https://store-images.s-microsoft.com/image/apps.51882.dc5de646-cc3e-4d37-9d08-ea54b471cffa.cf970e0e-5b10-441c-a856-a6a3bbd334ae.913a373e-36dd-42aa-a6d1-b0acca736bea
MAKANA
by Mobius Logic
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MAKANA is a MLOps platform that makes it easy for data scientists and developers to collaborate.
Data Science and AI are becoming an integral part of every industry, yet their integration into regular enterprise operations is still a challenge. According to Gartner 60% of AI models never get operationalized.
MAKANA, from Mobius Logic, is a cloud-based MLOps platform that makes it easy for data scientists and software application developers to implement DevOps for Machine Learning (ML) through comprehensive support for all phases of the ML life cycle. The MAKANA Designer allows data scientists to build ML models faster, automate the testing of several algorithms to deliver the best ML model, and to jump from proof-of-concept to a live ML model in a few clicks. MAKANA enhances the data scientists' productivity by automating tedious and simple tasks and integrating their activities into the DevOps pipeline so they are ready to release to production the moment the ML model is validated. Using MAKANA, enterprises and government agencies can now let AI drive value in every corner of their business by enabling collaboration between AI teams and business leaders, expanding business processes to include AI and data science teams, and automating workflows and share knowledge across various teams using the MAKANA Enterprise Portal.
Our customers use MAKANA to:
(1) streamline and automate the end-to-end ML life cycle and tie it to existing DevOps processes
(2) enhance collaboration between data scientists, application developers and business users
(3) integrate data science and AI projects into the core enterprise operations by enabling easy access to validated ML models and faster retraining of current ML models.
Built on Microsoft Azure, MAKANA supports all phases of the ML model life-cycle with full support for popular, open-source Python packages such as scikit-learn, TensorFlow, PyTorch, and MXNet.
At a glance
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