Top 50 Data Annotation Platform - Series B

SuperAnnotate is an AI data platform that integrates dataset creation, curation, and model evaluation into a single workflow, enabling users to build and fine-tune high-quality models efficiently. The platform addresses the challenges of data annotation and model performance assessment by providing customizable tools and access to a global marketplace of trained annotation teams.

Kognic offers a data annotation platform specifically designed for sensor-fusion datasets, enabling efficient management and accurate labeling of complex multi-sensor data. By utilizing an auto-label co-pilot, Kognic reduces annotation time by up to 68%, addressing the high costs and complexities associated with generating and curating representative datasets.

V7 is an AI training data platform that provides high-quality image and video annotations for computer vision models, utilizing AI-assisted labeling tools to enhance accuracy and efficiency. The platform addresses the challenge of slow and error-prone data labeling processes by streamlining workflows and enabling rapid deployment of training data.

Kili Technology provides tailored data annotation and evaluation services for large language models, utilizing expert-led project management to streamline the data pipeline. This approach eliminates data bottlenecks, enabling companies to enhance model performance and accelerate AI project deployment.

Encord is an AI data development platform that enables computer vision and multimodal AI teams to manage, curate, and annotate diverse data types, including images, videos, and documents, all in one place. By transforming unstructured data into high-quality training datasets, Encord enhances AI model performance and accelerates labeling processes, resulting in significant improvements in accuracy and efficiency.

Datagen Technologies develops simulated data technology that generates scalable, bias-free datasets with automatic annotation capabilities. This technology addresses the challenges of data scarcity and bias in machine learning, enabling more accurate and reliable model training.

Centaur Labs provides a medical AI platform that utilizes a global network of expert annotators for precise data labeling across various modalities, including text, audio, and imaging. This approach addresses the challenge of slow and inconsistent data annotation by ensuring high-quality labels through automated quality checks and performance metrics.

Labelbox operates a data training platform that utilizes AI-assisted labeling and a global network of experts to provide high-quality data curation and evaluation for machine learning applications. This platform addresses the challenge of efficiently managing large-scale data labeling and evaluation, enabling businesses to accelerate model development and improve AI performance.

HumanSignal provides a data labeling platform that combines automation and human oversight to prepare training data, fine-tune large language models, and evaluate AI outputs. This solution enhances model accuracy and efficiency while ensuring compliance and data security across various use cases and data types.

Superb AI offers an end-to-end training data platform that automates data preparation and curation, enabling rapid and systematic dataset creation for AI model development. This solution addresses the inefficiencies in data handling, allowing organizations to streamline their AI workflows and enhance model deployment speed.

Voxel51 provides the FiftyOne platform, which enables machine learning and computer vision teams to efficiently curate, visualize, and manage large datasets while automating the identification of annotation errors. This technology enhances model performance by ensuring high-quality data is readily available for training and evaluation, streamlining the development of visual AI applications.

Snorkel Flow is an AI data development platform that enables data scientists to programmatically label and annotate large datasets, significantly reducing the time required for data preparation. By leveraging domain knowledge and automated techniques, the platform enhances the accuracy and efficiency of training data for specialized AI applications in fields like bioinformatics and natural language processing.

Outlier AI connects AI development companies with a global network of domain experts for specialized data annotation and model evaluation. The platform facilitates remote, flexible work, enabling experts to improve AI model accuracy through tasks like rating AI outputs and evaluating multi-modal data.

Roboflow provides a platform for developers to manage image data and streamline the process of training and deploying computer vision models. By offering tools for dataset annotation, preprocessing, and one-click model training, it simplifies the complexities of computer vision projects, enabling faster development and deployment.

DatologyAI develops automated data curation tools that utilize modality-agnostic algorithms to identify and eliminate redundant and noisy data points without requiring labels. This technology enables organizations to optimize their deep learning model training, significantly improving performance while reducing computational costs.

DataLoops provides a data management and annotation platform that automates the preprocessing and curation of unstructured visual data, enabling the rapid generation of machine-readable datasets. This solution enhances the efficiency of AI application development by streamlining data pipelines and integrating human feedback for improved accuracy.

