Data Science has gotten us to the point of collecting servers full of manufacturing data. We can do some analytics. But there are miles to go before we sleep.
This press release crossed my email stream last week. I haven’t time to interview the founder–that will come later. But here is a teaser.
Data Science Pioneer Drew Conway Closes $2.5M in Seed Funding to Bring Machine Learning to Industrial Operations
New venture Alluvium delivers “Mesh Intelligence” to close the machine-to-human gap
Alluvium, developers of Mesh Intelligence solutions that harness machine learning insights for real-time applications in industrial use cases, today announced $2.5 million in seed funding led by investors IA Ventures, Lux Capital, and Bloomberg Beta. The machine learning venture is running pilot projects of its Mesh Intelligence technology in fleet management, and oil and gas, among other vertical industrial applications.
Alluvium aims to conquer one of big data’s greatest unsolved challenges for complex industrial operations with expert human operators. Alluvium’s breakthrough Mesh Intelligence solution frees the data from these proprietary systems, transforms it into rich information streams, and provides real-time insights to human operators for immediate action.
“The commoditized big data stack is fundamentally broken for complex industrial operations,” said Drew Conway, Founder and CEO at Alluvium. “Modern industrial assets and hardware are continuing to be instrumented by OEMs who have not considered how these heterogeneous streams of machine data should be leveraged in the overall workflow and data strategy of the organization. And the modern analytics ‘stack’ — where data is moved and crunched in back end systems — does not meet the real-time requirements of human operators at the edge.”
Conway, who earned his PhD at NYU, is a leading expert in the application of computational methods to social and behavioral problems at large-scale. He started his career in counter-terrorism as a computational social scientist in the U.S. intelligence community and is known for his venn diagram definition of data science as well as applying data science to study human decision making.
At the core of Alluvium’s Mesh Intelligence platform is unique technology for extracting data from all elements of complex industrial operations — tablets, sensors, as well as industry-specific assets — with no expectations of compute resources or network bandwidth. This breakthrough allows machine learning processing to occur at the edge of systems where human operators need data most — in-real time.
“The early days of big data were about capturing and storing the vast amounts of new information streaming from devices in manufacturing, transport, medicine and more,” said Mike Olson, co-founder and Chief Strategy Officer at Cloudera, and a seed investor in Alluvium. “As that technology has matured, the more important and more interesting problem has become: What can we learn from all that data? Alluvium is focused on extracting meaning from streaming data coming from hardware that instruments all sorts of industries. The company augments human expertise with its powerful machine learning technology to make customers smarter and help them operate better.”
Independent research and surveys show the massive economic opportunity for IoT and machine learning across industrial use cases. A report by Jabil found that “$1.9 trillion dollars of economic value could be created by the use of IoT devices and asset tracking solutions.” For U.S. oil and gas suppliers — an industry where Alluvium has had significant early traction — the daily cost of unplanned downtime at a refinery can reach $1.7 million per day, and the daily cost of unplanned downtime for liquid natural gas drillers can top $11 million per day. A recent McKinsey report found that “car data monetization could be as high as $750 billion by 2030” — which has far-reaching implications for fleet management. Analyst firm Gartner forecasted more than 6 billion connected devices will be in use worldwide in 2016 supporting more than $265 billion in services. And in a 2015 “Moving Toward the Future of the Industrial Internet” report by GE and Accenture, 84% of executives expected Big Data to shift the competitive landscape within the next year.
“Bringing machine intelligence into the physical world is an incredibly difficult task,” said Shivon Zilis, partner at Bloomberg Beta. “We were excited to back Alluvium because of their unique insights into how complex industrial systems could be transformed by predictive engines.”
Read Alluvium Founder’s Perspective on Starting the Company