How Can You Streamline Your Cloud-Based ML/AI Projects?

Hi Data Pros, Are you maximizing the potential of your cloud-based ML/AI projects? We're excited to share that Outerbounds, along with the robust capabilities of open-source Metaflow, is now available on all major cloud platforms, including AWS, Azure, and GCP.

​Check it out here​

If you've been managing multiple cloud services and looking for a unified solution, Outerbounds offers a seamless integration within your existing cloud infrastructure. This means you can deploy and manage AI/ML projects directly within your cloud environment without the hassle of switching between different services.

For those already using cloud services for ML/AI, consider the edge Outerbounds provides: from development to deployment, the platform ensures that your operations are as smooth and efficient as possible. This is done by leveraging native cloud capabilities such as scalable storage and compute, while enhancing them with a dedicated layer for faster, more secure, and cost-effective ML development.

Moreover, Outerbounds integrates tightly with your existing security policies and infrastructure, ensuring that no data leaves your premises and all processing remains within your control.

Ready to take your ML/AI projects to the next level with a platform that's built for developers and respects your existing cloud setups? Learn more about how Outerbounds can streamline your operations and reduce costs, while providing the freedom to use the best of each cloud service effectively.

Visit the blog to dive deeper into the benefits of Metaflow and Outerbounds and start transforming your approach to ML/AI today: https://bit.ly/3xWfdff​

If these types of things interest you, also join the Metaflow community Slack to chat about them with nearly 4,500 data scientists and MLEs :)

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Looking forward to hearing your thoughts!
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Best,

Ravit Jain

Founder & Host of The Ravit Show