Explain any AI architecture in 30 seconds
Type your agent architecture in plain text. Get an animated diagram you can drop into any presentation, doc, or architecture review. Works with LangGraph, CrewAI, OpenAI Agents SDK, or any custom system.
to first diagram
starter templates
video export
How it works
Text in, animated architecture out
Describe your agent architecture
Define agents, tools, and data flow
using simple arrow syntax
User -> Agent -> Tool -> API
Watch the data flow
See animated messages flowing between
agents, tools, and APIs in real time
User ~~→ Agent ~~→ Tool
Export and share
Export as PNG for docs or
WebM video for presentations
→ agent-arch.webm (1.4 MB)
AI architecture diagram features
From simple agents to complex multi-agent orchestration
Multi-Agent Systems
Visualize coordinator, supervisor, and swarm patterns. See how agents delegate, collaborate, and pass data between each other.
RAG Pipelines
Diagram retrieval-augmented generation flows. Show embedding, vector search, context assembly, and generation stages animated.
Tool Call Workflows
Visualize LLM function calling and tool use patterns. See the agent reason, select a tool, call an API, and process the response.
Fan-Out Orchestration
Show parallel agent execution, task distribution, and result aggregation. Perfect for orchestrator-worker and router patterns.
AI architecture diagram examples
Common patterns — type these and watch the animated data flow
Single Agent with Tool Calls
User sends a query, the LLM agent reasons, calls an external API, and returns a response. The most basic agentic pattern.
User -> LLM Agent -> API Tool -> LLM Agent
LLM Agent -> User
Multi-Agent Coordinator
A coordinator agent distributes tasks to specialized sub-agents in parallel. Classic orchestrator-worker pattern used in CrewAI and LangGraph.
User -> Coordinator
Coordinator -> {Researcher, Writer, Reviewer}
RAG Pipeline
User query gets embedded, searched against a vector database, context is assembled, and the LLM generates a grounded response.
User -> Embedder -> Vector DB -> Context
Context -> LLM -> User
MCP Tool Server
An LLM agent uses the Model Context Protocol to connect to external tool servers. Emerging standard for agent interoperability.
LLM Agent -> MCP Client -> MCP Server
MCP Server -> {Database, API, FileSystem}
Reflection Loop
Agent generates output, a critic evaluates it, and the agent refines. Iterative self-improvement pattern used in production systems.
User -> Generator Agent -> Critic Agent
Critic Agent -> Generator Agent -> User
Agentic RAG
An autonomous agent decides when to retrieve, which sources to query, and iteratively refines until the answer quality is sufficient.
User -> Agent -> {Vector DB, Web Search, Knowledge Graph}
Agent -> Evaluator -> Agent -> User
Framework-agnostic
Diagram any AI agent architecture, regardless of framework
Why animated agent diagrams
Static diagrams show what the system looks like. Animation shows how it works.
Architecture reviews
Walk through agent reasoning flows step by step. Spot where tool calls bottleneck, where context is lost, where loops occur.
Conference talks
Export animated diagrams as WebM video for slides. Show audiences how multi-agent systems coordinate in real time.
System design
Prototype agent architectures before coding. Try different orchestration patterns and see how data flows through each one.
Stakeholder communication
Non-technical stakeholders understand animated flows instantly. Show them how the AI agent actually processes their request.
AI architecture diagram tools compared
Why AI engineers switch from Mermaid and Excalidraw
| Feature | Chartado | Mermaid | Excalidraw | Eraser.io | Lucidchart |
|---|---|---|---|---|---|
| Animated data flow | Yes | No | No | No | No |
| Text/code input | Yes | Yes | No | AI | No |
| Video export | WebM | No | No | No | No |
| Multi-agent fan-out | Native | Manual | Manual | Manual | Manual |
| Request-response animation | Yes | No | No | No | No |
| Version control friendly | Yes | Yes | JSON | No | No |
Built for the AI architecture era
Static diagrams show structure. Animated diagrams show behavior.
30 seconds to first diagram
No signup, no install, no drag-and-drop. Type your architecture in plain text and see the animated result immediately. Works in any browser.
Export as video for presentations
Record your animated architecture as WebM video. Drop it into slide decks, Notion docs, or Slack threads. No other diagram tool exports animation.
Version control friendly
Your diagram is a single line of text. Diff it, commit it, review it in PRs. When the architecture changes, update one line — not fifty drag-and-drop boxes.
Frequently asked questions
About AI architecture diagrams
What is an AI architecture diagram?
An AI architecture diagram visually represents how an AI system's components interconnect -- showing the flow from user input through LLM reasoning, tool calling, memory access, and response generation. An animated AI architecture diagram goes further by showing the sequential data flow that static diagrams cannot convey.
How do I create a RAG architecture diagram?
With Chartado, type your RAG pipeline components using arrow syntax: "User -> Embedding -> Vector DB -> Context -> LLM -> User". Chartado generates an animated diagram showing how data flows through the retrieval, context assembly, and generation stages. Works with any vector database (Pinecone, ChromaDB, Qdrant) and any LLM.
What is the best tool for AI architecture diagrams?
Chartado is the only diagramming tool with animated data flow for AI architectures. Unlike Mermaid (static flowcharts), Excalidraw (manual drag-and-drop), or Eraser.io (AI-generated static diagrams), Chartado animates messages flowing between agents, tools, and APIs in real time. It also exports as WebM video for presentations -- no other tool does this.
Can I use Chartado with LangGraph, CrewAI, or OpenAI Agents SDK?
Yes. Chartado is completely framework-agnostic. You can diagram architectures for LangGraph state graphs, CrewAI crews, AutoGen multi-agent systems, OpenAI Agents SDK handoff chains, Google ADK agents, or any custom system. The text-based input describes your architecture, not your framework.
Can I export AI architecture diagrams as video?
Yes. Chartado can record your animated architecture diagram as a WebM video file. This is ideal for conference talks, slide decks, Loom recordings, and social media posts. No other AI architecture diagram tool offers animated video export.
What is the difference between MCP and A2A protocols?
MCP (Model Context Protocol) standardizes how agents connect to tools and data sources. A2A (Agent-to-Agent) standardizes how agents communicate with each other. Chartado can diagram both: use arrows for MCP tool connections and fan-out patterns for A2A agent-to-agent communication.
Your next architecture review, animated
Paste your agent workflow or AI architecture. 30 seconds to a shareable diagram. No signup required.
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