Sight Machine Named a Gartner “Cool Vendor in Manufacturing Operations, 2015”
SAN FRANCISCO, May 7, 2015 – Sight Machine, developer of the leading Manufacturing Analytics platform, today announced it has been named a Gartner Inc. “Cool Vendor in Manufacturing Operations” for 2015. Sight Machine is one of four companies profiled in the report.
Sight Machine’s Manufacturing Analytics platform transforms heterogeneous machine and sensor data into actionable insights, helping manufacturers tackle critical challenges in quality, performance and operations. Unlike general-purpose Big Data tools, Sight Machine is built for the specific needs of manufacturers.
“The amount of content and data that is not corralled in manufacturing operations is staggering. Gartner estimates that, on average, 70% of the data generated in the production environment (either by the production processes directly or through audits and inspections) is never put to plausible use. In turn, organizations do not have a complete understanding of their processes or product content. This prevents targeted improvements and systemic adjustments to production processes, product designs and other continuous improvement efforts,” says Gartner’s report, written by Rick Franzosa and Simon F. Jacobson and published April 29, 2015.
“World-class manufacturers know production data contains invaluable insight, but for a long time the data has been impossible to use,” said CEO and co-founder Jon Sobel. “Manufacturing Analytics transforms how manufacturers use their data. Sight Machine takes technologies hardened through 20 years of Internet and puts them to work for factories, solving perennial challenges in efficiency and quality.”
About Sight Machine
Sight Machine is the developer of the world’s leading Manufacturing Analytics platform. Sight Machine’s Manufacturing Analytics solution transforms machine and sensor data into actionable insights, enabling manufacturers to address critical challenges in quality and operations. Sight Machine provides manufacturers with real-time reporting of quality problems; retrospective analysis of product variation and failures; predictive analytics to support process improvement; and defensive recordkeeping and proof of quality for customers.
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