CloudFactory

Recent Posts

The New AI Factory Model: How to Scale Quality Training Data

A Production Problem (Solved)

When Henry Ford attempted to produce the Model T at a rapid pace and with high quality, he ran into a problem. It was difficult to organize teams of specialized workers to assemble automobiles, and with so many workers needed to scale the process, it was highly inefficient. To make matters worse, late delivery of parts caused pile-ups of workers vying for space to work and delays in production.

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The Life of a Data Scientist [Infographic]

As the volume of the world’s big data grows at a staggering speed, so too does the need for people who know how to extract knowledge, insights, or solutions from it. Today’s data scientist must have both the technical skills to solve complex data problems and the curiosity to seek out the hidden problems data can solve.

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CloudFactory’s Mike Riegel Talks Machine Learning at Google I/O Extended

Google’s three-day I/O’18 conference in Mountainview, Calif., last week brought together developers from around the globe for hands-on learning, discussion with experts, and a look at Google’s latest developer products. The conference also featured Google I/O Extended sessions held in technology hubs across the country, including a panel discussion that featured CloudFactory Chief Revenue Officer Mike Riegel.

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CloudFactory Calls for Entries to AIconics Awards at London Tech Week

CloudFactory invites tech disruptors to enter the fifth annual AIconics Awards at 2018 London Tech Week. AIconics is the world’s only independently judged artificial intelligence (AI) award program. The ceremony, to be held at Kensington Palace on June 12, celebrates the best in AI and innovation that is taking shape around the globe.

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Solving the Dirty Data Problem: Clean-Data Practices for Tech Innovators [Ebook]

Data is today’s gold for businesses, representing huge potential value. But there’s a catch: the data must be uncovered, clean, and structured.

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Ibotta Boosts Data Processing Accuracy and Speed During Busiest Retail Season

Our latest client success story shares how Ibotta, a cash-back rewards app, partnered with CloudFactory to improve accuracy and processing time on its important data-verification work. Retail consumers use Ibotta to submit photos of receipts for cash-back rewards from brands. With nearly 22 million downloads, it is one of the most frequently used shopping apps in the United States.

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People in the AI Tech Stack [Infographic]

For all of AI’s promises, we still need people to do a lot of work behind the scenes to make it all possible. People collect, enrich, clean, and prepare data for AI systems to operate accurately and optimally. In fact, data scientists spend countless hours cleaning and combining datasets, a process commonly referred to as “data wrangling.”

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CloudFactory Named One of ‘10 Best Tech Startups in Durham’

Earlier this month, The Tech Tribune recognized CloudFactory as one of the 10 Best Tech Startups in Durham. The list of tech startups based in Durham, N.C., was the result of research on each company’s revenue potential, leadership team, brand and product traction, and competitive landscape.

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The Workforce Strategy Behind CloudFactory’s 'People Who Care'

One of our clients said it best: “CloudFactory has people who care.” It’s true: our teams are known for high quality work, and they love the role they play in working with the world’s most innovative technology companies. Since 2008, we have helped hundreds of companies grow their businesses by providing a highly scalable, managed workforce to be an extension of their teams.

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3 Steps to Get Clean, Structured Data You Trust

It’s their least favorite part of the job, yet it consumes most of their time. Data wrangling – or gathering and preparing dirty data so it can be used in critical business applications – is the biggest problem in data science today, according to a Kaggle survey. So how can you get clean, structured data you can trust?

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