Create a workspace
Start with a project so your prompts, runs, and artifacts stay organized in one place.
Public documentation
Learn how to use CloudDesignAI without digging through developer internals
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.
Generate architecture
Describe your system, budget, scale, and goals to generate a structured architecture recommendation.
Review cost and tradeoffs
Compare cheaper, balanced, and more scalable directions before committing to an approach.
Export implementation artifacts
Use Terraform, CLI commands, and diagrams as a starting point for review and implementation.
Getting Started
Use CloudDesignAI in four simple steps
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.
01
Sign in and create a project
Use the dashboard to create a project workspace for the system you want to design.
02
Describe what you are building
Add your system idea, cloud preference, region, budget, and expected scale.
03
Generate a design run
CloudDesignAI creates a recommendation and attaches the outputs to the project history.
04
Inspect, compare, and refine
Review architecture, sequence, cost, Terraform, CLI, and risks before acting on the result.
Outputs
Understand what CloudDesignAI generates
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.
Overview
A readable summary of the recommended path, explanation, assumptions, and main reasoning.
Architecture
A system-level diagram and service-role view to understand the proposed topology.
Sequence Diagram
A request-flow view that shows how traffic moves through the system at runtime.
Cost
Directional cost ranges, biggest cost drivers, and alternative architecture paths.
Terraform
Starter infrastructure-as-code output to help accelerate review and implementation planning.
CLI
Command-oriented setup and deployment guidance for users who prefer an operational workflow.
Risks
Review assumptions, operational concerns, and caveats before treating a design as ready.
Best Practices
Use the outputs responsibly
CloudDesignAI is most useful when it helps you reason faster, compare options, and prepare implementation work. It should support engineering review, not bypass it.
Treat generated outputs as a starting point for engineering review, not as an auto-deploy decision.
Double-check IAM, secrets handling, networking, backups, observability, and cost assumptions before implementation.
Use the project history to compare multiple runs instead of trying to force every scenario into one prompt.
Prefer clearer, constraint-rich prompts over vague requests when you want better architecture recommendations.
Review both the architecture view and the sequence diagram so you understand topology and runtime flow together.
Important reminder
Generated Terraform, CLI commands, and diagrams are intended to accelerate design and review. They still need human validation before production use.
Prompting tip
Include traffic assumptions, budget range, critical integrations, and operational priorities if you want more actionable recommendations.
FAQ
Questions people usually ask first
These are the most common framing questions for new users who are deciding how to use CloudDesignAI in practice.
Who is CloudDesignAI for?
It is built for solo developers, students, consultants, startup teams, and cloud practitioners who want faster architecture drafts with clearer tradeoffs.
Does CloudDesignAI deploy infrastructure for me?
No. It helps you design, compare, and prepare implementation artifacts, but you should still review everything before deployment.
Are the cost estimates exact?
No. They are directional planning estimates based on assumptions, intended to support early design decisions rather than final billing forecasts.
Can I reuse generated outputs?
Yes. The product is designed around reusable artifacts such as diagrams, Terraform, and CLI outputs that you can review and export.
Which cloud providers can I target?
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.