Datalayer Private Beta
We are super excited to announce that Datalayer is entering Private Beta! After months of development, we are inviting today those who signed up on our waiting list to experience our solution first-hand.
How to Join the Beta?
If you registered on our waiting list, keep an eye on your inbox, invitations are being sent out now! We're thrilled to have you onboard as part of this exclusive group, helping us shape the future of Datalayer.
But don't worry if you haven't signed up yet—there are still limited spots available. Simply register on the waiting list to secure your spot in the private beta.
Why Join the Beta?
This is your opportunity to get early access to the cutting-edge features of Datalayer, and we need your help to make it even better. Your experience and feedback will be invaluable in helping us fine-tune the product, optimize performance, and add features that truly meet your needs. It would be great to have you on board and we can't wait to hear your thoughts!
As a beta user, you'll enjoy:
- Free credits to try out Remote Kernels.
- Direct support from our team to ensure a smooth experience.
- Directly influence the future development of Datalayer through your feedback.
What Can Datalayer Bring You?
Datalayer simplifies access to powerful computing resources (GPU or CPU) for data scientists and AI engineers. Whether you're training models or running large-scale simulations, you can seamlessly scale your workflows without changing your code or setup.
Key Benefits
- Effortless Remote Kernel Access: Seamlessly connect to high-performance Remote Kernels from JupyterLab, VS Code, or via the CLI. Switch kernels with just a few clicks to run your code on powerful machines, without altering your workflow or setup.
- Flexible and Simple Setup: Avoid the complexity of configuration changes or workflow disruption. Launch Remote Kernels effortlessly and scale your data science or AI workflows with ease, whether you're working on notebooks or scripts.
- Optimized Resource Usage: Gain control over resource allocation by running specific notebook cells on Remote Kernels only when needed. This precision helps minimize resource consumption and maximize efficiency.
- Flexible Credits-Based Model: Enjoy a pay-as-you-go credits system that adapts to your needs. With transparent usage tracking and detailed reports, you'll only pay for the resources you use, making it a cost-effective solution for scaling your projects.
Learn more about Datalayer's features on our user documentation and online SaaS.
