Data Labeling reviews by real, verified users. Find unbiased ratings on user satisfaction, features, and price based on the most reviews available anywhere.
Data labeling software—also known as training data, data annotation, data tagging, or data classification software—provides a tool set for businesses to turn unlabeled data into labeled data and build corresponding artificial intelligence algorithms. Within these tools, the user inputs a given dataset and the software provides a label through machine learning-assisted labeling, a human taskforce, or the user themselves. Some platforms allow for the combination of the three, giving the user (or the system itself) the ability to choose who or what is doing the labeling, based on factors such as price, quality, and speed.
Data labeling tools differ as it relates to the types of data (e.g., image, video, audio, and text), as well as the subsets of those types (e.g., satellite imagery, LIDAR, etc.), they support. The types of annotation also vary and include image segmentation and object detection for image data; named entity recognition (NER) and sentiment detection for text data; and transcription and emotion recognition for speech annotation. To assess the quality of the labels, most tools use metrics like consensus, ground truth, and more.
For supervised learning, a type of machine learning, to get off the ground and make accurate predictions based on inputted data, there must be labeled data in place. Therefore, data labeling software is a crucial component in many artificial intelligence projects. This software can often integrate with data science and machine learning platforms, whereby the labeled data from the data labeling software helps to train an algorithm.
To qualify for inclusion in the Data Labeling category, a product must:
Amazon SageMaker Ground Truth helps you build highly accurate training datasets for machine learning quickly. SageMaker Ground Truth offers easy access to public and private human labelers and provides them with built-in workflows and interfaces for common labeling tasks.
Appen collects and labels images, text, speech, audio, video, and other data to create training data used to build and continuously improve the world’s most innovative artificial intelligence systems. We offer a state of the art, licensable data annotation platform to annotate training data use cases in computer vision and natural language processing. Our platform enhances accuracy and efficiency through our Smart Labeling and Pre-Labeling features which use Machine Learning to ease human anno
The fastest annotation platform and services for training AI. A complete set of solutions for image and video annotation and an annotation service with integrated tooling, on-demand narrow expertise in various fields, and a custom neural network, automation, and training models powered by AI.
Enterprise-grade data platform for vision AI. Dataloop is a one-stop shop for building and deploying powerful computer vision pipelines data labeling, automating data ops, customizing production pipelines and weaving the human-in-the-loop for data validation. Our vision is to make machine learning-based systems accessible, affordable and scalable for all.
Founded in 2013, Hive is a pioneering AI company specialized in computer vision and deep learning. Hive is focused on powering innovators across industries with practical AI solutions and data labeling, grounded in the world's highest quality visual and audio metadata. The company solves challenges for enterprises through three main pillars of the business: Hive Data, Hive Predict, and Hive Enterprise. Hive Data is the world's largest distributed data labeling platform with over 2 million regist
Clarifai offers an end-to-end AI lifecycle platform for deep learning and unstructured data that transforms unstructured images, video, and text into structured data, significantly faster and more accurately than humans would be able to do on their own. Clarifai has won numerous awards and is recognized by Forrester as a leader in computer vision platforms in line with companies such as Google and Microsoft. The company was founded in 2013 by CEO Matt Zeiler, Ph.D., after winning the top 5 place
Playment’s GT Studio is a no-code, self-serve data labeling platform that is heuristically designed to help ML teams create diverse, high-quality ground truth datasets at an efficient cost, scale, and speed. Most ML teams work with sub-optimal data or rely on tools or processes that take up a significant amount of their time which could be spent innovating. GT Studio is a web-based labeling platform that eliminates inefficiencies for the annotator and the project manager via ML-assisted annota
Automated Image Annotation and Neural Network training. V7 Darwin is the most powerful platform to automatically create ground truth to enable AIs to learn. Trusted by the likes of Merck, GE Healthcare, and Stanford, our technology speeds up the creation of visual data labels by 10x.
CloudFactory is a global leader in combining people and technology to provide workforce solutions for machine learning and business process optimization. Our growing team of data analysts prepare the data that powers products and trains artificial intelligence. We work with innovators across diverse industries and process millions of tasks a day for some of the world’s most innovative companies. We exist to create meaningful work for one million talented people in developing nations, so we can e
91% of teams take > 3 weeks to create their first dataset. And months to get to Beta. Here's why: The process of creating datasets gets blocked by default. Teams create many sets. This is because the needed abstractions (such as various Templates) only become known through an iterative process. With Diffgram, your Data Science team moves into a higher level control position of the Datasets. The system manages the data, including the Sync process between files. This makes the process non-
DefinedCrowd offers an intelligent data infrastructure for AI that provides high-quality training data to help machine learning oriented products reach market quicker and with better quality. It offers efficient data workflows that enable data scientists to collect, synthesize, enrich and structure training data by combining human intelligence and machine learning capabilities to accelerate enterprise AI initiatives.
Lionbridge partners with brands to break barriers and build bridges all over the world. For more than 20 years, we have helped companies connect with global customers by delivering marketing, testing and globalization services in more than 300 languages.
Predictly Tech Labs aims to enhance the usage and adoption of Artificial Intelligence technologies into different industries to experience its benefits in their products and services. For this reason, Predictly provides various kinds of services to their clients, such as data annotation, datasets, Pre-trained models, AI-transformation services.
The ShaipCloud™ AI data platform simplifies workflow, reduces the friction of working with a distributed global workforce, provides greater visibility, real-time quality control, and seamless collaboration with all major cloud providers. There are data platforms. Then there are AI data platforms. We’re the latter because the secure ShaipCloud™ human-in-the-loop platform offers the unparalleled functionality and speed to create, transform, and annotate large amounts of data for your AI and ML mod
Accelerate the development of your AI solutions with our complete labeling toolset built for speed and ease for dataset creation. Available with Sense for integrated model training or as a standalone application, HyperLabel helps machine learning teams iterate quickly and easily.
Supervisely Enterprise is fully self-hosted and cloud frendly: install it on your servers or in the cloud, keep everything private. We provide API, SDK and backend source codes. So it is highly customizable and can be integrated into any technology stack.
swivl is simplifying AI training. In general, data scientists typically spend 80% of their time on non-value added task such as finding, cleaning, and annotating data. Our focus - get data scientists back to doing what they do best, analyzing and developing algorithms to achieve business objectives. Our SaaS platform helps teams outsource these data annotation tasks to a diverse crowd to close the feedback loop in a cost effective way. This involves the action of training, testing, and tun
TaQadam means Progress. TaQadam is a female founded startup that aims to advance economic opportunity for youth and democratize GEO-AI. TaQadam develops imagery solutions for market intelligence, monitoring and measuring of business risks and vulnerabilities. We believe the development of a global map of physical assets and infrastructure is essential in today’s context. Identifying assets (e.g. mines, farm equipment, schools) and their features (e.g. cooling, water tanks, construction materia
The Universal Data Tool is a web/desktop app for editing and annotating images, text, audio, documents and to view and edit any data defined in the extensible .udt.json and .udt.csv standard. Collaborate with others in real time, easily train labelers, integrate into your applications. Perform Image Segmentation, Image Classification, Audio Transcription, Named Entity Recognition (NER) and Named Entity Linking (NEL). Run with docker, use with Tensorflow, Keras, or Fast.ai.