Insights Concurrency, Inc. receives two 2020 Microsoft US Partner Awards: Industry – Manufacturing & Azure – AI and Machine Learning

Concurrency, Inc. receives two 2020 Microsoft US Partner Awards: Industry – Manufacturing & Azure – AI and Machine Learning

BROOKFIELD, WI (July 16, 2020) — Concurrency, Inc. today announced it has been awarded two 2020 Microsoft US (MSUS) Partner Awards: Industry – Manufacturing and Azure – AI and Machine Learning.  

The company was honored among a field of top MSUS partners for its leadership in customer impact, solution innovation, deployment and exceptional use of advanced features in Microsoft technologies over the past year.

The Manufacturing award recognized Concurrency’s technical expertise and business outcome-based approach to drive digital transformation throughout the manufacturing industry in the areas of AI and machine learning, cloud migration, security and workplace productivity.

The AI and Machine Learning award recognized Concurrency’s artificial intelligence work in the areas of machine learning and AI for Good, including a project that expands workplace opportunities for people with cognitive disabilities.

“In a time of global uncertainty, it’s incredibly gratifying to do work that positively impacts people’s everyday lives,” said James Savage, founder and president of Concurrency. “Both of these awards demonstrate the power of artificial intelligence to impact the greater good.” 

Savage continued, “Only a fraction of job-seeking individuals with cognitive disabilities are employed. I commend our talented team as well as our outstanding client and community partners. People with disabilities are especially vulnerable to COVID-19 pressures, as Microsoft noted in its recent announcement of an initiative to help 25 million people worldwide acquire digital skills. We applaud that effort and are proud to be aligned with it.”

Concurrency’s Data & AI practice was among the first to harness the power of Microsoft Azure’s AI technologies to improve workplace experiences while also driving operational efficiencies.