Best AI Infrastructure Platforms for Apache Airflow
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Compare the Top AI Infrastructure Platforms that integrate with Apache Airflow as of June 2025
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This a list of AI Infrastructure platforms that integrate with Apache Airflow. Use the filters on the left to add additional filters for products that have integrations with Apache Airflow. View the products that work with Apache Airflow in the table below.
What are AI Infrastructure Platforms for Apache Airflow?
An AI infrastructure platform is a system that provides infrastructure, compute, tools, and components for the development, training, testing, deployment, and maintenance of artificial intelligence models and applications. It usually features automated model building pipelines, support for large data sets, integration with popular software development environments, tools for distributed training stacks, and the ability to access cloud APIs. By leveraging such an infrastructure platform, developers can easily create end-to-end solutions where data can be collected efficiently and models can be quickly trained in parallel on distributed hardware. The use of such platforms enables a fast development cycle that helps companies get their products to market quickly. Compare and read user reviews of the best AI Infrastructure platforms for Apache Airflow currently available using the table below. This list is updated regularly.
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BentoML
BentoML
Serve your ML model in any cloud in minutes. Unified model packaging format enabling both online and offline serving on any platform. 100x the throughput of your regular flask-based model server, thanks to our advanced micro-batching mechanism. Deliver high-quality prediction services that speak the DevOps language and integrate perfectly with common infrastructure tools. Unified format for deployment. High-performance model serving. DevOps best practices baked in. The service uses the BERT model trained with the TensorFlow framework to predict movie reviews' sentiment. DevOps-free BentoML workflow, from prediction service registry, deployment automation, to endpoint monitoring, all configured automatically for your team. A solid foundation for running serious ML workloads in production. Keep all your team's models, deployments, and changes highly visible and control access via SSO, RBAC, client authentication, and auditing logs.Starting Price: Free -
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Cake AI
Cake AI
Cake AI is a comprehensive AI infrastructure platform that enables teams to build and deploy AI applications using hundreds of pre-integrated open source components, offering complete visibility and control. It provides a curated, end-to-end selection of fully managed, best-in-class commercial and open source AI tools, with pre-built integrations across the full breadth of components needed to move an AI application into production. Cake supports dynamic autoscaling, comprehensive security measures including role-based access control and encryption, advanced monitoring, and infrastructure flexibility across various environments, including Kubernetes clusters and cloud services such as AWS. Its data layer equips teams with tools for data ingestion, transformation, and analytics, leveraging tools like Airflow, DBT, Prefect, Metabase, and Superset. For AI operations, Cake integrates with model catalogs like Hugging Face and supports modular workflows using LangChain, LlamaIndex, and more.
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