Bridge Data Science and DevOps
Deliver Prediction Services Anywhere
Getting completed machine learning models into production is challenging. Data scientists are not experts in building production services and DevOps best practices. Trained AI/ML models produced by a data science team are hard to test and hard to deploy. This often leads to a time consuming and error-prone workflow, where a pickled model or weights file is handed over to a software engineering team.
Our Ai-API Engine is a framework within Zeblok's Ai-MicroCloud® for serving, managing and deploying completed Ai/ML models. It bridges the gap between data science and DevOps, and enables teams to deliver prediction services in a fast, repeatable and scalable way.
Quick view of the APIs that are successfully deployed
Select the completed Ai/ML model to deploy as an API
Option to select a namespace
Select from the list of your data centers or Edge locations where model is to be deployed.
Click Create button to create the API – the Ai-API Engine does the rest, deploying Ai inference to all locations.
that’s it. it’s this much easy to use out Ai-AppStore to create your APIs. mb-lg-10 mb-md-10
©️ Zeblok Computational Inc. 2022