Alternatives to Labelbox

Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case. Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection. Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.

Our decentralized platform streamlines AI data collection and labeling through a worldwide contributor network. By combining crowdsourcing with blockchain technology, we deliver high-quality, traceable datasets. Platform Highlights: Worldwide Collection: Tap into global contributors for comprehensive data gathering Blockchain Security: Every contribution tracked and verified on-chain Quality Focus: Expert validation ensures exceptional data standards Platform Benefits: Rapid scaling of data collection Complete data providence tracking Validated datasets ready for AI use Cost-efficient global operations Flexible contributor network How It Works: Define Your Needs: Create your data collection task Community Activation: Global contributors notified and start gathering data Quality Control: Human verification layer validates all contributions Sample Review: Get dataset sample for approval Full Delivery: Complete dataset delivered once approved

Ango Hub is an all-in-one, quality-oriented data annotation platform that AI teams can use. Ango Hub is available on-premise and in the cloud. It allows AI teams and their data annotation workforces to quickly and efficiently annotate their data without compromising quality. Ango Hub is the only data annotation platform that focuses on quality. It features features that enhance the quality of your annotations. These include a centralized labeling system, a real time issue system, review workflows and sample label libraries. There is also consensus up to 30 on the same asset. Ango Hub is versatile as well. It supports all data types that your team might require, including image, audio, text and native PDF. There are nearly twenty different labeling tools that you can use to annotate data. Some of these tools are unique to Ango hub, such as rotated bounding box, unlimited conditional questions, label relations and table-based labels for more complicated labeling tasks.

Manage unstructured data to develop AI solutions in record time. Enterprise-grade data platform with vision AI. Dataloop offers a single-stop-shop for building and deploying powerful data pipelines for computer vision, data labeling, automation of data operations, customizing production pipelines, and weaving in the human for data validation. Our vision is to make machine-learning-based systems affordable, scalable and accessible for everyone. Explore and analyze large quantities of unstructured information from diverse sources. Use automated preprocessing to find similar data and identify the data you require. Curate, version, cleanse, and route data to where it's required to create exceptional AI apps.

Harness the power of AutoML Vision or leverage pre-trained Vision API models to extract meaningful insights from images stored in the cloud or at the network's edge, allowing for emotion detection, text interpretation, and much more. Google Cloud presents two advanced computer vision solutions that utilize machine learning to provide top-notch prediction accuracy for image analysis. You can streamline the creation of bespoke machine learning models by simply uploading your images, using AutoML Vision's intuitive graphical interface to train these models, and fine-tuning them for optimal performance in terms of accuracy, latency, and size. Once perfected, these models can be seamlessly exported for use in cloud applications or on various edge devices. Additionally, Google Cloud’s Vision API grants access to robust pre-trained machine learning models via REST and RPC APIs. You can easily assign labels to images, categorize them into millions of pre-existing classifications, identify objects and faces, interpret both printed and handwritten text, and enhance your image catalog with rich metadata for deeper insights. This combination of tools not only simplifies the image analysis process but also empowers businesses to make data-driven decisions more effectively.

A powerful labeling platform for all stages and types of ML development. We leverage a suite of industry-leading computer vision algorithms to automatically detect and classify the content of your images and videos. Creating detailed segmentation information is a time-consuming process. Machine assistance speeds up task completion by as much as 70%, saving you both time and money. We leverage ML to propose labels that accelerate human labeling. This includes computer vision models to automatically detect, localize, and classify entities in your images and videos before handing off the task to our workforce. Automatic labelling reduces workforce costs and allows annotators to spend their time on the more complicated steps of the annotation process. Our video annotation tool is built to handle 4K resolution and long-running videos natively and provides innovative features like interpolation, object proposal, and entity resolution.

