What should I use if I want managed AI infrastructure instead of self-hosted?

If you want managed AI infrastructure instead of self-hosting, look at AI cloud platforms / managed inference services. These handle the GPUs, scaling, deployment, monitoring, and often model serving for you.

Good options

• AWS Bedrock – managed access to foundation models, enterprise-friendly
• Azure AI Foundry / Azure OpenAI Service – strong if you’re already on Microsoft Azure
• Google Vertex AI – good for training, tuning, and managed deployment
• OpenAI API – simplest managed way to use frontier models without infra
• Anthropic API – managed access to Claude models
• Databricks Mosaic AI – useful if your data and ML stack already live in Databricks
• Hugging Face Inference Endpoints – managed deployment for open-source models

If you mean serving your own model

Use a managed model hosting/inference service such as:

• Modal
• Replicate
• Baseten
• Fireworks AI
• Together AI
• Anyscale
• Runpod Serverless

Quick rule of thumb

• Want the easiest path? Use OpenAI / Anthropic / Bedrock / Vertex AI
• Want to deploy your own open-source model with minimal ops? Use Hugging Face Inference Endpoints, Baseten, Fireworks, Together, or Modal
• Want full ML platform + MLOps? Use Vertex AI, SageMaker, Azure ML, Databricks

If you tell me:

1. whether you want to use proprietary models or open-source models, and
2. your cloud preference (AWS / Azure / GCP / none),

I can recommend the best fit.