Uptake, leader in industrial artificial intelligence (AI), has launched the ECO FUTURE AWARD to offer fleet management software free to five public sector, nonprofit or social impact organizations that aim to reduce their environmental impact. The winning organizations will receive Uptake’s fleet management optimization solution for eighteen months, as well as mentorship from Uptake.org, the philanthropic and civic innovation arm of Uptake, which is using data science and machine learning to address the world’s most pressing problems
“One of the initiatives of Uptake.org is to address the reality that often the organizations that can benefit most from predictive insight are those with limited technology resources,” said Brad Keywell, Uptake’s CEO. “Uptake’s fleet optimization products ensure that critical vehicles — ambulances, for example, as well as vehicles of organizations like the American Red Cross — are reliable and not subject to unexpected failure. With Uptake.org, the Uptake team shares our solutions for societal good, and this offer of our Asset IO software is another step on our journey of impact.”
By deploying Asset IO for Good, organizations can lower operational costs through advance insight of vehicle component failure as well as optimized fuel management. With the additional benefit of reducing carbon emissions. Uptake.org is delivering the value of predictive analytics to the social sector. Applications will be accepted until September 6 at https://www.uptake.org/award.
“We have partnered with Uptake to put telematics devices on many of our fleet vehicles. This allows us to see where our vehicles are, where they’ve been, and when they’ll need maintenance, so we can respond even quicker,” said Jim McGowan, Director of Information Management & Situational Awareness at the American Red Cross of Chicago & Northern Illinois.
Uptake’s Asset IO software uses artificial intelligence (AI) to create business value from operational data. Traditional asset management only covers routine maintenance tasks. Today’s asset-intensive environments require a new approach with industrial data science generating OEM-agnostic insights, predictions and recommendations for any asset. The result is higher uptime of critical equipment, lowered operations cost and improved productivity.