in seconds.
Spend more time perfecting AI with your application and less time on infrastructure.
Build and push
Build the inference server and push it to an docker registry, or use our pre-built templates directly.
Create deployment
Write your prediction code and deploy it to the cloud. You could use one of our templates to get started or build and deploy a new deployment from scratch.
Make predictions
The easiest way to make predictions is to use the Modelz SDK. You could also use the curl command to make predictions.
Modelz provides the following features out-of-the-box
Auto scaling
Serverless architecture enables us to easily scale seemlessly from zero, up or down, according to your needs. This allows us to provide a reliable and scalable solution for deploying and prototyping machine learning applications at any scale.
Rich ecosystem
Modelz is designed for machine learning workloads, providing support for popular ML serving frameworks like mosec and user-friendly UI tools like Gradio and Streamlit, which facilitate easy model deployment and prototyping with interactive UIs.
DevOps (Coming soon)
At Modelz, we are dedicated to being a developer-first platform. In line with this, we are currently working on supporting OpenAPI for model operations, to enable developers to seamlessly integrate their models into existing workflows and systems.
Our domain experience
The Modelz founding team has years of experience building ML infrastructure at AWS, TikTok, Shopee, Tencent, and the open-source community.