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Version: 4.5

Model Deployment

Model deployment is a pivotal phase in the journey of a machine learning model, marking the transition from theoretical development to practical application. At its core, model deployment involves making the carefully crafted and trained model available to end-users or other systems for inference, prediction, or decision-making. This process is essential for harnessing the power of artificial intelligence and machine learning in various industries, enabling businesses and organizations to automate tasks, gain valuable insights, and improve decision-making.

Discover Katonic AI's versatile model deployment options:

Katonic Registry Deployment :

If you've built your model within the Katonic Platform, you can easily deploy it through our Katonic Registry. Simply log your experimentation, select your model, and register it. This makes your model readily available in the Katonic Registry for seamless deployment. Choose from the array of models stored in the registry and deploy them effortlessly for your specific needs.

Custom Model Deployment :

With our Custom Model Deployment feature, you have the flexibility to deploy models directly using pre-existing model files. There's no need to recreate the model within our platform. This streamlined approach allows you to efficiently utilize your existing models without any additional development effort.