and a proven track record in delivering high-quality labeled datasets, we specialize in human-in-the-loop annotation for complex visual data—ranging from images and videos to LiDAR, medical scans, satellite imagery, and more. Our mission is to streamline the data pipeline for companies working in autonomous vehicles, smart surveillance, agriculture, medical imaging, geospatial analytics, and retail AI and other fields. Whether you're training your first computer vision model or scaling to production, we adapt quickly with flexible workflows, competitive pricing, and domain-trained resources. We operate with a strong focus on: Accuracy: Every dataset goes through a strict QA process designed to exceed industry benchmarks. Tool Flexibility: We work on industry-standard tools and also integrate seamlessly with your in-house platforms. Speed & Scalability: Ramp up annotation teams quickly without compromising quality—ideal for startups and enterprises alike. Free Pilot Projects: We offer a no-commitment pilot to demonstrate our quality before scaling further. Learning Spiral AI has helped companies reduce annotation costs by up to 40%, improve model accuracy, and accelerate time-to-market by weeks. Our client-centric approach and transparent processes have made us the preferred annotation partner for AI-driven innovation. If you're looking to turn raw visual data into reliable, production-ready datasets—Learning Spiral AI is ready to collaborate. #### Who Is the Company Behind Learning Spiral AI? - **Seller:** [Learning Spiral AI](https://www.g2.com/sellers/learning-spiral-ai) - **Year Founded:** 1999 - **HQ Location:** Kolkata, IN - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=47354afa25d94d2815b2d0c257db239ade61155f05e836bdb7c940debb7be3f5&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Flearningspiralai&secure%5Burl_type%5D=linkedin_company_website) 38 employees on LinkedIn® ### [Lodestar](https://www.g2.com/products/lodestar/reviews) The world’s first real-time active learning data annotation platform to accelerate high-quality dataset and computer vision model creation. Label up to 10 hours of video in a single project. Lodestar is a complete management suite for developing computer vision models from video data. Our unique real-time integrated tools can help create production models 4x faster than traditional AI workflows. #### Who Is the Company Behind Lodestar? - **Seller:** [Lodestar](https://www.g2.com/sellers/lodestar) - **Year Founded:** 2019 - **HQ Location:** Cupertino, US - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=b143eb312da847e96e11c737ece25db865cb6007bba27ea7e2d118026b350ef8&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F40851032&secure%5Burl_type%5D=linkedin_company_website) 14 employees on LinkedIn® ### [Luel](https://www.g2.com/products/luel/reviews) Luel is an AI training data marketplace that connects enterprises with contributors to source high-quality, rights-cleared multimodal datasets essential for developing and refining AI models. By facilitating the collection and licensing of video, audio, and image data, Luel accelerates AI development while providing content creators with opportunities to monetize their media. Key Features and Functionality: - Curated Datasets: Enterprises can access a catalog of pre-collected, quality-verified datasets ready for immediate use, streamlining the AI training process. - Custom Data Collection: Organizations can request bespoke datasets tailored to specific requirements, ensuring relevance and precision in training data. - Enterprise Security: Luel employs bank-level encryption and adheres to compliance standards such as SOC 2 and GDPR, safeguarding data integrity and confidentiality. - Instant Payouts for Contributors: Content creators receive payments within 24-48 hours after approval, facilitated through platforms like Venmo or Stripe, incentivizing the provision of high-quality data. - Global Opportunities: The platform enables contributors worldwide to participate, offering flexibility and accessibility regardless of location. - User-Friendly Upload Process: A simple drag-and-drop interface with automatic quality checks and duplicate detection ensures a seamless experience for contributors. Primary Value and User Solutions: Luel addresses the critical need for diverse, high-quality training data in AI development by providing a reliable source of rights-cleared datasets. For enterprises, this means accelerated model training and deployment with