According to Gartner, “The democratization of ML techniques in the last few years has seen the proliferation of model development practices but unfortunately a majority of these models are neither operationalized nor deployed at scale. This capability is becoming critical for the survival of data science teams and this urgency will push ModelOp toward the Plateau of Productivity in two to five years.”
“We got ahead of the market when we started this venture, convinced that the unique characteristics of data science and machine learning (DS/ML) models would require new organizational and technical approaches in order to realize their value, especially within large enterprises” said Pete Foley, CEO of ModelOp.
Foley continued, “Our expanding customer base, and the level of activity we are seeing in the industry overall strongly validates our vision and makes us extremely excited for this next phase of growth.” ModelOp’s customers include five of the top 10 largest financial institutions, as well as Fortune 500 manufacturers, insurers, and credit bureaus.
Model Operations, “DevOps for AI”
According to The Forrester Wave: Multimodal Predictive Analytics And Machine Learning Solutions, Q3 2018, “Data scientists regularly complain that their models are only sometimes or never deployed. A big part of the problem is organizational chaos in understanding how to apply and design models into applications. But another big part of the problem is technology. Models aren’t like software code, because they need model management. And models must make it into applications.”
“Rapid advances in AI and ML are putting powerful tools into the hands of a growing group of professional and “citizen” data scientists, resulting in an explosion of models that can add significant value across the enterprise,” said Stu Bailey, co-founder and CTO of ModelOp.
Bailey continued, “In this new, model-driven world, no single development platform will prevail, as organizations will continually look for the best tool for each model use case. Our mission at ModelOp is to provide our customers with an independent model operations platform that maximizes model velocity, effectiveness and accountability and avoids dev platform lock-in.”
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