Different tools

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Tutorial

Quick start - deploy your first sample model using our Platform

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Swagger UI

Access easy-to-use APIs.

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Github

Test our sample models

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Some Literature

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AI model deployment, a problem or a challenge?

About 50 conversations with Machine Learning Engineers, Researchers, Team Leaders and Founders, working in different industries, tackling different problems share with me their position about obstacles during moving AI models into production.

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We're about to disrupt the way you deliver AI algorithms into production environment

Our goal is to help you monetize your AI skills by managing your workflow after you trained your model and you want to  put it into production.

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To develop and manage a production-ready model, you must work through the several stages like data preparation, model development, training and deployment. Unfortunately, deploying Machine Learning (ML) models at scale is one of the biggest challenges for companies willing to create value through AI.

Our approach powers the process of AI model deployment by the simplified resource management, models versioning and easy-to-use API.

You don't need to have special skills or prior experience in order to bring a value to business with your algorithms. Our tool will help you manage and monetize this workflow.