What is Mobile Machine Learning Delivery?
Machine Learning is an emergent, rapidly changing field, and building a model is hard enough. Now you have to figure out how to make it work on an edge device, manage it in production, and make sure your architecture is both scalable and performant? Fortunately, we have a team of experienced, dedicated data scientists and software engineers who understand the unique challenges and opportunities of running ML on the edge, and how to make it work in your app. Learn more below or reach out to us today.
Have an app integration live in just minutes.
Models are updated, in the background, without the need for any app bundle updates.
Deliver Core ML or, for that matter, any framework of your liking (Turi Create, TensorFlow, TF-Lite, MXNet, PyTorch, for starters) to your apps.
Remove the hassle of tracking which environment you are updating your models to. Single click deployment and tracking from the dashboard.
Use the Python SDK to post trained models to Skafos without disrupting your workflow or your CI/CD pipeline.
Sleep well at night knowing that your model delivery has built-in validation. Our Framework does the heavy lifting for you to prevent an update from crashing your app.