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Welcome

Welcome on Craft AI's MLOps Platform. This Platform is designed to create, deploy and run ML & LLM models.

This documentation is divided in 2 main parts :

  • Tutoriels that present the key features of the platform
  • General documentation that explains every available feature

Platform

This Platform has been designed for ML Engineer.

To use it, the basic workflow is:

  • Choose a configured environment on the cloud provider of your choice
  • Create Machine Learning pipelines with your Python code
  • Deploy and execute the pipelines on environments running on Kubernetes
  • Monitor the performance of the models in production and the health of the infrastructure

The Platform aims to be an end-to-end tool that brings together all the functionalities required for the successful implementation and deployment of any AI project.

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What is MLOps ?

Machine Learning Operations (MLOps), aims to provide an end-to-end development process to design, build and manage reproducible, testable, and evolvable ML-powered software.

MLOps :

  • aims to unify the release/production cycle for ML and software application release.
  • enables automated testing of machine learning artifacts (e.g. data validation, ML model testing, and ML model integration testing).
  • enables the application of agile principles to machine learning projects.
  • enables supporting machine learning models and datasets to build these models as first-class citizens within CI/CD systems.
  • reduces technical debt across machine learning models.
  • must be a language-, framework-, platform-, and infrastructure-agnostic practice.