We’re excited to announce we have secured $65 million in growth equity funding from FTV Capital and Weatherford Capital.

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Nobody does it quite like you. Except us.

We’re CloudFactory. Masters of the art and science of labeling data for Machine Learning and more using virtually any tool on the planet.

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What We Offer

For
Machine
Learning

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Dedicated, tech-forward, and scalable teams building the most accurate and reliable training datasets to bring AI to life through computer vision, NLP, and predictive analytics applications.

For
Core Data
Processes

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Flexible workforce solutions to accurately process high-volume, routine tasks and time-sensitive data that powers your core business.

 
 
 
 
 

Use Cases

From spatial data and object recognition, to semantic understanding and 3D point cloud annotations, we bring a greater understanding of the visual world with detailed, accurately tagged images and datasets to improve the user experience.

Accurately tag and annotate images and videos, train sentiment, semantic, syntax, and context analysis, and categorize and process statements, all to prepare datasets for smarter natural language processing algorithms across the automation ecosystem.

Save time and money by efficiently and accurately transcribing detail and leveraging optical character recognition from a host documents as well as image, video, and audio so core business processes can be executed rapidly. Additionally, datasets can be leveraged to gain key insights and metrics for more actionable, real-time reporting, allowing you to focus your valuable time elsewhere.

Machine learning and AI requires the use of large sets of data. Getting to an accurate data entry automation process takes extensive human interaction to train general datasets for large-scale application.

Aggregate and transcribe critical data by researching similar products from different resources to complete missing information, enhance competitive analysis, optimize sales data, or establish price comparison at massive scale.

Our Clients

How it Works

Context matters. Unlike crowdsourced solutions, our teams work with you to understand the backdrop of your business and the nuances of your project. Our CloudWorkers are vetted for both skill and character, receiving growth and training opportunities that naturally result in high-quality work.

Each WorkStream is driven by a proven methodology focused on scaling your data processing needs with tight quality controls for maximum task precision. Our process, including daily sprints, paired learning, and iterative feedback loops, supports rapid time to market which means faster time to value for you.

Our proprietary platform is an integral part of every WorkStream, reducing the friction of working with an external team and provides visibility to every step of the process. Our technology powers your project with enhanced team workspaces, real-time quality visualization, and seamless collaboration tools.

 
 
 

Resources

Data Engineering, Preparation, and Labeling for AI 2019

The big challenge for organizations looking to make use of advanced machine learning is getting access to large volumes of clean, accurate, complete, and well-labeled data to train ML models. AI analyst firm Cognilytica explores the race to usable data and evaluates the requirements for solutions that clean, augment, and annotate data for AI.

Crowd vs. Managed Team

Data scientists at Hivemind tested CloudFactory’s managed workforce and a leading crowdsourcing platform’s anonymous workers to complete a series of the same tasks, ranging from basic to more complicated, to determine which team delivered the highest-quality structured datasets and at what relative cost.

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