Spare5's Smart Crowdsourcing Platform Delivers Detailed Insights into Unstructured Data
SEATTLE, WA: With an aim to provide human insights to the product leaders for managing the unstructured data, Spare5 has released Intelligent Crowdsourcing Platform. The platform provides a scalable way to handle large volumes of data, and helps them quickly improve and utilize all the data.
The large data sets are reduced to micro tasks for enrichment, clean-up and labeling; to achieve these tasks Crowdsourcing takes the help of business experts. The platform proves to be a beneficial solution to the product owners, by allowing them to train powerful artificial intelligence models, providing assistance in researching, augmenting directories and many more.
Spare5’s platform incorporates a combination human insights and automation to overcome the complex problem of utilizing unstructured data. It includes one of the most competitive and fastest growing data sources in present world like video, social media content, images and text messages.
"Our mission is to tap the world's potential brainpower," says Matt Bencke, Founder and CEO of Spare5.
Spare5’s idea of having a secure network of qualified individuals has paid off. Having right human in right loop helps them to deliver the best insights into unstructured data and enables the product leaders to make the best use of data to build efficient products.
Spare5’s prime customers include Avvo, Expedia, Getty Images, GoPro, and Sentient Technologies. "Spare5 is valuable part of our product development for Sentient Aware, with Spare5's unique ability to access people with specific domain experience, we are able to quickly validate our AI-generated models," asserts Myles Brundage, Director at Sentient Technologies.
Spare5 follows a rigorous quality assurance process; with the proprietary machine learning algorithms the firm is able to filter task results for better accuracy and quality. In order to constantly improve accuracy, Spare5's Reputation Engine applies machine learning to rate each individual's performance by domain.