Amazon SageMaker is a comprehensive machine learning platform that integrates powerful tools for model building, training, and deployment in one cohesive environment. It combines data processing, AI model development, and collaboration features, allowing teams to streamline the development of custom AI applications. With SageMaker, users can easily access data stored across Amazon S3 data lakes and Amazon Redshift data warehouses, facilitating faster insights and AI model development. It also supports generative AI use cases, enabling users to develop and scale applications with cutting-edge AI technologies. The platform’s governance and security features ensure that data and models are handled with precision and compliance throughout the entire ML lifecycle. Furthermore, SageMaker provides a unified development studio for real-time collaboration, speeding up data discovery and model deployment.

Revolutionary machine teaching is here with an exceptionally efficient annotation tool driven by active learning. Prodigy serves as a customizable annotation platform so effective that data scientists can handle the annotation process themselves, paving the way for rapid iteration. The advancements in today's transfer learning technologies allow for the training of high-quality models using minimal examples. By utilizing Prodigy, you can fully leverage contemporary machine learning techniques, embracing a more flexible method for data gathering. This will enable you to accelerate your workflow, gain greater autonomy, and deliver significantly more successful projects. Prodigy merges cutting-edge insights from the realms of machine learning and user experience design. Its ongoing active learning framework ensures that you only need to annotate those examples the model is uncertain about. The web application is not only powerful and extensible but also adheres to the latest user experience standards. The brilliance lies in its straightforward design: it encourages you to concentrate on one decision at a time, keeping you actively engaged – akin to a swipe-right approach for data. Additionally, this streamlined process fosters a more enjoyable and effective annotation experience overall.

Build, test and optimize Generative AI apps that unlock the value in your data. Our industry-leading ML expertise, our state-of-the art test and evaluation platform and advanced retrieval augmented-generation (RAG) pipelines will help you optimize LLM performance to meet your domain-specific needs. We provide an end-toend solution that manages the entire ML Lifecycle. We combine cutting-edge technology with operational excellence to help teams develop high-quality datasets, because better data leads better AI.

The premier platform designed for the complete computer vision process allows you to evolve from image annotation to precise neural networks at speeds up to ten times quicker. Utilizing our exceptional data labeling tools, you can convert your images, videos, and 3D point clouds into top-notch training data. This enables you to train your models, monitor experiments, visualize results, and consistently enhance model predictions, all while constructing custom solutions within a unified environment. Our self-hosted option ensures data confidentiality, offers robust customization features, and facilitates seamless integration with your existing technology stack. This comprehensive solution for computer vision encompasses multi-format data annotation and management, large-scale quality control, and neural network training within an all-in-one platform. Crafted by data scientists for their peers, this powerful video labeling tool draws inspiration from professional video editing software and is tailored for machine learning applications and beyond. With our platform, you can streamline your workflow and significantly improve the efficiency of your computer vision projects.

SuperAnnotate is the best platform to build high-quality training datasets for NLP and computer vision. We enable machine learning teams to create highly accurate datasets and successful pipelines of ML faster with advanced tooling, QA, ML, and automation features, data curation and robust SDK, offline accessibility, and integrated annotation services. We have created a unified annotation environment by bringing together professional annotators and our annotation tool. This allows us to provide integrated software and services that will lead to better quality data and more efficient data processing.

Innotescus is an image and video annotation platform that enables collaboration and data handling. It streamlines Computer Vision development through intuitive collaboration features, smart annotation tools and seamless data handling. Its data visualization tools and cross functional collaboration features help to identify data bias early and improve data accuracy. This allows for faster and more cost-efficient deployments of high-performance Artificial Intelligence.

swivl simplifies AI training Data scientists spend about 80% of their time on tasks that are not value-added, such as cleaning, cleaning, and annotation data. Our SaaS platform that doesn't require code allows teams to outsource data annotation tasks to a network of data annotators. This helps close the feedback loop cost-effectively. This includes the training, testing, deployment, and monitoring of machine learning models, with an emphasis on audio and natural language processing.

