At ScaleHub, we process tens of millions of documents and billions of characters for our customers on a scaled AWS cloud solution annually. Our customers generally face the same challenges: Handling structured and unstructured inbound data always requires some human intervention for data processing and exception handling, including correcting OCR results and fine-tuning AI engines. Using Amazon Mechanical Turk’s platform, we engage thousands of MTurk users around the world daily. Our customers benefit from faster turnaround times, higher quality and an optimized cost structure. We reshape the future of document processing.

As a strategy and innovation group that's constantly inventing new research tools, we love using MTurk to test out prototypes of our new tools. The flexibility of MTurk allows us to quickly try out new things that wouldn't make sense with traditional research panels, such as single question experiments.

The F&B industry has always operated at the mercy of changing tastes and preferences of consumers. Our goal is to surface consumer insights and spot emerging trends, so our clients can effectively respond with effective strategies. Workers on Amazon Mechanical Turk respond to our requests to gather information from menus, websites, and other channels. We are able to leverage these human collective insights to better understand customer needs and uncover important market trends.

At Radiant Solutions, we source trillions of satellite pixels every day, and understanding every object, location, and action on this planet is an enormous challenge. Using Amazon Mechanical Turk's crowdsourcing platform, large communities of users sift through massive volumes of data to tag important objects, features, or locations. These labeled datasets serve as ground truth that helps us train and refine our advanced geospatial algorithms.

Today, brands are capable of producing hundreds of millions of social conversations and stories across the digital media spectrum. For Zignal, natural language processing is critical to rapidly synthesizing this massive amount of media data in real-time. Amazon Mechanical Turk makes it possible to generate human-annotated data for machine learning algorithms quickly and at scale. By harnessing the power of the crowd to obtain high-quality labeled data, we were able to measure and build effective models applicable across the media spectrum.