
CloudFactory
Founded Year
2010Stage
Series B - II | AliveTotal Raised
$77.3MLast Raised
$65M | 5 yrs agoMosaic Score The Mosaic Score is an algorithm that measures the overall financial health and market potential of private companies.
-12 points in the past 30 days
About CloudFactory
CloudFactory focuses on providing workforce solutions for machine learning and business process optimization. The company offers services such as data labeling, accelerated annotation, and human-in-the-loop automation, which support workflows and fill gaps in artificial intelligence (AI) and automation. CloudFactory primarily serves sectors such as the autonomous vehicles industry, finance, healthcare, insurance, and retail. It was founded in 2010 and is based in Reading, United Kingdom.
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CloudFactory's Product Videos


CloudFactory's Products & Differentiators
Data Annotation Solution
A fully managed data annotation service that includes both the tooling and workforce for one monthly price.
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Research containing CloudFactory
Get data-driven expert analysis from the CB Insights Intelligence Unit.
CB Insights Intelligence Analysts have mentioned CloudFactory in 3 CB Insights research briefs, most recently on Feb 20, 2024.

Feb 20, 2024
The AI training data market map
Sep 29, 2023
The machine learning operations (MLOps) market map
Jul 31, 2023
The data quality market mapExpert Collections containing CloudFactory
Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.
CloudFactory is included in 2 Expert Collections, including HR Tech.
HR Tech
4,044 items
The HR tech collection includes software vendors that enable companies to develop, hire, manage, and pay their workforces. Focus areas include benefits, compensation, engagement, EORs & PEOs, HRIS & HRMS, learning & development, payroll, talent acquisition, and talent management.
Artificial Intelligence
14,767 items
Companies developing artificial intelligence solutions, including cross-industry applications, industry-specific products, and AI infrastructure solutions.
Latest CloudFactory News
Sep 11, 2024
Posted on Google (US), Appen (Australia), IBM (US), Oracle (US), TELUS International (Canada), Adobe (US), AWS (US), Alegion (US), Cogito Tech (US), Anolytics (US), AI Data Innovation (US), Clickworker (Germany), CloudFactory (UK), CapeStart (US), DataPure (US), LXT (Canada), Precise BPO Solution (India). Data Annotation and Labeling Market by Component, Data Type, Application (Dataset Management, Sentiment Analysis), Annotation Type, Vertical (BFSI, IT and ITES, Healthcare and Life Sciences) and Region – Global Forecast to 2027. The global data annotation and labeling market is expected to grow at a compound annual growth rate (CAGR) of 33.2% during the forecast period, rising from an estimated USD 0.8 billion in 2022 to USD 3.6 billion by 2027. Key factors driving this growth include the increasing demand for improving machine learning models and the necessity to train AI algorithms for enhanced performance. Since AI algorithms are trained rather than programmed, there is a growing need for vast amounts of accurately labeled, high-quality data to ensure optimal efficiency. By vertical, healthcare and life sciences segment to register highest CAGR during forecast period The data annotation and labeling market has been segmented based on vertical into BFSI, IT and ITES, Healthcare and Life Sciences, Telecom, Reatil and Consumer Goods, Automotive, Government, Defense and Public Agencies and other verticals. Businesses are using data annotation techniques to reliably and efficiently identify huge volumes of Al training data with minimum human assistance. Healthcare organizations are now able to do faster research in the field of automated patient diagnosis due to the adoption of healthcare training data for the development of sophisticated Al applications. This has driven the demand for high-quality annotated medical datasets to develop high-performance healthcare solutions. In May 2021, Cogito Tech had announced the expansion of its medical annotation capabilities in pathology, ophthalmology & cardiology. During the forecast period the healthcare and life sciences segment is anticipated to grow at a highest CAGR. By applications, corporate communication is projected to register largest market size during the forecast period The data annotation and labeling market has been segmented based on applications into corporate communication, training and development, and marketing and client engagement. Corporate communications solutions facilitate communication with employees irrespective of their geographic locations. Executives can build a more personal relationship with the workforce with the use of data annotation and labeling tools. Due to the growing need for businesses to facilitate communications with both internal and external workers, the market for corporate communications via data annotation and labeling is developing. During the forecast period this segment is anticipated to register the largest market size. By data type, audio is anticipated to grow at a highest CAGR during the forecast period The data annotation and labeling market has been segmented based on data type into image, text, video, and audio. Among these data type, audio is anticipated to grow at a highest CAGR during the forecase period. It adds appropriate metadata and tags in audio recordings to enable machines to comprehend sounds and speech based on their emotional, sentimental, and semantic contexts for training natural language processing systems. Audio annotation can be used for a variety of purposes, such as organizing audio files, enhancing searchability, and making it simpler to find specific parts of an audio recording. However, the most important use of audio annotations is in the training and development of speech recognition systems, including chatbots, virtual assistants, security systems, and more. North America anticipated to account for largest market size during forecast period Among the regions, North America is anticipated to account for the largest market size during the forecast period. The presence of various key market players and the demand for highly customized data sets curated by trained professionals would fuels the growth of data anootation and labeling market across the region. Due to its well-established economies, countries across North America are witnessing significant investments in data annotation and labeling projects. Unique Features in the Data Annotation and Labeling Market The data annotation and labeling market offers a variety of techniques tailored to different data types, including text, image, video, and audio. These techniques range from basic labeling to complex tasks such as semantic segmentation, object recognition, and sentiment analysis. A defining feature of this market is its focus on producing high-quality, accurately labeled datasets. These datasets are essential for training machine learning and AI models. Data annotation platforms offer scalability to handle large datasets efficiently. Whether a company needs to annotate small sets of data or large volumes, the market provides flexible solutions that can be scaled according to business requirements. Many data annotation services incorporate human-in-the-loop systems, where human annotators collaborate with automated tools. This combination of human oversight and AI-driven automation ensures higher accuracy, especially for complex tasks that require nuanced judgment, such as emotion detection or complex object classification. Companies in the data annotation and labeling market offer customizable tools that allow businesses to define specific labeling criteria according to their project needs. These tools can be adapted for industry-specific