KeaML allows data scientists to create machine learning environments with no effort. You just have to select an image, the hardware specs that best suit your needs from our large catalog and click 'Create'. That's all.

Experience a seamless AI development journey with KeaML, as we empower you through all stages — develop, train, and deploy.

Hey PH community 👋! I'm Gabriel, founder of KeaML. Today is super exciting for us! A year ago, we launched KeaML, stepping into the realm of Cloud Development Environments for machine learning. And guess what? We’re back, and this time we bring you Kea Deployments! Diving into AI and spending 8 years in it, I’ve experienced firsthand the gritty challenges of pushing models into production. It's a tough nut to crack, isn’t it? That’s where Kea Deployments swings into action. Our goal? To streamline the deployment process, allowing us, the data scientists and ML engineers, to pour our energy into sculpting extraordinary models without being tied down by the intricate layers of infrastructure. Drawing inspiration from the sleek simplicity that platforms like Vercel shower on the frontend world, Kea is here to redefine the deployment experience in the ML landscape. We are geared up, supporting Scikit Learn models, and guess what’s on the horizon? Transformers, Pytorch, and TensorFlow are gearing up to join the Kea family! 🚀 Jump in and kickstart your journey with our free tier! And here’s a cherry on top — use the code PH1MO to unlock a free month on our paid tiers! Your feedback is the north star guiding KeaML’s evolution and what we are actually want to get from this launch. I’m all ears for your insights, suggestions, and thoughts. So, hop in, explore Kea Deployments, and let’s carve the future of ML deployments together! Cheers, Gabriel

@gobaldia Interesting Idea! Congrats on the launch

Hey @keshini_dabare2! Thanks for your words!

This will save me a TON of time deploying my models 🤓

Hey @manu_reynaert1! Glad to hear that! Go ahead and create a free account to try KeaML out 🤓

What if the model requires a lot of code to write?

Hi @kingromstar! That’s a great question. We understand that at this stage, we don’t cover all possible use cases, but we’re working towards supporting several of them. The inclusion of pipelines for pre/post-processing is in our backlog. Could you please share the specific use cases you have in mind?

I have been a user of the closed beta for a while. I think KeaML has a really clear and easy to use user interface, with almost no learning curve. It's not completely mature but it looks really promising.

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