Best Data Labeling Software - Page 4

Compare the Top Data Labeling Software as of January 2026 - Page 4

  • 1
    UHRS (Universal Human Relevance System)
    When you need transcription, data validation, classification, sentiment analysis, or other related tasks, UHRS can give you what you need. We provide human intelligence to train machine learning models to help you solve some of your most challenging problems. We make it easy for judges to access UHRS anywhere, at any time. All that’s needed is an internet connection, and judges are good to go. Work on tasks like video annotation in just a few minutes. With UHRS, you can classify thousands of images quickly and easily. Train your products and tools with improved image detection, boundary recognition, and more with high quality annotated image data. Classify images, semantic segmentation, object detection. Validating audio to text, conversation, and relevance. Identify sentiment of a tweet, and document classification. Ad hoc data collection tasks, information correction/moderation, and survey.
  • 2
    Klatch

    Klatch

    Klatch Technologies

    Klatch Technologies is a global data services provider helping companies and institutions collect, annotate, and process data. We assist Artificial Intelligence companies, research institutions, Machine Learning or Computer Vision projects in data labeling, data collection, content moderation, and other data projects. Our Specialists provide rapid scalability, precise accuracy, swift turnaround time, multilingual capability, and data security at a low-cost. - Data Annotation Services: Image Annotation Video Annotation Search Relevance Text NLP Annotation Text Classification Sentiment Analysis Image Segmentation LIDAR Annotation - Data Collection Services: Healthcare Training Data Chatbot Training Data & all other data collection needs - IT Managed Services: Content Moderation Ecommerce Data Categorization
  • 3
    CrowdAI

    CrowdAI

    CrowdAI

    Systematically manage the end-to-end AI pipeline, from raw data to production. Build custom models that are sensitive to your operations, powering competitive advantage. Build a diverse AI workforce that can easily build and deploy AI, all without a single line of code. Put AI into action anywhere, on the factory floor, in outer space, or anywhere in between. Invest in a proven platform, deployed in some of the most data-sensitive environments. Assisted user flows to walk you through creating your first model. Rather than siloing enterprise data across cloud providers and hardware devices, centralize all media into a single, curated library that is optimized for discoverability.
  • 4
    DataForce

    DataForce

    DataForce

    DataForce is a global data collection and labeling platform that combines technology with a diverse network of over one million data contributors, scientists, and engineers. It offers companies in technology, automotive, life sciences, and other industries secure and reliable AI services for exceptional structured data and customer experiences. As part of the TransPerfect family of companies, DataForce provides a range of services, including data collection, data annotation, data relevance and rating, chatbot localization, content moderation, transcription, user studies, generative AI training, business process outsourcing, and bias mitigation. The DataForce platform is a proprietary solution developed in-house by TransPerfect for various types of data-oriented projects with a focus on AI and machine learning applications. Its capabilities include data annotation, data collection, and community management, supporting and improving relevance models, accuracy, and recall.
  • 5
    Labelbox

    Labelbox

    Labelbox

    The training data platform for AI teams. A machine learning model is only as good as its training data. Labelbox is an end-to-end platform to create and manage high-quality training data all in one place, while supporting your production pipeline with powerful APIs. Powerful image labeling tool for image classification, object detection and segmentation. When every pixel matters, you need accurate and intuitive image segmentation tools. Customize the tools to support your specific use case, including instances, custom attributes and much more. Performant video labeling editor for cutting-edge computer vision. Label directly on the video up to 30 FPS with frame level. Additionally, Labelbox provides per frame label feature analytics enabling you to create better models faster. Creating training data for natural language intelligence has never been easier. Label text strings, conversations, paragraphs, and documents with fast & customizable classification.
  • 6
    Innodata

    Innodata

    Innodata

    We Make Data for the World's Most Valuable Companies Innodata solves your toughest data engineering challenges using artificial intelligence and human expertise. Innodata provides the services and solutions you need to harness digital data at scale and drive digital disruption in your industry. We securely and efficiently collect & label your most complex and sensitive data, delivering near-100% accurate ground truth for AI and ML models. Our easy-to-use API ingests your unstructured data (such as contracts and medical records) and generates normalized, schema-compliant structured XML for your downstream applications and analytics. We ensure that your mission-critical databases are accurate and always up-to-date.
  • 7
    Amazon Mechanical Turk
    Amazon Mechanical Turk (MTurk) is a crowdsourcing marketplace that makes it easier for individuals and businesses to outsource their processes and jobs to a distributed workforce who can perform these tasks virtually. This could include anything from conducting simple data validation and research to more subjective tasks like survey participation, content moderation, and more. MTurk enables companies to harness the collective intelligence, skills, and insights from a global workforce to streamline business processes, augment data collection and analysis, and accelerate machine learning development. While technology continues to improve, there are still many things that human beings can do much more effectively than computers, such as moderating content, performing data deduplication, or research. Traditionally, tasks like this have been accomplished by hiring a large temporary workforce, which is time consuming, expensive and difficult to scale, or have gone undone.