Alternatives to Scale Data Engine

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.

The training data platform for AI teams. A machine learning model can only be as good as the training data it uses. Labelbox is an integrated platform that allows you to create and manage high quality training data in one place. It also supports your production pipeline with powerful APIs. A powerful image labeling tool for segmentation, object detection, and image classification. You need precise and intuitive image segmentation tools when every pixel is important. You can customize the tools to suit your particular use case, including custom attributes and more. The performant video labeling editor is for cutting-edge computer visual. Label directly on the video at 30 FPS, with frame level. Labelbox also provides per-frame analytics that allow you to create faster models. It's never been easier to create training data for natural language intelligence. You can quickly and easily label text strings, conversations, paragraphs, or documents with fast and customizable classification.

APISCRAPY is an AI-driven web scraping and automation platform converting any web data into ready-to-use data API. Other Data Solutions from AIMLEAP: AI-Labeler: AI-augmented annotation & labeling tool AI-Data-Hub: On-demand data for building AI products & services PRICE-SCRAPY: AI-enabled real-time pricing tool API-KART: AI-driven data API solution hub  About AIMLEAP AIMLEAP is an ISO 9001:2015 and ISO/IEC 27001:2013 certified global technology consulting and service provider offering AI-augmented Data Solutions, Data Engineering, Automation, IT, and Digital Marketing services. AIMLEAP is certified as ‘The Great Place to Work®’. Since 2012, we have successfully delivered projects in IT & digital transformation, automation-driven data solutions, and digital marketing for 750+ fast-growing companies globally. Locations: USA: 1-30235 14656 Canada: +1 4378 370 063 India: +91 810 527 1615 Australia: +61 402 576 615

Shaip is a comprehensive AI data platform delivering precise and ethical data collection, annotation, and de-identification services across text, audio, image, and video formats. Operating globally, Shaip collects data from more than 60 countries and offers an extensive catalog of off-the-shelf datasets for AI training, including 250,000 hours of physician audio and 30 million electronic health records. Their expert annotation teams apply industry-specific knowledge to provide accurate labeling for tasks such as image segmentation, object detection, and content moderation. The company supports multilingual conversational AI with over 70,000 hours of speech data in more than 60 languages and dialects. Shaip’s generative AI services use human-in-the-loop approaches to fine-tune models, optimizing for contextual accuracy and output quality. Data privacy and compliance are central, with HIPAA, GDPR, ISO, and SOC certifications guiding their de-identification processes. Shaip also provides a powerful platform for automated data validation and quality control. Their solutions empower businesses in healthcare, eCommerce, and beyond to accelerate AI development securely and efficiently.

Surge is building the modern human data infrastructure to power the next wave of AI – like building powerful large language models with RLHF and training rich content moderation systems. Our team hails from Google, Meta, Stanford, Harvard, and MIT.

Select the most impactful unlabeled data to enhance domain coverage and boost model performance. Ensure your metadata is registered with Dioptra while retaining full control over your data. Identify the underlying causes of model failure and regressions through a comprehensive data-focused toolkit. Utilize our active learning miners to extract the most valuable unlabeled datasets. Leverage Dioptra’s APIs to seamlessly integrate with your labeling and retraining processes. Systematically curate your data at scale tailored to your specific use case. We offer open-source solutions for data curation and management applicable to computer vision, NLP, and LLMs. Our support has enabled clients to elevate model accuracy on challenging cases, accelerate training durations, and cut down on labeling expenses, ultimately leading to more efficient workflows. This approach not only streamlines the data management process but also fosters innovation in model development.

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.

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.

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.

The quality of training data is vital for all large language models, whether it is created in-house or sourced from existing datasets. Implementing a human-in-the-loop labeling system provides immediate feedback that is crucial for refining datasets, ultimately leading to the development of highly effective and unique AI models. Our precise data labeling services incorporate quicker human contributions, which enhance the diversity and resilience of input, thereby increasing the adaptability of language models for various enterprise applications. By effectively managing our labeling teams, we ensure you only invest in the necessary expertise and experience that your data labeling project demands. Sapien is adept at quickly adjusting labeling operations to accommodate both large and small annotation projects, demonstrating human intelligence at scale. Additionally, we can tailor labeling models to meet your specific data types, formats, and annotation needs, ensuring accuracy and relevance in every project. This customized approach significantly boosts the overall efficiency and effectiveness of your AI initiatives.

