The Data Collection Challenge

When you need a large dataset with which to train AI, you have a wide range of options – but not all of them are good. 

Confronted with a need for data, some companies turn to public data sets. But often these were never intended to support AI, and raise issues of data quality and bias. Similar problems apply to scraping data off the internet – with added legal risk.  

When companies try to collect data themselves, programs become difficult to scale and tough to manage – whether they recruit internally or try to crowdsource. And even with the best of intentions, getting a high-quality, representative sample of properly collected and annotated data requires is often beyond even enterprise capabilities.  

Data Sets for Modern AI

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Image Data

Pactera EDGE builds data sets to train AI to recognize certain types of images, or for optical character recognition (OCR) scenarios such as invoices, business cards, and restaurant menus.
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Voice Data: LoopTalk™

Custom voice recordings in a variety of settings, accents, and contexts are key to training robust AI models, with applications ranging from customer ordering to employee skill development.
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Parallel Data for NLP

We deliver bilingual or multilingual sets of parallel content to train Natural Language Processing or to establish baseline models for machine translation.
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Why Pactera EDGE?

All in OneForma™

A single, powerful platform handles everything from user recruitment to workflows to analytics.

Global Resources

With a talent pool of hundreds of thousands of contributors globally, we build properly weighted and unbiased data sets.

Data Security

Strong confidentiality and robust data security measures ensure that your data stays yours.