AI Systems Mermaid Diagrams

Modern AI applications are built from a web of interacting pipelines, models, and data stores that are difficult to reason about without a clear visual model. This collection of 20 free Mermaid diagrams covers the full lifecycle of production AI systems — from the moment a user query enters an LLM Request Flow to the long-running loops of an AI Feedback Loop that continuously improves model quality.

Retrieval-Augmented Generation is represented end-to-end: the RAG Architecture diagram connects document ingestion, Embedding Generation Flow, and Vector Database Query into a single coherent picture. For prompt engineering, see Prompt Processing Pipeline and Prompt Cache System, which show how modern inference stacks reduce latency and cost.

Agentic systems have their own dedicated diagrams: AI Agent Workflow maps the plan-act-observe loop, while AI Tool Calling Flow shows how models invoke external functions at runtime. The collection also covers the full MLOps lifecycle — Model Training Pipeline, Feature Engineering Pipeline, Inference Pipeline, and Model Version Deployment. Application-layer patterns round out the set: AI Search System, AI Ranking Pipeline, AI Recommendation System, AI Moderation Pipeline, AI Content Generation Pipeline, and AI Chat Application Architecture. Every diagram opens directly in Graphlet for live editing and export.

Frequently asked questions

AI systems diagrams are visual representations of the components, data flows, and interactions within production AI applications — such as LLM serving stacks, RAG pipelines, agent loops, and MLOps workflows. They help engineers reason about complex, multi-system architectures at a glance.

Mermaid diagrams use a plain-text syntax that can be committed alongside code, embedded in documentation, and rendered in tools like GitHub, Notion, and Graphlet. This makes it easy to keep architecture diagrams up to date as systems evolve.

The collection spans the full AI lifecycle: LLM inference and streaming, RAG and embedding pipelines, vector databases, prompt engineering, AI agents and tool calling, MLOps (training, feature engineering, inference, deployment), and application-layer patterns like search, ranking, recommendations, moderation, and chat.

Yes. Every diagram in this collection opens in Graphlet for live editing. You can modify the Mermaid source, preview changes in real time, and export to SVG, PNG, or copy the code for use in your own documentation.

AI Systems Diagrams

Frequently asked questions