The startup offers a machine learning-based data platform that integrates and verifies data from thousands of sources, including business names, addresses, and operational hours. This platform provides companies with accurate records essential for analyzing human movement patterns and making informed decisions.

The startup offers a Chrome extension that enables users to annotate web content directly in their browser, facilitating real-time collaboration and knowledge sharing. This tool addresses the challenge of fragmented information by allowing users to highlight, comment, and organize insights from various online sources in one accessible location.

Worlds provides an AI platform that utilizes real-time video and sensor data to create custom AI applications for enterprise operations. This technology enables companies to automate processes such as hazard detection, asset tracking, and environmental compliance, significantly reducing human effort and improving operational efficiency.

The startup offers a feature store workflow platform that streamlines data acquisition, integration, and feature engineering for data scientists. By automating repetitive data preparation tasks, it enables teams to focus on delivering actionable insights more efficiently.

Parallel Domain provides a synthetic data platform that generates high-fidelity camera, LiDAR, and radar data for training and testing AI perception systems. This technology enables developers to simulate diverse scenarios in procedurally generated environments, reducing the risks and costs associated with real-world data collection.

The startup offers a visual recognition platform that autonomously processes diverse visual data, including infrared and X-ray images, while accurately tagging objects of interest. This technology enhances operational efficiency and ensures high-quality results for clients across various industries.

The startup offers a creative collaboration and online proofing platform that centralizes feedback and automates the review process for marketing content. By streamlining annotation and commenting workflows, the software enhances review efficiency, allowing marketing professionals to focus on brand governance and compliance.

Surge AI provides a data labeling platform that utilizes human feedback to enhance the training of large language models (LLMs). By delivering high-quality labeled data, Surge AI enables organizations to improve the accuracy and performance of their NLP applications.

Provides a platform for building, deploying, and scaling computer vision models tailored to specific industry tasks, such as object detection and optical character recognition. By integrating with tools like Snowflake, it enables organizations to perform visual AI tasks directly on their data without moving it, reducing deployment time by 80% and supporting over 1 billion annual image inferences with 99.99% uptime.

Synthesis AI offers a synthetic data generation platform specifically designed for computer vision applications, enabling the creation of privacy-compliant and unbiased datasets. This technology addresses the need for high-quality training data in areas such as biometric identification, autonomous vehicle behavior simulation, and augmented reality, facilitating faster model development and deployment.

Clarifai offers an end-to-end AI lifecycle platform that automates data labeling, model training, and deployment, enabling organizations to build and operationalize AI applications efficiently. By standardizing workflows and optimizing compute resources, the platform reduces development time and costs, allowing enterprises to scale AI solutions rapidly.

Defined.ai provides a marketplace for ethically sourced training data, specializing in diverse datasets for speech recognition, natural language processing, and medical image analysis. The company addresses the need for high-quality, bias-free data that complies with ethical and legal standards, enabling organizations to develop AI solutions responsibly and effectively.

Dataiku is an enterprise AI and machine learning platform that enables organizations to prepare data, build models, and deploy AI applications at scale. It addresses the challenge of fragmented data workflows by providing a unified environment for collaboration, governance, and operational efficiency across various teams and industries.

The startup develops an open-source DataOps platform that enables data teams to transform large datasets efficiently, facilitating collaborative data management and testing of data pipeline changes. This solution addresses the challenges of data integration and decision-making by providing a framework that enhances the scalability and reliability of data operations.

Cleanlab automates data error detection and correction using AI-powered algorithms to enhance the quality of datasets for machine learning and analytics. This technology addresses issues such as label noise, outliers, and data drift, significantly reducing the time and cost associated with data management while improving model performance.

Pienso provides a no-code platform for training and deploying customized Large Language Models (LLMs) using both structured and unstructured data, enabling users to categorize, label, and analyze their data efficiently. The solution ensures data privacy by operating in the user's environment, allowing businesses to gain real-time insights while maintaining control over their sensitive information.

Edge Impulse provides a platform for developing embedded machine learning models that run on various edge devices, including microcontrollers and gateways. This technology enables manufacturers to optimize sensor data processing, reduce bill of materials costs, and accelerate time to market for their products.

Coactive AI is a machine learning platform that automates metadata generation for unstructured image and video data, achieving 95% accuracy without manual tagging. This technology enhances content discoverability and optimizes media management systems, enabling businesses to unlock the value of their digital archives.

