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Top 62 Data Labeling Software SaaS Companies in May 2026

As of May 2026, there are 62 SaaS companies in Data Labeling Software. They have combined revenues of $4.5B and employ 15.1K people. They have raised $1.9B and serve 502.5K customers combined.

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.

Companies
62
Revenue
$4.5B
Funding
$1.9B
Employees
15.1K

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Top Data Labeling Software Companies

Showing 10 of 62 companies ranked by annual revenue.

1
Scale AI

San Francisco, California, United States

Scale AI Inc. is a machine learning data annotation platform that provides high-quality training data to help develop and improve artificial intelligence (AI) models.

Revenue
$2B
Customers
1K
Year founded
2016
Funding
$1.6B
Team size
5.8K
Growth
129.89%
2
Surge AI

San Francisco, California, United States

The world's most powerful data labeling and RLHF platform, designed for the next generation of AI

Revenue
$1.4B
Customers
-
Year founded
2018
Funding
$25M
Team size
121
Growth
12.5%
3
sama.com

San Francisco, California, United States

Sama is the global leader in ethical data annotation and model evaluation solutions for computer vision, generative AI and other major applications of artificial intelligence. Our solutions minimize the risk of model failure and lower the total cost of ownership through an enterprise ready ML-powered platform, actionable data insights uncovered by proprietary algorithms, and a highly skilled on-staff team of over 5,000 data experts. 25% of Fortune 50 companies, including GM, Ford, Microsoft and Google, trust Sama to help deliver industry-leading ML models. Ethical AI is responsible AI, and as a Certified B-Corp, we’ve pioneered an impact model that harnesses the power of markets for social good, and has been proven to meaningfully improve employment and income outcomes for those with the greatest barriers to formal work. So far, helping more than 65,000 people lift themselves out of poverty.

Revenue
$470.6M
Customers
-
Year founded
2008
Funding
-
Team size
4.3K
Growth
-
4
Snorkel AI

Redwood City, California, United States

Snorkel AI is a software company that provides a platform for building and managing training data for machine learning models. Their platform allows developers and data scientists to label data programmatically and efficiently, using a combination of weak supervision and human-in-the-loop labeling. By automating the data labeling process, Snorkel AI enables companies to train machine learning models faster and with higher accuracy, while reducing the cost and time required for data labeling. The company was founded in 2019 by a group of researchers from Stanford University and is based in Palo Alto, California.

Revenue
$148M
Customers
-
Year founded
2019
Funding
$135.3M
Team size
776
Growth
302.17%
5
TranscribeMe

San Francisco, California, United States

TranscribeMe is the global leader in speech to text transcription services, providing accurate and reliable transcription solutions to thousands of clients in a wide range of industries. With a worldwide network of highly trained transcriptionists, TranscribeMe is able to provide high-quality transcriptions at scale, fast turnaround times, affordable pricing, and the highest level of security. Our technology enables us to deliver solutions to industries that require the highest levels of consistent accuracy and high security, including the medical, legal, and AI training spaces. At the core of our offering is a proprietary workforce management & task distribution platform that utilizes the very latest in AI to ensure all kinds of tasks are done efficiently and at scale. This is paired with a network of highly trained & skilled global pool of freelancers to enable unstructured audio/video data to be accurately transcribed and annotated in a variety of languages and at any volume. Unique to TranscribeMe is the flexibility our platform and workflows allow. Our capabilities enable us to manage all types of content, and have processes that are compliant with HIPAA, GDPR, and CCPA, as well as content containing PCI & PII. We understand the security of your data is a top priority and have built our platform around ensuring data is stored, accessed, and managed with the highest information security protocols in place. With a global team and headquartered in the Bay Area, California, we work with companies all over the world and provide 24/7 support. We would be delighted to work with you on your transcription needs.

Revenue
$108.6M
Customers
-
Year founded
2011
Funding
$15.6M
Team size
987
Growth
-
6
prolific.com

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.

Revenue
$72.4M
Customers
-
Year founded
2014
Funding
-
Team size
600
Growth
-
7
Labelbox

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.

Revenue
$50M
Customers
50
Year founded
2018
Funding
-
Team size
232
Growth
125.23%
8
Lyzer

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.

Revenue
$50M
Customers
500K
Year founded
2024
Funding
$11.7M
Team size
56
Growth
-
9
DataForce

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]

Revenue
$46M
Customers
-
Year founded
2020
Funding
-
Team size
418
Growth
-
10
SuperAnnotate

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.

Revenue
$27.4M
Customers
-
Year founded
2018
Funding
-
Team size
249
Growth
-

Inclusion Criteria

- 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.