Introducing dploy.ai 🎉

Hi 👋! I’m very happy to officially announce our work on the dploy.ai platform 🥂. While it’s not live just yet, our team has been working hard behind the scenes since beginning of 2020 and is currently gearing up for its first initial (limited) public release.

What’s in a name?

Well actually, in this case most of it is. We’re trying to highly simplify AI deployment, hence dploy.ai 😇. We consider AI to mean anything that can serve as a (pseudo-)automated decision support algorithm. This can range from simple heuristics, statistical models, “traditional” machine learning and deep learning models to optimization models.

Our objective is to help you to make it ridiculously simple for others to use the output of your AI models. Be it your team, an application in your production system or a client you want to give access to your models. We believe that from the moment you’re satisfied with your model performance you should be just a few commands away from being able to share its results.

The challenge today is that from the moment you deploy your AI model your journey has only just begun. With dploy.ai we want you to be able to simply focus on model building, we’ll make sure that we take care of important afterthoughts like security, auditing, performance monitoring, integration, scalability, SLAs and monetization.

Enough talk, where is it?

I realise that the above is still quite high level and the proof of the pudding is of course in the eating. Therefore our next release (2020.2.0 for the versioning fans), a public one this time, will give you access to some cool and freely available AI models-as-a-service. Yes, usage will be free as in beer 🍻.

I’ll make sure to keep you posted on our progress and will share regular status updates and tidbits here!

Live long and prosper! 🖖

FYI. make sure to sign up to our mailinglist here: https://dploy.ai/