requirements, ensuring that the annotations align with the particular demands of sectors such as finance, healthcare, and retail. Major Highlights of the Data Annotation and Labeling Market A key highlight of the market is the rising need for high-quality annotated data to train AI and ML algorithms. As AI models become more integral to industries such as healthcare, finance, automotive, and eCommerce, the requirement for massive, accurately labeled datasets has surged, driving the expansion of the annotation market. The integration of human annotators alongside automated systems is a crucial feature of the market. This HITL approach ensures that complex and nuanced tasks—such as image recognition, sentiment analysis, or medical diagnosis—are handled with greater accuracy, blending human judgment with machine efficiency. The increasing adoption of automation within the data annotation process is another market highlight. AI-powered annotation tools are being used to streamline repetitive tasks, speed up processes, and reduce costs while maintaining high accuracy. The data annotation market serves a wide range of industries. In healthcare, it supports medical imaging analysis; in automotive, it aids in training autonomous vehicle algorithms; and in retail and eCommerce, it powers recommendation engines and personalized marketing efforts. One of the major highlights of the market is the emphasis on high-quality, accurately labeled data. Ensuring that AI models are trained on precise datasets is critical to their success. Market players are increasingly focusing on creating annotation systems that prioritize accuracy to deliver better AI outcomes. Top Companies in the Data Annotation and Labeling Market Some of the major data annotation and labeling market vendors are Google (US), Appen (Australia), IBM (US), Oracle (US), TELUS International (Canada), Adobe (US), AWS (US), Alegion (US), Cogito Tech (US), Anolytics (US), AI Data Innovation (US), Clickworker (Germany), CloudFactory (UK), CapeStart (US), DataPure (US), LXT (Canada), Precise BPO Solution (India), Sigma (US), Segment.ai (US), Defined.ai (US), Dataloop (Israel), Labelbox (US), V7 (UK), LightTag (Germany), SuperAnnotate (US), Scale (US), Datasur (US), Kili Technology (France), Understand.ai (Germany), Keylabs (Israel), and Label Your Data (US). Appen is one of the world’s leading companies in data for the AI Lifecycle. With more than 25 years of experience in data sourcing, data annotation, and human model evaluation, the company helps businesses introduce cutting-edge AI systems. In addition to the market’s most sophisticated AI-assisted data annotation platform, its expertise includes a worldwide pool of over one million professional contractors who know more than 235 languages in over 70,000 locations across 170 countries. To offer the highest level of quality and efficiency, Appen has developed specialized capabilities that are integrated into products and processes. It offers a wide range of products and services, enabling global leaders in technology, automotive, financial services, retail, healthcare, and governments to launch top-tier AI products confidently. Appen’s AI platform provides the highest-quality training data for ML projects by fusing the human intelligence of over a million individuals around the world with cutting-edge models. The platform can also annotate various types of raw data, including text, video, image, and audio, to produce the precise ground truth required for models. TELUS International develops, builds, and distributes cutting-edge digital solutions to improve customer experience for disruptive and international businesses. The company’s services help its clients rapidly adopt next-generation digital technology and produce superior business results over their digital transformation journey. The integrated solutions and capabilities of TELUS International include AI Data Annotation, Ground Truth Annotate which enable teams to be more efficient, rapid, and precise in producing quality AI training datasets at scale. They also include digital strategy, innovation, consulting, and design, as well as digital transformation and IT lifecycle solutions. TELUS International partners with companies across high-growth sector verticals, such as tech and games, communications and media, eCommerce and fintech, healthcare, and travel and hospitality, to fuel corporate growth at all stages. Oracle is a world leader in offering a wide range of products, services, and solutions that are intended to satisfy the needs of business IT environments, including platforms, applications, and infrastructure. It operates through three business segments: cloud and license, hardware, and services. Oracle’s customers include businesses of all sizes, governments, academic organizations, and resellers. The company offers its goods and services both directly and indirectly through a worldwide sales force and the Oracle Partner Network. The business focuses in developing, distributing, and marketing databases, application software, and hardware systems. It offers solutions such as Cloud Infrastructure Data Labeling, Cloud Infrastructure AI services and Machine Learning services to build, train, deploy, and manage custom learning models. It is present in over 175 countries and caters to more than 4,30,000 customers across the globe in various verticals such as banking, telecommunications, engineering and construction, financial services, healthcare, insurance, public sector, retail, and utilities verticals. LightTag, based in Germany, is a prominent player in the data annotation and labeling market, specializing in text data. Their platform is designed to streamline and enhance the efficiency of text annotation tasks such as entity recognition, classification, and sentiment analysis. LightTag’s tools support collaborative annotation, enabling teams to work together effectively while maintaining consistency and quality. The platform also incorporates robust quality control mechanisms to ensure the accuracy and reliability of annotated data, making it a valuable resource for training AI and machine learning models. Keylabs, headquartered in Israel, is a significant player in the data annotation and labeling market, offering comprehensive solutions for various types of data including images, videos, and text. Their platform is designed to support high-quality annotation processes essential for training AI and machine learning models. Keylabs focuses on providing scalable and customizable annotation services, ensuring precision and efficiency through advanced tools and a managed workforce. Their services cater to diverse industries such as autonomous vehicles, healthcare, and retail, helping clients enhance their AI applications with accurately labeled data. Media Contact
CloudFactory Frequently Asked Questions (FAQ)
When was CloudFactory founded?
CloudFactory was founded in 2010.
Where is CloudFactory's headquarters?
CloudFactory's headquarters is located at The Blade, Abbey Street, Reading.
What is CloudFactory's latest funding round?
CloudFactory's latest funding round is Series B - II.
How much did CloudFactory raise?
CloudFactory raised a total of $77.3M.
Who are the investors of CloudFactory?
Investors of CloudFactory include FTV Capital, Weatherford Capital Management, The Social Entrepreneurs' Fund, Dolma Fund Management, The Rockefeller Foundation and 5 more.
Who are CloudFactory's competitors?
Competitors of CloudFactory include Scale, Snorkel AI, Super.AI, Aya Data, Datasaur and 7 more.
What products does CloudFactory offer?
CloudFactory's products include Data Annotation Solution and 4 more.
Who are CloudFactory's customers?
Customers of CloudFactory include Matterport, Sartorius, Luminar, True Lark and Ibotta.
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Compare CloudFactory to Competitors