Introducing the ultimate data annotation tool that offers unparalleled flexibility and ease of installation. Users can create customized user interfaces or opt for ready-made labeling templates tailored to their specific needs. The adaptable layouts and templates seamlessly integrate with your dataset and workflow requirements. It supports various object detection methods in images, including boxes, polygons, circles, and key points, and allows for the segmentation of images into numerous parts. Additionally, machine learning models can be utilized to pre-label data and enhance efficiency throughout the annotation process. Features such as webhooks, a Python SDK, and an API enable users to authenticate, initiate projects, import tasks, and manage model predictions effortlessly. Save valuable time by leveraging predictions to streamline your labeling tasks, thanks to the integration with ML backends. Furthermore, users can connect to cloud object storage solutions like S3 and GCP to label data directly in the cloud. The Data Manager equips you with advanced filtering options to effectively prepare and oversee your dataset. This platform accommodates multiple projects, diverse use cases, and various data types, all in one convenient space. By simply typing in the configuration, you can instantly preview the labeling interface. Live serialization updates at the bottom of the page provide a real-time view of what Label Studio anticipates as input, ensuring a smooth user experience. This tool not only improves annotation accuracy but also fosters collaboration among teams working on similar projects.

Deep Block is a no-code platform to train and use your own AI models based on our patented Machine Learning technology. Have you heard of mathematic formulas such as Backpropagation? Well, I had once to perform the process of converting an unkindly written system of equations into one-variable equations. Sounds like gibberish? That is what I and many AI learners have to go through when trying to grasp basic and advanced deep learning concepts and when learning how to train their own AI models. Now, what if I told you that a kid could train an AI as well as a computer vision expert? That is because the technology itself is very easy to use, most application developers or engineers only need a nudge in the right direction to be able to use it properly, so why do they need to go through such a cryptic education? That is why we created Deep Block, so that individuals and enterprises alike can train their own computer vision models and bring the power of AI to the applications they develop, without any prior machine learning experience. You have a mouse and a keyboard? You can use our web-based platform, check our project library for inspiration, and choose between out-of-the-box AI training modules.

Keylabs.ai is an image and video annotation platform built by annotation experts to deliver high-performance data annotation and management features and unique operations management. Its tools have a proven track record of handling large datasets efficiently and accurately. Trusted by global technology leaders, Keylabs.ai combines innovative technology with user-focused design to deliver solutions to projects of any type and size.

Our company is the premier provider of data labeling services in AI. We cover industries like Automotive, Robotics, Fintech, Healthcare, E-commerce, Manufacturing, and Insurance. With over 500+ annotation gurus and multilingual support, we provide efficient and accurate services for both enterprise and R&D projects. Our range of services includes Computer Vision and NLP annotation, data processing, and more. Choose Label Your Data for unparalleled quality of your training datasets. Our top priority is to ensure the security and quality of client's data. To ensure the confidentiality of client data, our facilities and teams have been certified by ISO 27001 and PCI DSS (level 1). We adhere to the most important industry security standards, such as GDPR and CCPA.

Your AI Data Platform High Quality Training Data for Enterprise Data Labeling Software for Machine Learning Your Kubernetes Cluster up to 3 users is free TRUSTED BY 5,000 HAPPY UBERS WORLDWIDE Images, Video, and Text Spatial Tools Quadratic Curves and Cuboids, Segmentation Box, Polygons and Lines, Keypoints, Classification tags, and More You can use the exact spatial tool that you need. All tools are easy-to-use, editable, and offer powerful ways to present your data. All tools are available as Video. Attribute Tools More Meaning. More freedom through: Radio buttons Multiple selection. Date pickers. Sliders. Conditional logic. Directional vectors. Plus, many more! Complex knowledge can be captured and encoded into your AI. Streaming Data Automation Manual labeling can be up to 10x faster than automated labeling

Mindkosh is your premier data management platform, streamlining the curation, tagging, and verification of datasets for AI initiatives. Our top-tier data annotation platform merges team-oriented functionalities with AI-enhanced annotation tools, delivering an all-encompassing toolkit for categorizing diverse data types, including images, videos, and 3D point clouds from Lidar. For images, Mindkosh offers advanced semi-automated segmentation, pre-labeling of bounding boxes, and completely automatic OCR capabilities. For video annotation, Mindkosh's automated interpolation significantly reduces the need for manual labeling. And for Lidar data, single-click annotation enables swift cuboid generation with just one click. If you are simply looking to get your data labeled, our high quality data annotation services combined with an easy to use Python SDK and web-based review platform, provide an unmatched experience.

