Best Data Labeling Software for Amazon Web Services (AWS)

Compare the Top Data Labeling Software that integrates with Amazon Web Services (AWS) as of October 2025

This a list of Data Labeling software that integrates with Amazon Web Services (AWS). Use the filters on the left to add additional filters for products that have integrations with Amazon Web Services (AWS). View the products that work with Amazon Web Services (AWS) in the table below.

What is Data Labeling Software for Amazon Web Services (AWS)?

Data labeling software is a tool that assists in the organization and categorization of large datasets. Data labeling tools enable data to be labeled with relevant tags depending on the purpose such as for machine learning, image annotation, or text classification. Data labeling software can also assist in categorizing input from customers so businesses can better understand their needs and preferences. The software typically comes with different features such as automated labeling, collaboration tools, and scaleable solutions to handle larger datasets. Compare and read user reviews of the best Data Labeling software for Amazon Web Services (AWS) currently available using the table below. This list is updated regularly.

  • 1
    Amazon SageMaker
    Amazon SageMaker is an advanced machine learning service that provides an integrated environment for building, training, and deploying machine learning (ML) models. It combines tools for model development, data processing, and AI capabilities in a unified studio, enabling users to collaborate and work faster. SageMaker supports various data sources, such as Amazon S3 data lakes and Amazon Redshift data warehouses, while ensuring enterprise security and governance through its built-in features. The service also offers tools for generative AI applications, making it easier for users to customize and scale AI use cases. SageMaker’s architecture simplifies the AI lifecycle, from data discovery to model deployment, providing a seamless experience for developers.
  • 2
    Diffgram Data Labeling
    Your AI Data Platform Quality Training Data for Enterprise Data Labeling Software for Machine Learning Free on your Kubernetes Cluster Up to 3 Users. TRUSTED BY 5,000 HAPPY USERS WORLDWIDE Images, Video, Text Spatial Tools Quadratic Curves, Cuboids, Segmentation, Box, Polygons, Lines, Keypoints, Classification Tags, and More Use the exact spatial tool you need. All tools are easy to use, fully editable, and powerful ways to represent your data. All tools are available in Video. Attribute Tools More Meaning. More degrees of freedom through: Radio buttons. Multiple select. Date pickers. Sliders. Conditional logic. Directional Vectors. And more! You can capture complex knowledge and encode it into your AI. Streaming Data Automation Up to 10x Faster then manual labeling
    Starting Price: Free
  • 3
    Athina AI

    Athina AI

    Athina AI

    Athina is a collaborative AI development platform that enables teams to build, test, and monitor AI applications efficiently. It offers features such as prompt management, evaluation tools, dataset handling, and observability, all designed to streamline the development of reliable AI systems. Athina supports integration with various models and services, including custom models, and ensures data privacy through fine-grained access controls and self-hosted deployment options. The platform is SOC-2 Type 2 compliant, providing a secure environment for AI development. Athina's user-friendly interface allows both technical and non-technical team members to collaborate effectively, accelerating the deployment of AI features.
    Starting Price: Free
  • 4
    HumanSignal

    HumanSignal

    HumanSignal

    HumanSignal's Label Studio Enterprise is a comprehensive platform designed for creating high-quality labeled data and evaluating model outputs with human supervision. It supports labeling and evaluating multi-modal data, image, video, audio, text, and time series, all in one place. It offers customizable labeling interfaces with pre-built templates and powerful plugins, allowing users to tailor the UI and workflows to specific use cases. Label Studio Enterprise integrates seamlessly with popular cloud storage providers and ML/AI models, facilitating pre-annotation, AI-assisted labeling, and prediction generation for model evaluation. The Prompts feature enables users to leverage LLMs to swiftly generate accurate predictions, enabling instant labeling of thousands of tasks. It supports various labeling use cases, including text classification, named entity recognition, sentiment analysis, summarization, and image captioning.
    Starting Price: $99 per month
  • 5
    NLP Lab

    NLP Lab

    John Snow Labs

    John Snow Labs' Generative AI Lab is a cutting-edge platform designed to empower enterprises with the ability to develop, customize, and deploy state-of-the-art generative AI models. The lab provides a robust, end-to-end solution that simplifies the integration of generative AI into business operations, making it accessible to organizations of all sizes and industries. The Generative AI Lab offers a no-code environment, allowing users to create sophisticated AI models without needing extensive programming expertise. This democratizes AI development, enabling business professionals, data scientists, and developers to collaboratively build and deploy models that can transform data into actionable insights. The platform is built on top of a rich ecosystem of pre-trained models, advanced NLP capabilities, and a comprehensive suite of tools that streamline the process of customizing AI for specific business needs.
  • 6
    Segments.ai

    Segments.ai

    Segments.ai

    Segments.ai is an advanced data labeling platform that allows users to label data from multiple sensors simultaneously, improving the speed and accuracy of labeling for robotics and autonomous vehicle (AV) applications. It supports 2D and 3D labeling, including point cloud annotation, and enables users to label moving and stationary objects with ease. The platform leverages smart automation tools like batch mode and ML-powered object tracking, streamlining workflows and reducing manual labor. By fusing 2D image data with 3D point cloud data, Segments.ai offers a more efficient and consistent labeling process, ideal for high-volume, multi-sensor projects.
  • 7
    understand.ai

    understand.ai

    understand.ai

    ​Understand.ai provides cutting-edge ground truth annotation technology to handle complexity at scale. Their state-of-the-art annotation platform is designed to manage complex ground truth annotation projects, featuring scalable infrastructure that effortlessly handles high data volumes and projects of any size. It excels in customized data elevation and workflows, tailored to meet specific project needs while prioritizing compliance with stringent data privacy and security standards. User-friendly tools enable streamlined collaboration between customers and labeling partners, and automation capabilities significantly reduce manual annotation efforts, making large-scale ADAS/AD programs commercially feasible. Key features include multi-sensor integration, allowing seamless incorporation and processing of data from multiple LiDAR sensors for a comprehensive view of complex 3D environments and precise annotation.
  • 8
    Centific

    Centific

    Centific

    Centific’s frontier AI data foundry platform, powered by NVIDIA edge computing, is purpose-built to accelerate AI deployments by increasing flexibility, security, and scalability through comprehensive workflow orchestration. It centralizes AI project management in a unified AI Workbench, overseeing pipelines, model training, deployment, and reporting within a single, streamlined environment, while it handles data ingestion, preprocessing, and transformation. RAG Studio simplifies retrieval-augmented generation workflows, the Product Catalog organizes reusable assets, and Safe AI Studio embeds built-in safeguards to ensure compliance, reduce hallucinations, and protect sensitive data. Its plugin-based modular architecture supports both PaaS and SaaS models with metering to monitor consumption, and a centralized model catalog offers version control, compliance checks, and flexible deployment options.
  • 9
    Claravine

    Claravine

    Claravine

    Claravine is redefining data integrity for the global enterprise. The Data Standards Cloud makes it easy for teams to standardize, connect, and control data collaboratively, across the organization. Leading brands use Claravine to take greater ownership and control of their data from the start, for better decisions, stickier consumer experiences, and increased ROI.
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