Labelbox develops a training data platform for machine learning teams to build real-world artificial intelligence (AI) solutions. The platform consists of label editor tools for batch, and real-time labeling workflows, collaboration, quality review, analytics, and more. It serves the government, retail, insurance, manufacturing, and healthcare sectors. It was founded in 2018 and is located in San Francisco, California.

Defined.ai provides a range of pre-collected and structured training datasets, including text, voice, and image data, and hosts an online marketplace where these datasets can be bought, sold, or commissioned. Defined.ai caters to the AI development sector, providing data that aids in the creation of fair, accessible, and ethical AI solutions. The company was founded in 2015 and is based in Seattle, Washington.
Select Star develops an artificial intelligence data crowdsourcing platform. The company provides a service that performs client-requested data collection/semi-automatic labeling through the users of its mobile app Cash Mission, examining all tasks to ensure high-quality data. Select Star was founded in 2018 and is based in Daejeon, South Korea.

Alegion is a company that focuses on data annotation and collection services, operating within the artificial intelligence and machine learning industry. The company offers services such as data collection, data annotation, and quality control, aimed at transforming unstructured data into high-quality, model-ready training data. Alegion primarily serves sectors such as healthcare, hospitality, insurance, manufacturing, retail, security, software, and sports. It was founded in 2012 and is based in Austin, Texas.

24x7offshoring specializes in data collection, data annotation, and localization services for various industries. The company offers a platform for artificial intelligence (AI) and machine learning data collection, data labeling, and outsourced services, as well as iterative AI training models. It caters to sectors such as science, technology, education, medical research, and public service. The company was founded in 2020 and is based in New Delhi, India.

Sama specializes in providing high-accuracy data annotation solutions for the development of computer vision AI models across various industries. The company offers a suite of services including image and video annotation, 3D point cloud labeling, and data validation to support machine learning professionals and AI team leads. Sama primarily serves sectors such as ADAS & autonomous vehicles, retail & e-commerce, consumer tech & media, robotics & manufacturing, and agriculture & food. It was founded in 2008 and is based in San Francisco, California.
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