Mindee provides an AI-driven platform for precise data extraction from various document types, significantly reducing manual data entry errors by up to 30%. The solution enables businesses to automate complex workflows, enhancing operational efficiency and cutting turnaround times by 57%.

1touch.io provides a sensitive data intelligence platform that utilizes supervised AI to achieve 98.6% accuracy in structured data and 100% accuracy in unstructured data across various environments, including on-premises and multi-cloud systems. The platform enables organizations to identify and protect sensitive information in real-time, addressing the challenge of unknown data exposure and compliance with privacy regulations.

The startup operates an AI-driven platform that automates data collection from third-party and proprietary sources for insurance underwriting. By providing traceability and full lineage of underwriting decisions, the platform reduces the manual workload of underwriters, enhancing efficiency and accuracy in the underwriting process.

DotData is an end-to-end data science automation platform that utilizes AI and machine learning to extract actionable insights from complex, multi-source data sets in minutes. It enables organizations to identify key performance drivers and enhance predictive model accuracy without requiring specialized coding skills.

The startup provides a straightforward tool for collecting and organizing data from API endpoints, enabling users to efficiently manage their data flow. This solution addresses the challenge of data fragmentation by simplifying the integration and accessibility of diverse API data sources.

Anomalo provides automated AI-driven data quality monitoring for enterprise data warehouses, utilizing unsupervised machine learning to detect anomalies and validate data integrity without requiring code. This solution addresses the issue of unreliable data by enabling rapid identification and resolution of data quality problems, ensuring accurate and trustworthy insights for business operations.

Flatfile provides a data onboarding platform that utilizes a JavaScript snippet to import, map, and normalize customer data from spreadsheets into software applications. This technology reduces the time and cost associated with manual data cleanup, ensuring high-quality, validated data for seamless integration into business systems.

The startup offers a cloud-based data analytics platform that processes and visualizes large omics datasets, including genomics, transcriptomics, and proteomics, to elucidate the molecular mechanisms underlying cellular phenotypes. This technology enhances decision-making in drug research and development, enabling scientists and clinicians to efficiently identify potential treatments for diseases.

The startup develops a data platform that utilizes algorithms and analytical tools to process large datasets, enabling investors to track portfolio companies, competitors, and market sectors. This platform provides actionable insights that help fund managers identify investment opportunities and manage risks, ultimately enhancing investment performance.

Ataccama is an AI-powered enterprise platform that integrates data quality, master data management, and metadata management to enhance data governance. The platform enables organizations to maintain accurate and consistent data across systems, improving decision-making and operational efficiency.

Dasera is a Data Security and Privacy Management (DSPM) platform that automates the discovery, classification, and governance of structured and unstructured data across on-premises, cloud, and hybrid environments. By providing precise visibility and control over data access and usage, Dasera minimizes the risks associated with data breaches and regulatory non-compliance.

The startup offers a creative measurement platform that analyzes images and videos by tagging content and cross-referencing it with brand guidelines and digital ad performance. This technology enables clients to enhance the effectiveness of their visual marketing by providing actionable insights derived from artificial intelligence.

Gulp Data provides data valuation, lending, and monetization services that enable companies to leverage their data as a financial asset. By offering rapid data valuations and pre-approved data loans, Gulp Data addresses the challenge of accessing non-dilutive funding for data-rich businesses.

This platform integrates internal and external data sources to provide actionable insights for sales and marketing teams. By analyzing structured and unstructured data, the platform helps businesses make data-driven decisions to optimize sales strategies and improve marketing performance.

Tecton provides an enterprise-ready feature store that automates the creation and management of data pipelines for machine learning applications, enabling data scientists to focus on feature engineering without the complexities of infrastructure. By delivering real-time, accurate data at scale, Tecton accelerates model deployment by up to 80% and enhances model performance through rapid feature experimentation.

Acryl Data provides an open-source data management platform, DataHub, and its enterprise counterpart, DataHub Cloud, which enable organizations to ensure reliable data and compliance for AI deployment. By integrating real-time metadata updates and governance features, Acryl Data helps businesses mitigate risks and streamline their AI workflows.