Rick Oppedisano, president and CEO of Delta Bravo AI, shares key takeaways from his experience helping manufacturers make the most of the mountains of data they collect. He lists the three key roles he considers foundational to ensuring predictive analytics goes to work to optimize product assembly.
Delta Bravo was chosen from over 100 select South Carolina startups to receive the SCRA’s prestigious Acceleration Grant. “We are excited to approve a $50,000 Acceleration Grant for Delta Bravo,” says SCRA Executive Director Bob Quinn. These grants are awarded to early-stage companies that are demonstrating fast growth and promise in their market. Delta Bravo’s product and leadership team are innovating with machine learning and artificial intelligence. We look forward to seeing their impact on South Carolina.”
SCRA is a state-chartered organization that fosters job creation and grows South Carolina’s Innovation Economy. Through SCRA’s Entrepreneurial Programs, early-stage companies are provided mentoring and grants and may be eligible for an investment from SC Launch, Inc. The program is open to qualified South Carolina companies in the Advanced Materials/Manufacturing, Information Technology and Life Sciences industries.
“We are honored and excited to receive this award,” says Delta Bravo CEO Rick Oppedisano. “SCRA’s choice validates our solution and continues to solidify our relationship with the state of South Carolina.”
Chartered in 1983 by the State of South Carolina as a public, non-profit corporation, SCRA fosters South Carolina’s Innovation Economy by supporting entrepreneurs, enabling academic research and its commercialization, and connecting industry to innovators.
Delta Bravo CTO John McAliley and CEO Rick Oppedisano are presenting “3 Lessons Learned in Developing a Production AI Platform” to the Charlotte Bots and AI meetup group on July 11, 2018.
“There’s a ton of interest in AI and Machine Learning,” says Oppedisano, “we want to help people understand where they can start and also learn from our journey. The lessons we’ve learned along the way could save them months of technology evaluation and development time and in some cases, thousands of dollars in system costs.”
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