V7 Darwin is a data labeling and training platform designed to automate and accelerate the process of creating high-quality datasets for machine learning. With AI-assisted labeling and tools for annotating images, videos, and more, V7 makes it easy for teams to create accurate and consistent data annotations quickly. The platform supports complex tasks such as segmentation and keypoint labeling, allowing businesses to streamline their data preparation process and improve model performance. V7 Darwin also offers real-time collaboration and customizable workflows, making it suitable for enterprises and research teams alike.

One tool can manage your entire data labeling workflow. We invite you to discover the best way to manage your labeling staff, improve data quality, work 70% faster, and get organized!

Appen combines the intelligence of over one million people around the world with cutting-edge algorithms to create the best training data for your ML projects. Upload your data to our platform, and we will provide all the annotations and labels necessary to create ground truth for your models. An accurate annotation of data is essential for any AI/ML model to be trained. This is how your model will make the right judgments. Our platform combines human intelligence with cutting-edge models to annotation all types of raw data. This includes text, video, images, audio and video. It creates the exact ground truth for your models. Our user interface is easy to use, and you can also programmatically via our API.

Labellerr is a data annotation platform aimed at streamlining the creation of top-notch labeled datasets essential for AI and machine learning applications. It accommodates a wide array of data formats, such as images, videos, text, PDFs, and audio, addressing various annotation requirements. This platform enhances the labeling workflow with automated features, including model-assisted labeling and active learning, which help speed up the process significantly. Furthermore, Labellerr includes sophisticated analytics and intelligent quality assurance tools to maintain the precision and dependability of annotations. For projects that demand specialized expertise, Labellerr also provides expert-in-the-loop services, granting access to professionals in specialized domains like healthcare and automotive, thereby ensuring high-quality results. This comprehensive approach not only facilitates efficient data preparation but also builds trust in the reliability of the labeled datasets produced.

Amazon SageMaker enables the identification of various types of unprocessed data, including images, text documents, and videos, while also allowing for the addition of meaningful labels and the generation of synthetic data to develop high-quality training datasets for machine learning applications. The platform provides two distinct options, namely Amazon SageMaker Ground Truth Plus and Amazon SageMaker Ground Truth, which grant users the capability to either leverage a professional workforce to oversee and execute data labeling workflows or independently manage their own labeling processes. For those seeking greater autonomy in crafting and handling their personal data labeling workflows, SageMaker Ground Truth serves as an effective solution. This service simplifies the data labeling process and offers flexibility by enabling the use of human annotators through Amazon Mechanical Turk, external vendors, or even your own in-house team, thereby accommodating various project needs and preferences. Ultimately, SageMaker's comprehensive approach to data annotation helps streamline the development of machine learning models, making it an invaluable tool for data scientists and organizations alike.

For tasks such as transcription, data validation, classification, sentiment analysis, and more, UHRS offers comprehensive solutions tailored to your needs. We leverage human intelligence to enhance machine learning models, aiding you in overcoming some of your toughest challenges. Judges can conveniently access UHRS from anywhere at any time with just an internet connection. This streamlined access allows for quick engagement with tasks like video annotation within minutes. With UHRS, managing the classification of thousands of images becomes a straightforward and efficient process. Our platform enables the training of your products and tools through high-quality annotated image data, enhancing capabilities like image detection and boundary recognition. You can efficiently classify images, conduct semantic segmentation, and implement object detection. In addition, we facilitate audio-to-text validation, conversation analysis, and relevance checks. Furthermore, our services extend to sentiment identification for tweets, document classification, and various ad hoc data collection tasks, including information correction, moderation, and conducting surveys. With UHRS, you gain a versatile partner in navigating a wide range of data-related challenges.

