CloudCrew AI

Describe it. Ship it. Own it.

CloudCrew AI turns a plain-English request into production AWS Terraform or Pulumi, with security scanning, architecture diagrams and decision records, delivered as a GitHub pull request. You approve it at two checkpoints before anything deploys.

Request a demo See a real run
You type six words. That's the whole request. No template, no YAML, no architecture diagram to draw first.
The CloudCrew app with the brief "Build Production three tier web application", compliance frameworks, network ranges and IaC engine options, next to the live pipeline panel showing the crew at work.
Terraform or PulumiHCL or Pulumi Python, your choice per run.
Two human checkpointsYou approve the plan, then the code. Nothing skips you.
Your account, your pipelineDeploys run in your own GitHub Actions. We never hold your AWS credentials.

How it works

A crew of specialised agents does the work. You make the decisions.

  1. 01

    Describe it

    Say what you need in plain English. A sentence is enough; Enhance reviews it against AWS Well-Architected and rewrites it into a full production brief.

  2. 02

    Approve the plan · checkpoint 1

    Review the proposed architecture and remove anything you don't want before a line of code is written.

  3. 03

    Review the code · checkpoint 2

    Generated infrastructure code, security findings, diagrams and decision records, all in one place.

  4. 04

    Merge and deploy

    It lands as a pull request in your repository and deploys through your own CI when you're ready.

What came back

Real CloudCrew output for this request. Every image is a screenshot, cropped but not edited.

01

CloudCrew reviews the request before designing anything

The Enhance review checks the brief against the AWS Well-Architected pillars and flags what a production system needs but the request left out. Here: no multi-AZ and no cost-allocation tags. It then rewrites the six words into a full production brief. You accept the rewrite or ignore it.

Enhance review findings: no multi-AZ or high availability specified, and no cost allocation tags.
02

You approve the blueprint · checkpoint 1

Every component, its key settings, and whether it can be removed. Nothing is generated until you approve.

Architecture blueprint at checkpoint 1: each component with its type, key configuration, and whether it is locked, flagged or free to remove.
Locked components cannot be removed. Warn can be removed, with a warning. Free can be removed.
03

The architecture

The Full Resource Map is drawn from the generated code and shows exactly what will deploy. In the app it is interactive: click any resource to trace its traffic. The illustrative view is AI-generated for a quick read, and labelled that way in the pull request.

Full resource map of the generated stack.
Full Resource Map. What actually deploys.
Illustrative AWS-style architecture diagram from the pull request, labelled as AI-generated.
Illustrative view. As it appears in the pull request.
04

Grounded, not guessed

Before writing code, CloudCrew checks its knowledge graph of AWS services and how they fit together. In this run, 69 of the 81 resource types had authored rules available at generation time.

Knowledge graph view: resource types grouped by capability, with a coverage map.
Knowledge graph coverage, grouped by capability.
05

The pull request · checkpoint 2

Modular Terraform, each layer with its own state, plus a decision record for every major choice, delivered to GitHub for review.

Pull request contents: Terraform files by layer and five Architecture Decision Records.
Generated files and decision records, from the pull request.

Request a demo

See CloudCrew on your own use case.

  • A live run on your use case. Bring a real infrastructure request and watch it become a pull request.
  • 30 minutes, no slides. Questions about the output are the point.
  • We reply by email to find a time that works.

Prefer email? info@cloudcrewai.com

We'll only use this to contact you about CloudCrew.

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