The easiest way to deploy ML models to production

I've always had a hard time deploying ML models into production. The traditional approach is to use Flask, Gunicorn with Nginx. This requires a lot of setup time, and it's slow!

https://www.panini.ai/ is a platform to serve ML/DL models at low latency and makes ML model deployment to production from few days to a few minutes. Once, deployed in the cloud it will provide you with an API key to infer the model. Panini is developed in C++, which provides very low latency during model inference and the model is stored in Kubernetes so, it is scalable to multiple nodes. It also takes care of caching and batching inputs during model inference.

I have also created a YouTube tutorial on how to use panini: https://www.youtube.com/watch?v=tCz-fi_NheE&t=

Please let me know what you guys think.

https://www.panini.ai/