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Atlas by Comet Lab
Infrastructure layer

Hosting and infrastructure, compared

This is where the whole stack runs: the front end, the API, the database and sometimes the model. Light, fast platforms suit the interface and API; heavy inference and long-running jobs belong elsewhere. The other question is whether you already have a cloud you need to stay inside.

Open this layer in the explorer

At a glance

Every tool in this layer, with where it fits and the facts that usually decide it.

Tool Where it fits Licence Self-hostable Hosted API Maturity
Vercel Application hosting A fast, low-friction home for the web front-end and light API layer of an AI application. Proprietary No Yes Mature
Amazon Web Services Cloud platform The natural home for a production AI stack when an organisation already runs on AWS and needs that governance and scale. Proprietary No Yes Mature
Cloudflare Workers Edge compute A fit for low-latency, globally distributed application logic and light AI features at the edge. Proprietary No Yes Established
Coolify Self-hosted PaaS A fit when you want a convenient deploy platform but need the whole stack to run on your own infrastructure. Open source Yes Yes Growing
Fly.io Application hosting A fit when an AI app needs low latency across regions, or wants app hosting and GPU inference on one platform. Proprietary No Yes Established
Google Cloud Cloud platform A natural home for an AI stack when an organisation is on Google Cloud or leans on BigQuery and Gemini. Proprietary No Yes Mature
Microsoft Azure Cloud platform The default cloud for Microsoft-stack enterprises, especially those wanting OpenAI models inside Azure governance. Proprietary No Yes Mature
Railway Application hosting A fit for small teams that want to deploy an AI backend and its database quickly, without cloud complexity. Proprietary No Yes Established
Render Application hosting A fit when you want a predictable managed home for an AI app backend, workers, and database without cloud-console depth. Proprietary No Yes Established
Supabase Backend platform A strong fit for an AI app that needs a database, auth, and vector search together, with the option to self-host. Open source Yes Yes Established

How to choose

Start from your situation. Where a line says “our”, it comes from Comet Lab’s own builds.

  1. The front end and a light API

    Vercel is our usual home for the front end of an AI build; Cloudflare Workers runs light logic at the edge. Keep inference and long jobs off both.

  2. A backend and database for a small team

    Railway and Render deploy a backend quickly without cloud complexity; Supabase gives you Postgres, auth and vector search in one.

  3. Low latency across regions, or GPUs on the same platform

    Containers close to users, with GPU deployment alongside the app.

  4. Your organisation already runs on a hyperscaler

    Stay inside the governance you have. More complexity than a small project needs.

  5. Everything on your own servers

    Managed-platform convenience, with the data never leaving your servers. You still own those servers.