data that meets stringent compliance and quality standards. For contributors, Luel offers a platform to monetize their content, turning everyday actions into income while supporting the advancement of AI technologies. #### Who Is the Company Behind Luel? - **Seller:** [Luel](https://www.g2.com/sellers/luel) - **Year Founded:** 2025 - **HQ Location:** San Francisco, US - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=5a64ceebe012388d0d0a7d32c5ece4a4a683da3e1079961504aac7f081aa64a0&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fluel&secure%5Burl_type%5D=linkedin_company_website) 3,155 employees on LinkedIn® ### [manot](https://www.g2.com/products/manot/reviews) manot is a fast-growing deep-tech startup committed to solving one of the most challenging aspects of data preprocessing-automated annotation of aerial images and videos. At manot, we strive to provide quality training data to accelerate AI and machine learning development by following our vision - empowering industries with meaningful aerial data. Our team is composed of data and computer science experts with years of experience developing models that assist companies in managing and distributing data by utilizing AI-based solutions. #### Who Is the Company Behind manot? - **Seller:** [manot](https://www.g2.com/sellers/manot) - **HQ Location:** N/A - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=7886df2ed926834e5eb248c77dcfa8e5c815d3ab1f0fe3132ced0dba45868834&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2FNo-Linkedin-Presence-Added-Intentionally-By-DataOps&secure%5Burl_type%5D=linkedin_company_website) 1 employees on LinkedIn® ### [MD AI Annotator](https://www.g2.com/products/md-ai-annotator/reviews) MD.ai Annotator is a comprehensive platform designed to facilitate the creation of high-quality labeled datasets and the development of AI-driven clinical workflows. It enables medical professionals and researchers to efficiently annotate medical images, deploy and validate AI models, and integrate these models into clinical practice. Key Features and Functionality: - Native DICOM Support: Built to support the DICOM standard, the platform accommodates most DICOM imaging modalities. Users can create datasets through direct uploads, cloud storage connections, or via the DICOM C-STORE protocol. Additionally, it supports non-DICOM images (JPEG, PNG, TIFF) and videos (MP4, AVI, MOV) in custom patient-centric file structures. - FDA 510(k)-Cleared Viewer: The web-based DICOM viewer is FDA 510(k)-cleared, enabling clinical image interpretation, review, annotation, and reporting. It supports various modalities, standard zoom/pan/windowing, hanging protocols, multiplanar reconstruction, and measurement tools, fully integrated with annotation tools. - Scalability: The autoscaling cloud infrastructure allows seamless scaling to millions of exams, terabytes of data, and thousands of concurrent users. The user management system provides fine-grained data access control and distributed labeling task assignments. - AI-Assisted Annotation and Model Deployment: Users can deploy models and run distributed inference on their data, utilizing models for pre-annotation or AI-assisted annotation. The platform supports federated validation across multiple sites without data sharing. - Built-in AI Tools: The platform offers AI-powered mask segmentation tools for efficient annotation, as well as built-in PHI detection and de-identification tools to prevent sensitive data leakage. - Developer APIs: Flexible APIs, including a CLI tool and Python client library, enable programmatic project management and control. Primary Value and User Solutions: MD.ai Annotator addresses the critical need for efficient and accurate annotation of medical imaging data, a foundational step in developing reliable AI models for clinical applications. By providing a scalable, secure, and user-friendly platform, it empowers medical professionals and researchers to build high-quality datasets, deploy and validate AI models, and integrate these models into clinical workflows. This accelerates the development and adoption of AI in medicine, ultimately enhancing patient care and outcomes. #### Who Is the Company Behind MD AI Annotator? - **Seller:** [MD AI](https://www.g2.com/sellers/md-ai) - **HQ Location:** New York, US - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=32bf7eb97841ce2e04ddb631a9ed8bf641344af3c2fe405f31003e0a5e3552ff&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fmdai%2F&secure%5Burl_type%5D=linkedin_company_website) 