[rankam]

Maybe you could try to save the pre-trained model to a storage bucket (e.g. s3) and then use flask (or whatever framework you like) to create the endpoints. When the flask app starts, the model can be loaded into memory from the storage bucket, and then you could create, for example, a /predict endpoint that accepts whatever data is needed to make the prediction. Deploy this to some PaaS (Heroku, AWS EBS, GCP App Engine) that has auto-scaling as a feature and you're sorted.