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.

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.

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.

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.

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.

Superb AI introduces a cutting-edge machine learning data platform designed to empower AI teams to develop superior AI solutions more efficiently. The Superb AI Suite functions as an enterprise SaaS platform tailored for ML engineers, product developers, researchers, and data annotators, facilitating streamlined training data workflows that conserve both time and financial resources. Notably, a significant number of ML teams allocate over half of their efforts to managing training datasets, a challenge that Superb AI addresses effectively. Customers utilizing our platform have experienced an impressive 80% reduction in the time required to commence model training. With a fully managed workforce, comprehensive labeling tools, rigorous training data quality assurance, pre-trained model predictions, advanced auto-labeling capabilities, and efficient dataset filtering and integration, Superb AI enhances the data management experience. Furthermore, our platform offers robust developer tools and seamless ML workflow integrations, making training data management simpler and more efficient than ever before. With enterprise-level features catering to every aspect of an ML organization, Superb AI is revolutionizing the way teams approach machine learning projects.

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.

AI is today blocked by a lack of labeled data. Not models. The first data-centric AI platform powered by a programmatic approach will unblock AI. With its unique programmatic approach, Snorkel AI is leading a shift from model-centric AI development to data-centric AI. By replacing manual labeling with programmatic labeling, you can save time and money. You can quickly adapt to changing data and business goals by changing code rather than manually re-labeling entire datasets. Rapid, guided iteration of the training data is required to develop and deploy AI models of high quality. Versioning and auditing data like code leads to faster and more ethical deployments. By collaborating on a common interface, which provides the data necessary to train models, subject matter experts can be integrated. Reduce risk and ensure compliance by labeling programmatically, and not sending data to external annotators.

Comprehensive annotation services that are scalable and offer quick turnaround times with exceptional precision are available. These services include 2D/3D bounding boxes, polygons, polylines, landmarks, and semantic segmentation solutions tailored for various applications, from LiDAR to geospatial imagery. Zuru's experts tackle intricate computer vision algorithms, addressing challenging edge cases and diverse taxonomies. Additionally, text annotations are provided in all major global languages, including less common ones like Bahasa, Cantonese, Finnish, and Hungarian. A dedicated team of trained linguistic labeling specialists has successfully annotated over 10 million data points across multiple sectors, including Retail, BFSI, and Healthcare. Whether it's advanced labeling for customer service automation or basic transcription and audio diarization, Zuru's team has experience in a wide array of tasks. Furthermore, a multilingual team of translators and interpreters is skilled in various accents and dialects, ensuring that AI teams gain a deeper understanding of cultural subtleties across different languages and regions. This extensive expertise highlights Zuru's commitment to delivering high-quality, context-aware annotation solutions for a diverse range of clients.

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.

Aquarium's innovative embedding technology identifies significant issues in your model's performance and connects you with the appropriate data to address them. Experience the benefits of neural network embeddings while eliminating the burdens of infrastructure management and debugging embedding models. Effortlessly uncover the most pressing patterns of model failures within your datasets. Gain insights into the long tail of edge cases, enabling you to prioritize which problems to tackle first. Navigate through extensive unlabeled datasets to discover scenarios that fall outside the norm. Utilize few-shot learning technology to initiate new classes with just a few examples. The larger your dataset, the greater the value we can provide. Aquarium is designed to effectively scale with datasets that contain hundreds of millions of data points. Additionally, we offer dedicated solutions engineering resources, regular customer success meetings, and user training to ensure that our clients maximize their benefits. For organizations concerned about privacy, we also provide an anonymous mode that allows the use of Aquarium without risking exposure of sensitive information, ensuring that security remains a top priority. Ultimately, with Aquarium, you can enhance your model's capabilities while maintaining the integrity of your data.

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.

