Automate and simplify the building, testing, deployment and monitoring of your AI pipelines and production data. Continuously train, test and deploy your LLMs and ML models based on changes in your data and business requirements.
Integrate MLRun, Iguazio’s open source framework for orchestrating your AI and ML pipelines, with CI engines to automatically run all AI/ML operations. After each PR and code change, MLRun and the CI engine prepare the data, train models, test, deploy to clusters, monitor the models and send back feedback for retraining and deployment. CI/CD for AI/ML simplifies, streamlines and accelerates the development and deployment process, ensures technological consistency and enables tracking and scalability.
Build and run complex workflows composed of local/library functions, external cloud services or other building blocks of your choice.
Track and version models, code, data, lineage parameters, artifacts and results with minimal effort.
Run AI/ML pipelines with MLRun and KubeFlow, GitHub Actions, GitLab, Jenkins, or other engines.
Elastically scale each step of the CI/CD pipeline. Specify the configurations, assign GPU, CPU and memory for each workflow step and MLRun will auto-scale.
Learn how to implement the data mesh approach to data architecture with the Iguazio AI Platform
