# AI System Architecture Tool

> Design, understand, and communicate software architecture with your project context, AI, and an editable visual workspace. Connect your codebase and relevant sources, map services and dependencies on the canvas, work with AI and coding agents, and turn architecture decisions into working software.

## Architecture is more than a diagram

A system architecture diagram is only useful when it reflects the system behind it. Isolated drawings drift. Screenshots rot. The useful map stays connected to code, requirements, dependencies, infrastructure, and the decisions that shaped them.

Drawsy AI brings those layers together on one visual workspace. Learn how [context engineering](/context-engineering) designs what information AI should receive — this page is about using that approach for software architecture.

```text
Diagram
+
Code
+
Requirements
+
Dependencies
+
Infrastructure
+
Decisions
        ↓
Useful architecture context
```

## Understand the system you already have

Connect a GitHub repository and related project sources, then map services, dependencies, and flows on the canvas. AI can help explain relationships in the context you authorize — not invent a system you do not have.

![System architecture mapped on a Drawsy AI canvas with services and dependencies](https://app.drawsyai.com/assets/use-cases/system-architecture.jpg)

```text
GitHub
   ↓
Project context
   ↓
Drawsy canvas
   ↓
Architecture map
   ↓
AI explains relationships
```

- Repository and service boundaries on one board
- Documentation and decisions linked beside the diagram
- Questions scoped to the architecture you selected

## Design systems before you build them

Sketch components, services, data flows, and dependencies while requirements are still changing. AI can help explore alternatives and structure incomplete designs — it does not make architectural decisions automatically.

```text
Requirements
      ↓
Components
      ↓
Services
      ↓
Data flows
      ↓
Dependencies
      ↓
Architecture
```

## AWS infrastructure → visual architecture

Yes — you can use Drawsy AI to understand and design AWS infrastructure as part of the same architecture workspace, not as a detached cloud-console export.

Connect AWS resource context, bring infrastructure relationships onto the canvas, and turn them into an editable architecture map you can reason about and redesign beside application design.

![AWS infrastructure and system architecture visualized on a Drawsy AI canvas](https://app.drawsyai.com/assets/use-systems.png)

```text
AWS resources
      ↓
Infrastructure context
      ↓
Drawsy canvas
      ↓
Editable architecture
      ↓
Reason / redesign
```

- Infrastructure context from AWS sits on the same board as application architecture
- Editable visual map — services, networks, and data stores you can rearrange
- Reason about the running estate and design changes without leaving the workspace
- Not a replacement for the AWS console — a visual layer for understanding and redesign

## Give coding agents the architecture behind the task

Architecture without implementation context is incomplete. Implementation without architecture context is risky. Drawsy AI provides a visual project layer so supported coding workflows — including Codex CLI and OpenCode CLI via Companion — can work from selected workspace context rather than an isolated prompt.

Learn what [AI coding agents](/ai-coding-agents) are, then use this page for the architecture → agent → build loop.

```text
Architecture
      +
Project context
      +
Selected code
      ↓
    Agent
      ↓
Implementation
```

## Don't stop at the diagram

Architecture is the bridge between understanding a system and building it. On Drawsy AI, the loop can continue past the diagram: agents work with project context, produce or change code, and live previews can bring running software back onto the canvas so you can refine the design against something real.

For the full workflow story, see [From Architecture Diagram to Running Software](/blog/from-architecture-diagram-to-running-software).

```text
Architecture
     ↓
Agent
     ↓
Code
     ↓
Run
     ↓
Live Preview
     ↓
Refine
```

## Keep architecture close to the code

DRAW.md is how Drawsy AI keeps architecture next to the repository — a canonical project document that can render into editable canvas content, then stay available to coding agents working from the same workspace.

The point is not another markdown format to maintain for its own sake. It is a bridge so architecture does not live as a detached diagram outside the project.

For the full rationale, see [Why We Built DRAW.md](/blog/why-we-built-draw-md).

```text
Repository
    ↕
 DRAW.md
    ↕
Drawsy canvas
    ↕
Coding agent
```

- Architecture stays close to the code that implements it
- Canvas content can stay aligned with a readable project document
- Agents can work from the same visual + project layer — not a screenshot in a slide deck
- Complements Git and docs; does not replace them as source of truth

## What you can design

Common architecture jobs on Drawsy AI:

- System architecture — services, dependencies, and data flows
- API architecture — endpoints, services, and integrations
- Database architecture — schemas, relationships, and migrations
- Cloud infrastructure — AWS resources and infrastructure relationships
- Distributed systems — queues, services, workers, and event flows
- Application architecture — frontend, backend, and external services

## What Drawsy AI isn't

Drawsy AI isn't your cloud console, Git provider, IDE, or project tracker. It gives you a visual workspace where context from those systems can be brought together to understand and design the system — then continue into agents, code, and previews when you need them.

## Related

For the end-to-end workflow, see [From Architecture Diagram to Running Software](/blog/from-architecture-diagram-to-running-software).

For why DRAW.md exists, see [Why We Built DRAW.md](/blog/why-we-built-draw-md).

For the broader developer workflow, see [AI workspace for developers](/use-cases/developers).

For the category, see [AI workspace](/ai-workspace) and [AI canvas](/ai-canvas).

For sources and grounding, see [connected context](/connected-context) and [context engineering](/context-engineering).

For the agent layer, see [AI coding agents](/ai-coding-agents) and [Drawsy Companion](/companion).

Start free: https://drawsyai.com

## FAQ

### What is an AI system architecture tool?

An AI system architecture tool helps you design, understand, and communicate software architecture with visual maps plus project context — not only static diagrams. Drawsy AI is an AI workspace used for that work.

### Can Drawsy create system architecture diagrams?

Yes. You can map services, dependencies, and flows on an infinite canvas, with AI helping expand or question the design from the context you authorize.

### Can I visualize an existing codebase?

Yes. Connect GitHub and related sources, map the architecture on the canvas, and ask AI about relationships in the context you selected.

### Can Drawsy visualize AWS infrastructure?

Yes. Connect AWS resource context, bring infrastructure onto the canvas as editable architecture, and reason about or redesign it beside application design — without replacing the AWS console.

### What is DRAW.md?

DRAW.md keeps architecture close to the code: a project document in the repository that can render into editable Drawsy canvas content and stay available to coding agents working from that workspace.

### Can I connect GitHub to an architecture workspace?

Yes. GitHub is a core connector for architecture workflows so repository context can sit beside the diagram.

### Can AI help design a software architecture?

AI can help explore options, structure incomplete designs, and question gaps. It does not automatically make architectural decisions — humans still own trade-offs.

### Can I use coding agents with my architecture?

Yes. Architecture and project context on the canvas can inform coding-agent workflows, including Codex CLI and OpenCode CLI via Drawsy Companion.

### Can I turn architecture into working software?

Drawsy AI supports continuing past the diagram — agents, code, and live previews — so architecture work can feed implementation and refinement on the same workspace.

### Does Drawsy replace my architecture or diagramming tools?

No. Drawsy AI is a visual workspace around your existing stack — cloud console, Git, IDE, and docs — not a replacement for them.

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HTML: https://app.drawsyai.com/use-cases/system-architecture
llms.txt: https://app.drawsyai.com/llms.txt