A platform designed for ML engineers that generates synthetic data, facilitating the creation of more advanced AI models. With straightforward APIs, users can quickly generate a wide variety of perfectly-labeled, photorealistic images as needed. This highly scalable, cloud-based system can produce millions of accurately labeled images, allowing for innovative data-centric strategies that improve model performance. The platform offers an extensive range of pixel-perfect labels, including segmentation maps, dense 2D and 3D landmarks, depth maps, and surface normals, among others. This capability enables rapid design, testing, and refinement of products prior to hardware implementation. Additionally, it allows for prototyping with various imaging techniques, camera positions, and lens types to fine-tune system performance. By minimizing biases linked to imbalanced datasets while ensuring privacy, the platform promotes fair representation across diverse identities, facial features, poses, camera angles, lighting conditions, and more. Collaborating with leading customers across various applications, our platform continues to push the boundaries of AI development. Ultimately, it serves as a pivotal resource for engineers seeking to enhance their models and innovate in the field.

DataSeeds.ai specializes in providing extensive, ethically sourced, and high-quality datasets of images and videos designed for AI training, offering both standard collections and tailored custom options. Their extensive libraries feature millions of images that come fully annotated with various data, including EXIF metadata, content labels, bounding boxes, expert aesthetic evaluations, scene context, and pixel-level masks. The datasets are well-suited for object and scene detection tasks, boasting global coverage and a human-peer-ranking system to ensure labeling accuracy. Custom datasets can be quickly developed through a wide-reaching network of contributors spanning over 160 countries, enabling the collection of images that meet specific technical or thematic needs. In addition to the rich image content, the annotations provided encompass detailed titles, comprehensive scene context, camera specifications (such as type, model, lens, exposure, and ISO), environmental attributes, as well as optional geo/contextual tags to enhance the usability of the data. This commitment to quality and detail makes DataSeeds.ai a valuable resource for AI developers seeking reliable training materials.

Human-powered data processing for AI and Automation. Our managed teams have helped hundreds of clients with use cases that range from simple and complex. Our proven processes provide high quality data quickly and can scale to meet your changing needs. Our flexible platform can be integrated with any commercial or proprietary tool so that you can use the right tool for your job. Flexible pricing and contract terms allow you to quickly get started and scale up or down as required without any lock-in. Clients have relied on our IT-Infrastructure to deliver high quality work remotely for nearly a decade. We were able to maintain operations during COVID-19 lockdowns. This allowed us to keep our clients running and added geographic and vendor diversity in their workforces.

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

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.

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.

HumanSignal's Label Studio Enterprise is a versatile platform crafted to produce high-quality labeled datasets and assess model outputs with oversight from human evaluators. This platform accommodates the labeling and evaluation of diverse data types, including images, videos, audio, text, and time series, all within a single interface. Users can customize their labeling environments through pre-existing templates and robust plugins, which allows for the adaptation of user interfaces and workflows to meet specific requirements. Moreover, Label Studio Enterprise integrates effortlessly with major cloud storage services and various ML/AI models, thus streamlining processes such as pre-annotation, AI-assisted labeling, and generating predictions for model assessment. The innovative Prompts feature allows users to utilize large language models to quickly create precise predictions, facilitating the rapid labeling of thousands of tasks. Its capabilities extend to multiple labeling applications, encompassing text classification, named entity recognition, sentiment analysis, summarization, and image captioning, making it an essential tool for various industries. Additionally, the platform's user-friendly design ensures that teams can efficiently manage their data labeling projects while maintaining high standards of accuracy.

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.

Kled serves as a secure marketplace powered by cryptocurrency, designed to connect content rights holders with AI developers by offering high-quality datasets that are ethically sourced and encompass various formats like video, audio, music, text, transcripts, and behavioral data for training generative AI models. The platform manages the entire licensing process, including curating, labeling, and assessing datasets for accuracy and bias, while also handling contracts and payments in a secure manner, and enabling the creation and exploration of custom datasets within its marketplace. Rights holders can easily upload their original content, set their licensing preferences, and earn KLED tokens in return, while developers benefit from access to premium data that supports responsible AI model training. In addition, Kled provides tools for monitoring and recognition to ensure that usage remains authorized and to detect potential misuse. Designed with transparency and compliance in mind, the platform effectively connects intellectual property owners and AI developers, delivering a powerful yet intuitive interface that enhances user experience. This innovative approach not only fosters collaboration but also promotes ethical practices in the rapidly evolving AI landscape.