The best data will help you achieve peak model performance. Create and manage training data for any visual modality. Debug models, boost performance and make foundation models yours. Expert review, QA, and QC workflows will help you deliver better datasets to your artificial-intelligence teams, improving model performance. Encord's Python SDK allows you to connect your data and models, and create pipelines that automate the training of ML models. Improve model accuracy by identifying biases and errors in your data, labels, and models.

Utilizing Automaton AI's ADVIT platform, you can effortlessly create, manage, and enhance high-quality training data alongside DNN models, all from a single interface. The system automatically optimizes data for each stage of the computer vision pipeline, allowing for a streamlined approach to data labeling processes and in-house data pipelines. You can efficiently handle both structured and unstructured datasets—be it video, images, or text—while employing automatic functions that prepare your data for every phase of the deep learning workflow. Once the data is accurately labeled and undergoes quality assurance, you can proceed with training your own model effectively. Deep neural network training requires careful hyperparameter tuning, including adjustments to batch size and learning rates, which are essential for maximizing model performance. Additionally, you can optimize and apply transfer learning to enhance the accuracy of your trained models. After the training phase, the model can be deployed into production seamlessly. ADVIT also supports model versioning, ensuring that model development and accuracy metrics are tracked in real-time. By leveraging a pre-trained DNN model for automatic labeling, you can further improve the overall accuracy of your models, paving the way for more robust applications in the future. This comprehensive approach to data and model management significantly enhances the efficiency of machine learning projects.

Clarifai is a leading AI platform for modeling image, video, text and audio data at scale. Our platform combines computer vision, natural language processing and audio recognition as building blocks for building better, faster and stronger AI. We help enterprises and public sector organizations transform their data into actionable insights. Our technology is used across many industries including Defense, Retail, Manufacturing, Media and Entertainment, and more. We help our customers create innovative AI solutions for visual search, content moderation, aerial surveillance, visual inspection, intelligent document analysis, and more. Founded in 2013 by Matt Zeiler, Ph.D., Clarifai has been a market leader in computer vision AI since winning the top five places in image classification at the 2013 ImageNet Challenge. Clarifai is headquartered in Delaware

The entire process of machine learning and computer vision is streamlined and expedited through a single no-code platform. Sense empowers users to create and implement AI IoT solutions across various environments, whether in the cloud, at the edge, or on-premises. Discover how Sense delivers ease, consistency, and transparency for AI/ML teams, providing robust capabilities for machine learning engineers while remaining accessible for subject matter experts. With Sense Data Annotation, you can enhance your machine learning models by efficiently labeling video and image data, ensuring the creation of high-quality training datasets. The platform also features one-touch labeling integration, promoting ongoing machine learning at the edge and simplifying the management of all your AI applications, thereby maximizing efficiency and effectiveness. This comprehensive approach makes Sense an invaluable tool for a wide range of users, regardless of their technical background.

Deepen AI provides cutting-edge tools and services for multi-sensor data labeling and calibration, aimed at enhancing the training process for computer vision applications in autonomous vehicles, robotics, and beyond. Their annotation suite addresses numerous critical use cases, which include 2D and 3D bounding boxes, semantic and instance segmentation, polylines, and key points. Powered by artificial intelligence, the platform boasts pre-labeling features that can automatically tag up to 80 commonly used classes, resulting in a productivity boost of seven times. Additionally, it incorporates machine learning-assisted segmentation, enabling users to segment objects effortlessly with minimal clicks, alongside precise object detection and tracking across frames to eliminate redundancy and conserve time. Furthermore, Deepen AI’s calibration suite accommodates all essential sensor types, such as LiDAR, cameras, radar, IMUs, and vehicle sensors. These sophisticated tools facilitate seamless visualization and inspection of the integrity of multi-sensor data, while also allowing for the rapid calculation of intrinsic and extrinsic calibration parameters in mere seconds. By streamlining these processes, Deepen AI empowers developers to focus more on innovation and less on manual data handling.

