Metis Machine's Skafos

Machine Learning Delivered. A Machine Learning automation platform for those that want to focus on their work.

Welcome to the Metis Machine documentation hub. You'll find comprehensive guides and documentation to help you start working with Metis Machine's Skafos platform as quickly as possible, as well as support if you get stuck. Fire it up!

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Machine Learning Delivered.

At Metis Machine, we are passionate about building tools that help data scientist and software engineers together use machine learning and deep learning to create the next generation of apps and experiences. We don't really know what those will be, per se, but we do know that if we remove the tedious and time consuming tasks of building reliable and managed machine learning pipelines it will make everyone's lives much better.

Our platform is built on what we refer to as Skafos Core.

Skafos Core orchestrates your code, data, and any dependencies into a containerized job that is securely deployed. Run a single monolithic project, or a series of jobs as micro services. Connect your existing data sources through our SDK. Power up your jobs with any frameworks you need and your own data streams. Monitor the performance of your models in development, and the health of your models in production.

However, we have been spending a lot of our time recently building a tool for mobile engineers which we refer to as either Skafos or Skafos For Creators. It is based on the fact that we are mobile engineers at heart and that we understand that, as mobile engineers, we just want to build apps. So we used our core platform to build Skafos.

Skafos is the tool for iOS developers to deploy machine learning to their app. Get started with a pre-trained model, drop in the SDK and then updates are pushed to your app in the background.

If you are an iOS Developer please go to "Quickstart for iOS Developers", Getting Started

If you are a Data Scientist please go to "Quickstart for Data Scientist", Getting Started

Also, you can always talk to us any time either at our Slack channel or Reddit. Please subscribe to both.