Top 50 Data Annotation Platform - Series B

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

The company provides a unified clinical genomics platform that automates NGS variant calling, annotation, and report generation using a curated knowledgebase of over 350,000 inferencing rules. Integrated HL7/FHIR and API interfaces embed results directly into EMR, LIS, and data warehouses, while professional services support assay design, validation, and regulatory compliance. The solution is assay‑agnostic and available as SaaS, on‑premise, or hybrid for clinical and reference laboratories and IVD manufacturers.

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.

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.

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.

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.

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.

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.

aiMotive provides an end‑to‑end platform that automates sensor data ingestion, AI‑assisted labeling, and photorealistic simulation while delivering modular, ISO‑26262‑aligned perception, planning, and control software for radar‑camera‑only ADAS and automated driving. The integrated cloud‑based NPU emulator enables faster‑than‑real‑time software‑in‑the‑loop testing within CI/CD pipelines, helping OEMs and Tier‑1 suppliers reduce development time and validation costs for L2‑L4 features.

Atlan is an active metadata platform that consolidates and enriches metadata from various data sources, enabling data teams to visualize column-level lineage and implement role-based access controls. This platform addresses the challenge of data discovery and governance by providing a centralized control plane for trusted, AI-ready data, enhancing compliance and user adoption across organizations.

Accern provides a no-code natural language processing (NLP) platform that classifies content to enhance research workflows and improve model accuracy across various industries. By automating the classification of key information, the platform helps businesses reduce costs and increase revenue through more efficient data utilization.

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.

Hyperscience is an intelligent document-processing platform that utilizes machine learning to automate the extraction and validation of data from various document types, achieving over 96% accuracy and 99% automation. The platform addresses the inefficiencies in manual document processing, enabling enterprises to significantly reduce turnaround times and operational costs.

Singleron provides an integrated platform that combines tissue preservation, automated 8‑channel dissociation, and high‑throughput single‑cell processing with a suite of library preparation kits for scRNA‑seq, V(D)J, and other multi‑omics assays. The system includes the Matrix NEO™ and Tensor instruments for up to 30 000 cells per run and cloud‑based analysis tools (CeleLens™ and SynEcoSys®) that deliver code‑free QC, annotation, and visualization. Optional contract services enable end‑to‑end sample handling, sequencing, and bioinformatics for academic, biotech, and pharma projects.

Provides a low-code computer vision platform that integrates into business operations to analyze visual data for industries such as manufacturing, logistics, and safety. It improves defect detection, real-time monitoring, and compliance by enabling organizations to automate visual inspections and reduce operational inefficiencies.

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.

Provides a data analysis platform that standardizes and integrates bioprocess data from various hardware and software sources, ensuring consistency and quality control. The platform replaces manual workflows with automated tools for data management, statistical analysis, and predictive modeling, enabling faster experimentation, reduced cycle times, and improved collaboration across teams.

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.

Swapp provides an AI-driven platform that automates construction documentation tasks, including dimensioning and tagging, to enhance accuracy and consistency in architectural projects. By reducing manual workload by up to 80%, it enables firms to streamline their workflows and focus on design rather than tedious documentation.

The startup offers a data visualization platform that enables users to explore and analyze data through an extensive library of reusable visualizations. This platform enhances understanding and collaboration among developers, data scientists, journalists, and educators by providing tools to effectively interpret complex data sets.

Flatfile (Obvious) provides an AI‑driven data preparation platform that automates extraction, schema mapping, cleaning, transformation, and validation of enterprise files from any source. The system combines a smart extractor, semantic AI mapping, real‑time validation with AutoFix, and natural‑language bulk edits, while offering both no‑code configuration and extensible SDKs in a secure, collaborative workspace. It is aimed at data onboarding teams and system integrators building pipelines for ERP systems such as NetSuite and Workday.

The platform enables organizations to build, manage, and scale AI‑ready data products within a collaborative environment. It leverages modular components and integrated governance to accelerate development and deliver reusable, high‑quality data assets that support business and AI initiatives.

The startup has developed an artificial intelligence platform for biomarker discovery and sequencing analysis, focusing on extracting biosignatures from single-cell and multi-omics data. This platform enables physicians to efficiently analyze complex disease patterns, reducing data processing time and costs while enhancing insights for patient stratification.

Provides an enterprise-scale Intelligent Document Processing (IDP) platform, CMR+, that uses AI to automate the extraction and organization of data from structured and unstructured documents, including handwritten notes, images, and tables. By reducing manual processing time and improving data accuracy, it enables organizations in industries like banking, insurance, and supply chain to streamline operations and make data-driven decisions.

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.

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%.

The startup offers a data intelligence platform that automatically collects and organizes non-personally identifiable data from encrypted user identities to corporate revenue statements. By providing subscription-based access and consulting services, the platform enables businesses to gain transparency into their performance and make informed decisions based on accurate data analysis.

Anonos provides the Data Embassy platform, a policy‑as‑code engine that encodes GDPR, CCPA and other regulations into machine‑readable policies and enforces them automatically on data wherever it resides—on‑prem, public cloud, or partner sites. The platform applies protection at ingestion, transformation, and export, supports cross‑border residency routing, AI data provenance, and on‑demand synthetic or masked test data, while logging all actions to an immutable audit trail accessible via API. It enables regulated enterprises to share and analyze sensitive data faster without compromising compliance.

Gretel is a multimodal synthetic data platform that utilizes generative AI and privacy-enhancing technologies to create artificial datasets that mirror the statistical properties of real data. This enables developers to train and validate AI models while maintaining data privacy and accelerating access to high-quality data.

Provides an AI-powered data discovery platform that enables users to find, understand, and trust their data through natural language search, automated documentation, and SQL query simplification. It reduces reliance on IT by offering self-service analytics while ensuring data governance, compliance, and security at scale.

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.

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.