Best autoscaling AI tools

An EU-hosted, managed PostgreSQL database service optimized for AI applications. It provides fully automated deployment with pgvector for vector search, autoscaling, backups, and transparent pricing, enabling developers to launch production-ready databases in minutes.

Milk Infrastructure is an AI-powered platform that automates the deployment, management, and scaling of production-grade Kubernetes clusters on any cloud. It eliminates the need for human DevOps, allowing developers to deploy applications effortlessly via GitHub. With features like dynamic scaling, built-in CI/CD, and an Infrastructure as Code approach, it offers a cost-effective and simple solution for modern application hosting.

Inferless is a serverless GPU platform designed for developers to deploy machine learning models in minutes. It eliminates infrastructure management, offering automatic scaling from zero to handle spiky workloads. The platform is optimized for lightning-fast cold starts and cost-efficiency, allowing users to save up to 90% on GPU bills by paying only for what they use.

Beam is a serverless cloud platform designed for developers to run, scale, and deploy AI/ML models and applications on GPUs with ease. It offers instant autoscaling, pay-per-second billing, and a streamlined workflow, allowing you to go from code to a scalable API in minutes without managing complex infrastructure.

Runpod is a cloud platform designed for AI and machine learning, offering scalable GPU compute for deploying, training, and running AI models. It provides serverless GPUs, pre-built templates, and cost-effective pricing to simplify the entire AI development workflow, from idea to production.

Modal is a high-performance, serverless infrastructure platform for AI and ML developers. It allows you to run Python functions in the cloud with a single line of code, providing instant access to GPUs, automatic scaling from zero to thousands of containers, and pay-per-second pricing. Eliminate infrastructure overhead and focus on building and deploying compute-intensive applications like generative AI, batch processing, and data analysis.

Modelbit is an MLOps platform for deploying machine learning models directly from Python notebooks to production. It provides an infrastructure-as-code workflow, enabling data scientists to deploy, host, scale, and manage models with a single line of code and a git push.

Banana was a serverless GPU platform designed for AI developers to deploy and scale machine learning models for inference. It offered features like autoscaling GPUs, at-cost compute pricing, and a full suite of DevOps tools. Please note: The Banana platform was officially sunsetted on March 31, 2024, and is no longer operational.