OCI Data Labeling is a powerful tool designed for developers and data scientists to create precisely labeled datasets essential for training AI and machine learning models. This service accommodates various formats, including documents (such as PDF and TIFF), images (like JPEG and PNG), and text, enabling users to upload unprocessed data, apply various annotations—such as classification labels, object-detection bounding boxes, or key-value pairs—and then export the annotated results in line-delimited JSON format, which facilitates smooth integration into model-training processes. It also provides customizable templates tailored for different annotation types, intuitive user interfaces, and public APIs for efficient dataset creation and management. Additionally, the service ensures seamless interoperability with other data and AI services, allowing for the direct feeding of annotated data into custom vision or language models, as well as Oracle's AI offerings. Users can leverage OCI Data Labeling to generate datasets, create records, annotate them, and subsequently utilize the exported snapshots for effective model development, ensuring a streamlined workflow from data labeling to AI model training. Consequently, the service enhances the overall productivity of teams focusing on AI initiatives.

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.

Lightly intelligently identifies the most impactful subset of your data, enhancing model accuracy through iterative improvements by leveraging the finest data for retraining. By minimizing data redundancy and bias while concentrating on edge cases, you can maximize the efficiency of your data. Lightly's algorithms can efficiently handle substantial datasets in under 24 hours. Easily connect Lightly to your existing cloud storage solutions to automate the processing of new data seamlessly. With our API, you can fully automate the data selection workflow. Experience cutting-edge active learning algorithms that combine both active and self-supervised techniques for optimal data selection. By utilizing a blend of model predictions, embeddings, and relevant metadata, you can achieve your ideal data distribution. Gain deeper insights into your data distribution, biases, and edge cases to further refine your model. Additionally, you can manage data curation efforts while monitoring new data for labeling and subsequent model training. Installation is straightforward through a Docker image, and thanks to cloud storage integration, your data remains secure within your infrastructure, ensuring privacy and control. This approach allows for a holistic view of data management, making it easier to adapt to evolving modeling needs.

DataOcean AI stands out as a premier provider of meticulously labeled training data and extensive AI data solutions, featuring an impressive array of over 1,600 pre-made datasets along with countless tailored datasets specifically designed for machine learning and artificial intelligence applications. Their diverse offerings encompass various modalities, including speech, text, images, audio, video, and multimodal data, effectively catering to tasks such as automatic speech recognition (ASR), text-to-speech (TTS), natural language processing (NLP), optical character recognition (OCR), computer vision, content moderation, machine translation, lexicon development, autonomous driving, and fine-tuning of large language models (LLMs). By integrating AI-driven methodologies with human-in-the-loop (HITL) processes through their innovative DOTS platform, DataOcean AI provides a suite of over 200 data-processing algorithms and numerous labeling tools to facilitate automation, assisted labeling, data collection, cleaning, annotation, training, and model evaluation. With nearly two decades of industry experience and a presence in over 70 countries, DataOcean AI is committed to upholding rigorous standards of quality, security, and compliance, effectively serving more than 1,000 enterprises and academic institutions across the globe. Their ongoing commitment to excellence and innovation continues to shape the future of AI data solutions.

Understanding the shortcomings of models can be challenging, particularly in identifying which data caused poor performance and the reasons behind it. Galileo offers a comprehensive suite of tools that allows machine learning teams to detect and rectify data errors up to ten times quicker. By analyzing your unlabeled data, Galileo can automatically pinpoint patterns of errors and gaps in the dataset utilized by your model. We recognize that the process of ML experimentation can be chaotic, requiring substantial data and numerous model adjustments over multiple iterations. With Galileo, you can manage and compare your experiment runs in a centralized location and swiftly distribute reports to your team. Designed to seamlessly fit into your existing ML infrastructure, Galileo enables you to send a curated dataset to your data repository for retraining, direct mislabeled data to your labeling team, and share collaborative insights, among other functionalities. Ultimately, Galileo is specifically crafted for ML teams aiming to enhance the quality of their models more efficiently and effectively. This focus on collaboration and speed makes it an invaluable asset for teams striving to innovate in the machine learning landscape.

