Create a workspace
Start with a project so your prompts, runs, and artifacts stay organized in one place.
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CloudDesignAI helps you turn a product idea into a structured cloud architecture workspace with provider-aware diagrams, cost guidance, Terraform, CLI output, and review notes across AWS, Azure, and Google Cloud. This docs page is for people using the product, not for exposing internal application details.
Start with a project so your prompts, runs, and artifacts stay organized in one place.
Describe your system, budget, scale, and goals to generate a structured architecture recommendation.
Compare cheaper, balanced, and more scalable directions before committing to an approach.
Use Terraform, CLI commands, and diagrams as a starting point for review and implementation.
The product is designed around a project workspace. Instead of pasting prompts into a chat thread, you create a project, run generation, and review outputs in a structured flow.
Use the dashboard to create a project workspace for the system you want to design.
Add your system idea, cloud preference, region, budget, and expected scale.
CloudDesignAI creates a recommendation and attaches the outputs to the project history.
Review architecture, sequence, cost, Terraform, CLI, and risks before acting on the result.
Each generation run produces a review surface that helps you inspect the recommendation from multiple angles. Use the tabs together rather than relying on only one output.
A readable summary of the recommended path, explanation, assumptions, and main reasoning.
A system-level diagram and service-role view to understand the proposed topology.
A request-flow view that shows how traffic moves through the system at runtime.
Directional cost ranges, biggest cost drivers, and alternative architecture paths.
Starter infrastructure-as-code output to help accelerate review and implementation planning.
Command-oriented setup and deployment guidance for users who prefer an operational workflow.
Review assumptions, operational concerns, and caveats before treating a design as ready.
CloudDesignAI is most useful when it helps you reason faster, compare options, and prepare implementation work. It should support engineering review, not bypass it.
Generated Terraform, CLI commands, and diagrams are intended to accelerate design and review. They still need human validation before production use.
Include traffic assumptions, budget range, critical integrations, and operational priorities if you want more actionable recommendations.
These are the most common framing questions for new users who are deciding how to use CloudDesignAI in practice.
It is built for solo developers, students, consultants, startup teams, and cloud practitioners who want faster architecture drafts with clearer tradeoffs.
No. It helps you design, compare, and prepare implementation artifacts, but you should still review everything before deployment.
No. They are directional planning estimates based on assumptions, intended to support early design decisions rather than final billing forecasts.
Yes. The product is designed around reusable artifacts such as diagrams, Terraform, and CLI outputs that you can review and export.
You can generate architectures for AWS, Azure, and Google Cloud. The workflow and tabs stay consistent, but the recommended services and artifacts adapt to the selected provider.