6 employees on LinkedIn® - [‹ Prev ‹ Prev](/categories/data-labeling?order=g2_score&page=5#product-list) - [1](/categories/data-labeling?order=g2_score#product-list) - [2](/categories/data-labeling?order=g2_score&page=2#product-list) - [3](/categories/data-labeling?order=g2_score&page=3#product-list) - [4](/categories/data-labeling?order=g2_score&page=4#product-list) - [5](/categories/data-labeling?order=g2_score&page=5#product-list) - 6 - [7](/categories/data-labeling?order=g2_score&page=7#product-list) - [8](/categories/data-labeling?order=g2_score&page=8#product-list) - [Next › Next ›](/categories/data-labeling?order=g2_score&page=7#product-list) Spotlight Categories [Quality Management Systems (QMS)](https://www.g2.com/categories/quality-management-qms) [E-commerce Fraud Protection Software](https://www.g2.com/categories/e-commerce-fraud-protection) [SEO Tools](https://www.g2.com/categories/seo-tools) [HCM Software](https://www.g2.com/categories/hcm-software) [Zero Trust Networking Software](https://www.g2.com/categories/zero-trust-networking) Similar Categories - [Active Learning Tools](/categories/active-learning-tools) - [Agentic AI](/categories/agentic-ai) - [AI Avatar Generators](/categories/ai-avatar-generators) - [AI Gateways](/categories/ai-gateways) - [AI Governance Tools](/categories/ai-governance-tools) - [AI Note-Taking Software](/categories/ai-note-taking-software) - [AI Orchestration](/categories/ai-orchestration) - [AI Proposal Generator Tools](/categories/ai-proposal-generator-tools) - [AI Search Visibility Optimization Tools](/categories/ai-search-visibility-optimization-tools) - [AI Security Posture Management (AI-SPM) Tools](/categories/ai-security-posture-management-ai-spm-tools) - [AI Security Solutions](/categories/ai-security-solutions) - [AI Storyboard Generators](/categories/ai-storyboard-generators) - [AI Voice Assistants](/categories/ai-voice-assistants) - [AI Voice Dictation](/categories/ai-voice-dictation) - [AI Writing Assistant](/categories/ai-writing-assistant) [Browse Data Labeling Themes](/categories/data-labeling/themes) ![Bijou Barry](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Bijou Barry") BB Researched and written by [Bijou Barry](https://research.g2.com/insights/author/bijou-barry) Updated April 9, 2026 Data labeling software helps data science and machine learning teams source, manage, annotate, and classify unstructured data, including text, images, videos, audio, and PDFs, into labeled datasets that create efficient training data pipelines for building and improving AI and ML models. ### Core Capabilities of Data Labeling Software To qualify for inclusion in the Data Labeling category, a product must: - Integrate a managed workforce and/or data labeling service - Ensure labels are accurate and consistent - Give the user the ability to view analytics that monitor the accuracy and speed of labeling - Allow annotated data to be integrated into data science and machine learning platforms to build machine learning models ### Common Use Cases for Data Labeling Software ML engineers, data scientists, and AI teams use data labeling tools to build high-quality training datasets across a wide range of application types. Common use cases include: - Annotating images, video, and text for computer vision, NLP, and speech recognition model training - Fine-tuning and evaluating large language models (LLMs) with human-labeled feedback data - Building training pipelines for object detection, named entity recognition, and sentiment analysis applications ### How Data Labeling Software Differs from Other Tools Data labeling is a foundational building block of the AI development lifecycle, distinct from the downstream tools it feeds. It integrates with [generative AI software](https://www.g2.com/categories/generative-ai), [MLOps platforms](https://www.g2.com/categories/mlops-platforms), [data science and machine learning platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms), [LLM software](https://www.g2.com/categories/large-language-models-llms), and [active learning tools](https://www.g2.com/categories/active-learning-tools) to support the full model development pipeline. ### Insights from G2 on Data Labeling Software Based on category trends on G2, labeling accuracy controls and workforce management features stand out as standout capabilities. Faster training data pipeline construction and improved model accuracy stand out as primary outcomes of adoption. Show More