Cogito Tech is a leading AI data solutions provider specializing in data labeling and annotation services. We deliver high-quality data for applications across computer vision, natural language processing (NLP), and content services. Our expertise extends to fine-tuning large language models (LLMs) through techniques like Reinforcement Learning from Human Feedback (RLHF), enabling rapid deployment and customization to meet business objectives. The company is headquartered in the United States and was featured in The Financial Times’ FT ranking: The Americas’ Fastest-Growing Companies 2025 and Everest Group’s report Data Annotation and Labeling (DAL) Solutions for AI/ML PEAK Matrix® Assessment 2024 Services offered by Cogito: • Image Annotation Service • AI-assisted Data Labeling Service • Medical Image Annotation • NLP & Audio Annotation Service • ADAS Annotation Services • Healthcare Training Data for AI • Audio & Video Transcription Services • Chatbot & Virtual Assistant Training Data • Data Collection & Classification • Content Moderation Services • Sentiment Analysis Services Cogito is one of the top data labeling companies offers one-stop solution for wide ranging training data needs for different types of AI models developed through machine learning and deep learning. Working with team of highly skilled annotators, Cogito is an industry in human-powered and AI-assisted data labeling service at most competitive prices while ensuring the privacy and security of datasets.

Utilize Weights & Biases (WandB) for experiment tracking, hyperparameter tuning, and versioning of both models and datasets. With just five lines of code, you can efficiently monitor, compare, and visualize your machine learning experiments. Simply enhance your script with a few additional lines, and each time you create a new model version, a fresh experiment will appear in real-time on your dashboard. Leverage our highly scalable hyperparameter optimization tool to enhance your models' performance. Sweeps are designed to be quick, easy to set up, and seamlessly integrate into your current infrastructure for model execution. Capture every aspect of your comprehensive machine learning pipeline, encompassing data preparation, versioning, training, and evaluation, making it incredibly straightforward to share updates on your projects. Implementing experiment logging is a breeze; just add a few lines to your existing script and begin recording your results. Our streamlined integration is compatible with any Python codebase, ensuring a smooth experience for developers. Additionally, W&B Weave empowers developers to confidently create and refine their AI applications through enhanced support and resources.

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.

Your AI warrants top-notch data. With an impressive accuracy rate of 99%, you can eliminate the hassle of acquiring machine learning datasets using Tictag's innovative mobile data platform along with Truetag's rigorous quality control. Tictag’s pioneering mobile data platform integrates a user-friendly design with engaging, gamified features to generate high-quality datasets, all supported by our unique Truetag quality assurance system. This represents the pinnacle of technology-driven labeling. Tictag adeptly gathers and annotates even the most complex datasets with exceptional accuracy for AI and ML applications, ensuring rapid turnaround times. The process of data labeling has reached unprecedented levels of speed and simplicity. Complete it once and do it correctly; Tictag's technologically enhanced Truetag quality control guarantees that your data meets your specific requirements. Additionally, through Tictag, your data demands create opportunities for individuals seeking alternative income sources or aspiring to acquire new skills. Thus, Tictag not only enhances your AI capabilities but also contributes to skill development in the community.

Gramosynth is an innovative platform driven by AI that specializes in creating high-quality synthetic music datasets designed for the training of advanced AI models. Utilizing Rightsify’s extensive library, this system runs on a constant data flywheel that perpetually adds newly released music, generating authentic, copyright-compliant audio with professional-grade 48 kHz stereo quality. The generated datasets come equipped with detailed, accurate metadata, including information on instruments, genres, tempos, and keys, all organized for optimal model training. This platform can significantly reduce data collection timelines by as much as 99.9%, remove licensing hurdles, and allow for virtually unlimited scalability. Users can easily integrate Gramosynth through a straightforward API, where they can set parameters such as genre, mood, instruments, duration, and stems, resulting in fully annotated datasets that include unprocessed stems and FLAC audio, with outputs available in both JSON and CSV formats. Furthermore, this tool represents a significant advancement in music dataset generation, providing a comprehensive solution for developers and researchers alike.