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Features
Deploy
The ability to rapidly and effortlessly create fault-tolerant, high-availability, and dependable cloud-based production environments opens up new horizons for teams aiming to bring their models into real-world operation quickly.
MLOne Features
ML Model Deployment with MLOne:
Fast, Easy, Reliable
Fast, Easy, Reliable
Unlike the traditional approach that requires crafting extensive infrastructure code and configuring environments on EC2 or EKS, MLOne offers a ready-made solution.
Users no longer need to be DevOps experts. The process is condensed into a few clicks, making it easy to select the required instances or even an elastic cluster.
A unique feature of MLOne is the capability to create auto-scalable ML services directly from Jupyter Notebook.
There's no longer a need to configure each tool separately.
The integration with frameworks like PyTorch, TensorFlow, Keras, MLFlow, Scikit-learn, Spark-mlib, Triton, ONNX, and many others provides maximum flexibility and toolset options.
There's no longer a need to configure each tool separately.
The integration with frameworks like PyTorch, TensorFlow, Keras, MLFlow, Scikit-learn, Spark-mlib, Triton, ONNX, and many others provides maximum flexibility and toolset options.
One of the significant advantages of MLOne is its automatic service scaling. When the load increases, the system autonomously scales, ensuring high performance and resilience.
This capability allows for the creation of a product that can efficiently address evolving user needs.
This capability allows for the creation of a product that can efficiently address evolving user needs.
MLOne also places a strong emphasis on data security. All services deployed through the platform come with secure inference endpoints, ensuring data confidentiality and privacy.
Furthermore, MLOne offers the convenience of automatically starting and stopping services on a schedule.
This intuitive and cost-effective solution for resource management optimizes expenses while maintaining high availability.
Furthermore, MLOne offers the convenience of automatically starting and stopping services on a schedule.
This intuitive and cost-effective solution for resource management optimizes expenses while maintaining high availability.
MLOne reshapes the way machine learning models are deployed and managed in production. Its user-friendly interface, integration with popular frameworks, and automated management functionalities make it a powerful tool for teams aiming to swiftly and effectively operationalize their models.