As of August 2026, Latka tracks 13 data labeling software companies with $10M–$100M in annual revenue. They have combined revenues of $448.1M and employ 3.6K people. They have raised $227.3M and serve 500.6K customers combined.
Every company below sells data labeling software to other businesses and is ranked by its most recent annual revenue. Revenue, funding, headcount and customer figures come from CEO interviews on the Latka podcast, public company filings, and Latka estimates where a company has not disclosed a number.
Data labeling software is designed to facilitate the process of annotating data, which is crucial for the development of machine learning and artificial intelligence models. Users of this software can label various data types, including images, audio, and text, providing the necessary annotations that allow algorithms to recognize patterns and make predictions. The software streamlines workflows, enabling large datasets to be processed efficiently and ensuring data quality through collaborative tools and automated features. Typical use cases for data labeling software include applications in computer vision for object detection, natural language processing for text classification, and audio analysis for speech recognition. With common features like user-friendly interfaces, quality control mechanisms, and integration capabilities with machine learning frameworks, this software empowers data scientists, AI developers, and researchers to prepare their data sets comprehensively. The primary buyers often include tech companies, research institutions, and enterprises looking to enhance their AI solutions and analytics capabilities.
Sorting: Highest -> Lowest
Showing 10 of 13 companies ranked by annual revenue.
London, United Kingdom
Prolific helps AI developers, researchers, and organizations easily access the highest-quality human data. It is a technology company building the biggest pool of quality human data in the world and the ultimate platform to access it.
Stanford, California, United States
Pareto.AI is a talent-first human data collection platform for AI research, empowering the top 0.01% of expert labelers to deliver the highest-quality training data. Please note that all recruitment emails for project opportunities are sent from @pareto.ai email addresses. Additionally, our recruiters may reach out to potential candidates through Linkedin. If you would like to apply, visit: https://pareto.ai/careers/ai-trainer
San Francisco, California, United States
Developer of a data training platform intended for computer vision machine learning applications. The company's platform offers a visual workflow interface and system of record for the data labeling process, using annotation tools as well as quality control functionality and performance analytics, enabling business to reduces model development times and empowers data science teams to build great machine learning applications.
Lisbon, Portugal
Lyzer is an AI-powered data analytics and decision intelligence platform that helps businesses analyze data, generate insights, and automate data-driven decisions without requiring deep technical expertise.
New York, New York, United States
DataForce delivers high-quality, multimodal training data and services to power the next generation of AI. From large language models to voice, image, and video generation, DataForce supports AI innovators in tech, life sciences, automotive, and beyond with scalable, secure solutions for development, testing, and safety. Backed by cutting-edge technology and over one million data contributors, DataForce helps ensure AI systems are accurate, adaptable, and ready for real-world deployment. DataForce is part of TransPerfect, the world’s largest provider of language and AI solutions for global business, with offices in more than 140 cities worldwide. Learn more at www.dataforce.ai. Contact: [email protected]
Bengaluru, India
Karya is a data cooperative, providing economically underprivileged Indians with respectable digital jobs and a road out of poverty. It is established as the world's first ethical data company.
San Francisco, California, United States
SuperAnnotate is the leading platform for building, fine-tuning, iterating, and managing your AI models faster with the highest-quality training data. With advanced annotation and QA tools, data curation, automation features, native integrations, and data governance, we enable enterprises to build datasets and successful ML pipelines. Partner with SuperAnnotate’s expert and professionally managed annotation workforce that can help you quickly deliver high-quality data for building top-performing models.
Sunnyvale, California, United States
At Deccan, our mission is to help AI teams worldwide model with pristine data—at scale and with speed. Your models are only as good as the data, and the data is only as good as the humans behind it. We push the boundaries of advanced models in reasoning, agentic capabilities, STEM, coding, multimodality, and many other use cases for leading companies, including Google and Snowflake. Our proprietary Human + AI vetting process, combined with our comprehensive Delivery + Quality playbook, enables us to deploy top experts from our talent pool of over 500,000 specialists across more than 25 domains, ensuring pristine quality in our deliverables. If you are looking for a reliable data partner for your AI development, please reach out to us at [email protected].
San Jose, California, United States
Developer of vision processing technology intended for autonomous vehicles. The company's auto labeling system produces training data with minimal human input, and a semi-supervised learning-based SVNet training tool allows customers to enhance SVNet by themselves during mass production projects, enabling autonomous vehicles to reach the next level of safety, accuracy and driver convenience through proper real-world detection, tracking, segmentation and classification.
San Jose, California, United States
Founded in 2017, Deepen AI is the only safety-first data lifecycle tools and services company focused on unlocking the potential of machine learning and AI for autonomous systems. Our tools and services are customizable to suit the needs of enterprises as well as start-ups.
Latka tracks 13 data labeling software companies with $10M–$100M in annual revenue. Together they generate $448.1M in annual revenue and employ 3.6K people.
prolific.com is the largest, with $72.4M in annual revenue, founded in 2014.
The average data labeling software company in this list makes $34.5M a year, across 13 companies with reported revenue. They serve 500.6K customers combined.
Ranked by annual revenue, the leaders are prolific.com, Pareto.AI, Labelbox, Lyzer and DataForce.
The 13 data labeling software companies with $10M–$100M in annual revenue tracked here have raised $227.3M in disclosed funding between them.
- Must provide tools for labeling diverse data types including images, text, and audio. - Should support both manual labeling and automated annotation processes. - Must include collaboration features for teams to work on data labeling tasks. - Must ensure quality control mechanisms to verify the accuracy of labeled data. - Not just a data management tool; must also provide data annotation capabilities.
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