Develop training datasets for computer vision models using our comprehensive management solution. We are convinced that the quality of data labeling plays a crucial role in crafting successful deep learning models. Our mission is to establish ourselves as the foremost data labeling platform in the industry, enabling businesses to fully leverage the potential of AI technology. Organize your media assets into distinct categories for better management. Highlight specific items of interest using one or multiple bounding boxes to enhance detection accuracy. Utilize bounding boxes with added precision for more detailed annotations. Provide accurate measurements of width, depth, and height for various objects. Classify every pixel in an image for fine-grained analysis. Identify and mark individual points to capture specific details within images. Annotate straight lines to assist in geometric assessments. Measure critical attributes like yaw, pitch, and roll for items of interest. Keep track of timestamps in both video and audio content for synchronization purposes. Additionally, annotate freeform lines in images to capture more complex shapes and designs, enhancing the depth of your data labeling efforts.

Intel® Geti™ software streamlines the creation of computer vision models through efficient data annotation and training processes. It offers features such as intelligent annotations, active learning, and task chaining, allowing users to develop models for tasks like classification, object detection, and anomaly detection without needing to write extra code. Furthermore, the platform includes optimizations, hyperparameter tuning, and models that are ready for production and optimized for Intel’s OpenVINO™ toolkit. Intended to facilitate teamwork, Geti™ enhances collaboration by guiding teams through the entire model development lifecycle, from labeling data to deploying models effectively. This comprehensive approach ensures that users can focus on refining their models while minimizing technical hurdles.

Klatch Technologies is a global provider of data services that helps companies and institutions collect and annotate data. We support Artificial Intelligence companies, research institutes, Machine Learning and Computer Vision projects in data labeling. Our specialists provide high-quality data security, rapid scalability and accuracy, as well as multilingual capability and quick turnaround time. Data Annotation Services Image Annotation Video Annotation Search Relevance Annotation for Text NLP Text classification Sentiment Analysis Image Segmentation LIDAR Annotation - Data collection services: Healthcare Training Data Chatbot Training Data All other data collection requirements IT Managed Services Moderation of Content Ecommerce Data Categorization

Enhance the platform to incorporate annotation capabilities specifically for segmentation tasks. Within the Zastra repository, innovative algorithms will facilitate segmentation processes to bolster active learning for various datasets. Comprehensive end-to-end ML operations will be implemented, complete with version control for datasets and experiments, alongside templated pipelines that enable model deployment across standard cloud environments and edge devices. By integrating advancements in Bayesian deep learning into the active learning framework, we aim to elevate the overall performance. Moreover, we will refine the accuracy of annotations using specialized architectures, such as Bayesian CNNs, ensuring superior results. Our dedicated team has invested extensive time and effort into developing this groundbreaking solution tailored for your needs. Though we are continuously enhancing the platform with new features, we eagerly invite you to experience a trial run! Zastra boasts a range of core functionalities, including active learning for object classification, detection, localization, and segmentation, applicable across various formats like images, videos, audio, text, and point cloud data. This versatility positions Zastra as a comprehensive tool to tackle diverse data challenges effectively.

Our AI Training Data Platform combines the best of data annotators and computer vision capabilities, with the power of the AI Community of professional annotations. GT Manage: Our proprietary platform manager for our 1M+ community. GT Annotate is our proprietary data annotation software. GT Data: Our global expertise for data collection and creation. Human-powered AI is the foundation of all AI. Our fully automated platform allows sophisticated data annotation across data types, all within the same software. It also provides seamless project and AI Community Management. Ground Truth (GT Annotate) is our proprietary software for data annotation. It was carefully designed to allow teams to create quality AI training datasets quickly and accurately. Below are some examples of how the technology is used.

