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.

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.

Klleon provides an AI-powered platform for automated data labeling and annotation services. The system accelerates the preparation of high-quality training datasets necessary for machine learning model development. This service streamlines the workflow for computer vision and NLP projects by ensuring data accuracy and consistency at scale.

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.

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.

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.

Outlier AI connects domain experts with leading AI companies to provide human feedback for improving large language models (LLMs). Experts perform tasks such as writing challenging prompts, creating grading rubrics, and rating AI-generated answers to enhance model accuracy. The platform offers flexible, remote work opportunities for subject matter experts to earn income while gaining hands-on experience in AI training.

Toloka provides specialized AI training data for complex models, including Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF). They leverage a global network of AI tutors to generate high-quality, diverse datasets for applications like coding copilots and conversational agents.

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.

Encord provides a multimodal data layer infrastructure for training and deploying physical AI systems across various modalities like video, LiDAR, and sensor fusion. The platform supports the entire AI lifecycle, from data collection and automated labeling to dataset curation and post-training model alignment. This unified solution enables AI teams to manage and scale complex data workflows for robotics, autonomous vehicles, and generative AI applications.

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.

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.

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.

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.

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 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.

Latent Labs provides curated, version‑controlled datasets for computer vision, natural language processing, and speech applications, delivered via secure API or bulk download. Its platform combines automated preprocessing pipelines with expert‑validated annotations and integrated compliance checks (e.g., GDPR, HIPAA) to ensure data quality and legal safety. The service also offers on‑demand custom data collection for enterprise AI teams and research labs.

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.

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.

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.

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 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.

Sahara AI provides a platform for building and hosting customizable, enterprise‑grade autonomous AI agents that can execute real‑world tasks and integrate securely with existing tech stacks. It also offers an on‑demand global data‑service workforce for end‑to‑end data collection, labeling, enrichment, and validation, supported by serverless infrastructure and blockchain‑based governance for transparent usage and micropayment billing.

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.

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.

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.

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.

Coactive provides a Multimodal AI Platform designed to accelerate content workflows by processing visual assets. The platform automatically generates rich, contextual metadata for videos and images at scale, enabling powerful semantic search and content discovery. This capability allows enterprises to enhance personalization, streamline content moderation, and optimize content performance analysis.

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.

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.

Provides an AI-powered dental platform that detects oral diseases with high precision, educates patients using annotated imaging, and automates insurance claim submissions and reviews. By reducing administrative workload by 90% and accelerating claim decisions to five times faster, it improves efficiency for dentists, insurers, and dental service organizations while enhancing patient care and outcomes.

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.

Prolific provides a platform for researchers to access high-quality data from a global community of over 200,000 vetted participants, enabling rapid collection of detailed responses for surveys and AI training tasks. The service addresses the challenge of slow and unreliable data acquisition by allowing researchers to launch studies in 15 minutes and receive responses within 2 hours.

Enable Medicine provides a cloud‑based platform that consolidates multimodal biological data—such as single‑cell, spatial, omics, imaging, and clinical metadata—into a unified atlas. Using proprietary AI/ML methods, including graph neural networks and spatial deep learning, the platform generates interpretable insights for target identification, biomarker discovery, patient stratification, and trial design, helping biopharma and academic researchers accelerate therapeutic development.

SmarterX provides specialized AI models that ingest, enrich, normalize, and structure product data from sources such as PDFs, labels, and data sheets, delivering accurate ingredient, hazard, and regulatory information for retail catalogs. The platform combines large‑language‑model intelligence with expert‑curated rules and a human‑in‑the‑loop verification layer to ensure compliance while reducing classification costs by up to 50×. Integrated data can be exported to ERP, PLM, or compliance systems, helping retailers manage safe handling, shipping, storage, and disposal at scale.

The startup develops data management software that utilizes artificial intelligence and machine learning to automate the identification, categorization, and storage of investment documents. This technology reduces manual data entry and latency, enhancing the efficiency of managing alternative investment data for businesses.

Explorium provides a data science platform that utilizes augmented data discovery and feature engineering to deliver high-quality, proprietary data signals for sales and marketing teams. This technology enables businesses to identify and prioritize the most relevant leads, significantly improving conversion rates and reducing data acquisition costs.

Flywheel offers a cloud-native platform that centralizes medical imaging data, providing searchable metadata, automated curation, and scalable compute for AI model training. The system includes role‑based access controls and 21 CFR Part 11 compliance, enabling secure multisite collaboration and regulatory‑ready dataset preparation. It also supports open‑source “Gears” plug‑ins and APIs for custom analysis pipelines.

SeqOne provides a clinical decision support platform that utilizes AI-driven bioinformatics to analyze next-generation sequencing (NGS) data for germline and somatic variants. The platform enhances diagnostic accuracy and efficiency by identifying complex genomic events that standard pipelines often overlook, thereby improving patient outcomes in precision medicine.

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.

Ocrolus is an AI-driven document automation platform that utilizes machine learning and human validation to analyze financial documents, enhancing accuracy in data extraction and risk management. The platform addresses the challenges of manual document review and fraud detection in the digital lending ecosystem, enabling faster and more reliable financial decision-making.

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.

DigitalOwl is an AI-powered platform that transforms unstructured medical records into structured data, enabling faster and more accurate reviews for insurance and legal professionals. By automating the medical review process, it reduces processing time by up to 72% while maintaining an accuracy rate of 97% or higher.

Alkymi develops an AI-powered platform that automates the extraction and transformation of unstructured investment data into structured, actionable datasets, enabling seamless integration with existing financial systems. This solution addresses the inefficiencies in managing diverse investment document workflows, allowing firms to process data faster and make informed, data-driven decisions.

The startup offers a cloud-based research data management platform that automates workflows for biomedical research, enabling collaborative studies and machine learning applications. This platform enhances data scalability and analysis, facilitating multicenter clinical trials and accelerating the pace of scientific discoveries.

Mapped provides an AI-powered data infrastructure platform that automates the discovery, extraction, and normalization of data from building systems, sensors, and vendor APIs. This technology enables property owners and facility operators to efficiently access and integrate real-time data, significantly reducing the time spent on asset discovery and enhancing operational efficiency.

This company offers an AI-powered optical character recognition (OCR) technology that extracts data from images, including barcodes and QR codes, directly on devices. Their solution converts scanned text into editable data without requiring a server connection, enabling offline data extraction for various applications.

Carta Healthcare combines artificial intelligence with expert clinical data abstractors to enhance the speed and quality of clinical data abstraction for healthcare registries. This approach addresses the inefficiencies of traditional data abstraction methods, which are often time-consuming, labor-intensive, and costly, by delivering high-quality data more efficiently.