Anolytics specializes in providing data annotation services for images, videos, and text, specifically tailored for machine learning and AI-driven computer vision applications. Their offerings include an economical annotation service aimed at facilitating the development of machine learning and artificial intelligence models. By utilizing various annotation techniques, Anolytics ensures that the data is accurately and precisely annotated, whether in text, image, or video formats. The company excels in Image Annotation, Video Annotation, and Text Annotation, maintaining high standards of accuracy throughout the process. Anolytics delivers a comprehensive range of data annotation services essential for training in both machine learning and deep learning environments. Their services encompass Bounding Boxes, Semantic Segmentation, 3D Point Cloud Annotation, and 3D Cuboid Annotation, catering to diverse industries such as healthcare, autonomous driving, drone operations, retail, security surveillance, and agriculture. With a focus on scalability, Anolytics ensures its solutions are available with rapid turnaround times and competitive pricing for clients around the world, thereby enhancing their accessibility and effectiveness in various applications. This commitment to quality and efficiency positions Anolytics as a leader in the data annotation industry.

Facilitate a variety of annotation types for both images and videos through a flexible, open-source web-based tool. This tool is designed to scale and supports user-friendly “click and drag” functionalities, allowing for the addition of multiple attributes with ease. It incorporates features that enable the fitting of boundaries using Bezier curves and the ability to duplicate shared boundaries. Users can annotate the specific areas where a driver is operating and mark lane lines to enhance vision-based vehicle localization and trajectory planning. An intuitive four-click method is employed to accurately encapsulate objects of interest, while advanced algorithms predict annotations across frames by utilizing object tracking and interpolation techniques for bounding boxes. It also offers prediction capabilities for individual object instances, with 2D tracking functionalities expanded into a three-dimensional context, enhancing the overall annotation process. This comprehensive tool aims to streamline the workflow for users involved in image and video annotation tasks.

Image categorization, bounding box detection, polygon annotation, curve tracing, and 3D positioning. Additionally, video tracking, text categorization, and named entity recognition are supported. Custom task plugins allow users to develop their own labeling tools. Files can be exported in PascalVoc XML format, identical to that used by ImageNet, as well as in CoreNLP format. The platform is compatible with Windows, Mac, CentOS, and Ubuntu operating systems. This versatility ensures that users can seamlessly integrate it into their existing workflows.

We make data for the world's most valuable companies. Innodata solves your most difficult data engineering problems using artificial intelligence and human expertise. Innodata offers the services and solutions that you need to harness digital information at scale and drive digital disruption within your industry. We secure and efficiently collect and label sensitive data. This provides ground truth that is close to 100% for AI and ML models. Our API is simple to use and ingests unstructured data, such as contracts and medical records, and generates structured XML that conforms to schemas for downstream applications and analytics. We make sure that mission-critical databases are always accurate and up-to-date.

Nexdata's AI Data Annotation Platform serves as a comprehensive solution tailored to various data annotation requirements, encompassing an array of types like 3D point cloud fusion, pixel-level segmentation, speech recognition, speech synthesis, entity relationships, and video segmentation. It is equipped with an advanced pre-recognition engine that improves human-machine interactions and enables semi-automatic labeling, boosting labeling efficiency by more than 30%. To maintain superior data quality, the platform integrates multi-tier quality inspection management and allows for adaptable task distribution workflows, which include both package-based and item-based assignments. Emphasizing data security, it implements a robust system of multi-role and multi-level authority management, along with features such as template watermarking, log auditing, login verification, and API authorization management. Additionally, the platform provides versatile deployment options, including public cloud deployment that facilitates quick and independent system setup while ensuring dedicated computing resources. This combination of features makes Nexdata's platform not only efficient but also highly secure and adaptable to various operational needs.

We guarantee top-notch service level agreements (SLAs) exceeding 95%, even for the most intricate workflows. Our dedicated team is on hand to assist with everything, from establishing a solid quality evaluation framework to addressing unique edge cases. As a socially responsible AI organization, we have created economic opportunities for more than 52,000 individuals from underrepresented and disadvantaged backgrounds. Through machine learning-assisted annotation, we achieve efficiency improvements of up to four times for single-class tasks. Our agile approach allows us to swiftly adjust to changes in project demands, focus shifts, and unforeseen challenges. Our ISO-certified delivery centers, along with biometric and two-factor authentication, ensure a secure operational environment. We facilitate the seamless reorganization of tasks, offer constructive feedback, and oversee models in active use. Our services encompass all data types, enabling you to achieve more with fewer resources. By integrating machine learning with human oversight, we meticulously filter data and curate images that align with your specific requirements. You will receive example results that adhere to your initial criteria, and we will collaborate with you to pinpoint edge cases while suggesting optimal annotation practices. Additionally, our commitment to quality ensures that every step of the process enhances the overall effectiveness of your project.

We apply the highest quality standards to label your data, ensuring that even the most intricate AI projects are well-supported through our exclusive labeling platform. This allows you to focus on developing the products that resonate with your customers. Our comprehensive solution for image annotation features rapid labeling tools, synthetic data generation, efficient data management, automation capabilities, and on-demand annotation services, all designed to expedite the completion of computer vision initiatives. When precision in every pixel is crucial, you require reliable, AI-driven image annotation tools that cater to your unique use cases, including various instances, attributes, and much more. Our skilled team of data labelers is adept at handling any data-related challenge that may arise. As your requirements for data labeling expand, you can trust us to scale the necessary workforce to achieve your objectives, ensuring that unlike crowdsourcing platforms, the quality of your data remains uncompromised. With our commitment to excellence, you can confidently advance your AI projects and deliver exceptional results.

Your software can see objects in video and images. A few dozen images can be used to train a computer vision model. This takes less than 24 hours. We support innovators just like you in applying computer vision. Upload files via API or manually, including images, annotations, videos, and audio. There are many annotation formats that we support and it is easy to add training data as you gather it. Roboflow Annotate was designed to make labeling quick and easy. Your team can quickly annotate hundreds upon images in a matter of minutes. You can assess the quality of your data and prepare them for training. Use transformation tools to create new training data. See what configurations result in better model performance. All your experiments can be managed from one central location. You can quickly annotate images right from your browser. Your model can be deployed to the cloud, the edge or the browser. Predict where you need them, in half the time.

Scale Data Engine empowers machine learning teams to enhance their datasets effectively. By consolidating your data, authenticating it with ground truth, and incorporating model predictions, you can seamlessly address model shortcomings and data quality challenges. Optimize your labeling budget by detecting class imbalances, errors, and edge cases within your dataset using the Scale Data Engine. This platform can lead to substantial improvements in model performance by identifying and resolving failures. Utilize active learning and edge case mining to discover and label high-value data efficiently. By collaborating with machine learning engineers, labelers, and data operations on a single platform, you can curate the most effective datasets. Moreover, the platform allows for easy visualization and exploration of your data, enabling quick identification of edge cases that require labeling. You can monitor your models' performance closely and ensure that you consistently deploy the best version. The rich overlays in our powerful interface provide a comprehensive view of your data, metadata, and aggregate statistics, allowing for insightful analysis. Additionally, Scale Data Engine facilitates visualization of various formats, including images, videos, and lidar scenes, all enhanced with relevant labels, predictions, and metadata for a thorough understanding of your datasets. This makes it an indispensable tool for any data-driven project.

Supercharge your AI with human expertise. SUPA is here to help you streamline your data at any stage: collection, curation, annotation, model validation and human feedback. Better data, better AI. SUPA is trusted by AI teams to solve their human data needs.