We have been using Mermaid for around 11 months in our CargoX logistics platform work, mainly to create and maintain diagrams that explain complex business and technical processes. What I like most is that we can create diagrams directly from text-based code instead of manually drawing every element.

For CargoX, this has been particularly useful for mapping the complete shipment lifecycle, from creating a shipment request and receiving offers from shipping providers to selecting an offer, processing the payment, assigning a driver, pickup, loading, transportation, delivery, proof of delivery, and provider payout.

We also use it to document different flows such as payment flows, driver workflows, order states, integrations, and system processes. Because the diagrams are code-based, updating a process is much faster than rebuilding a diagram manually. It also makes it easier for our team to keep diagrams consistent and include them alongside technical documentation and project files.

Another thing I appreciate is how quickly a rough process can be turned into a readable diagram. For complex logistics workflows with many steps and decision points, this saves a significant amount of documentation time. Review collected by and hosted on G2.com.

The main limitation we have encountered is that large diagrams can become difficult to manage visually. As our CargoX workflows became more detailed, a single diagram could contain many nodes, decision points, integrations, and different actors, which sometimes makes the final diagram crowded.

It also takes some time to get comfortable with Mermaid syntax. Small syntax mistakes can prevent the diagram from rendering, so when working on a large diagram, troubleshooting the exact line causing the problem can be a little frustrating.

For highly detailed diagrams, I sometimes prefer splitting one large workflow into several smaller diagrams rather than trying to represent the entire process in one view. Review collected by and hosted on G2.com.

The fact that I can create complex diagrams just by writing code is what got me hooked in the first place. I started using Mermaid in college when I needed to make class and sequence diagrams and had no idea tools like this existed. Before this I was literally using Paint-like tools to draw boxes and arrows manually.

What I genuinely like is how fast it is to go from an idea to a proper diagram. There's no time wasted on alignment or formatting — you just write the structure and it renders. For software architecture documentation especially, this is a huge productivity boost.

The free version itself is surprisingly capable — most of what I use day to day doesn't require a paid plan at all, which is rare for tools this good.

The AI compatibility is a big plus too. Since LLMs naturally output Mermaid syntax, I can describe a system and have a diagram ready in seconds. It has become a core part of how I document architecture at work.

The integrations are what really make it stick though. GitHub and GitLab render Mermaid natively in markdown files with zero setup. Notion supports it out of the box through code blocks. VS Code renders it in the built-in markdown preview. There's even an official plugin for Confluence. The syntax is completely platform-agnostic, so the same code block works across all your tools without any changes. Review collected by and hosted on G2.com.

The syntax can have a bit of a learning curve initially, especially for non-engineers on the team. Not everyone is comfortable writing code to create a diagram, which can limit adoption beyond the engineering team.

Confluence support still requires a third-party plugin rather than being natively supported, which adds a bit of friction for teams that are heavily Confluence-based.

Also for very large and complex diagrams, the rendering can sometimes feel slow and the auto-layout doesn't always produce the cleanest output — though the visual editor does let you manually reposition nodes which helps. Review collected by and hosted on G2.com.

Diagrams live as text in my markdown files, so they version-control like code. I can see exactly what changed in a PR diff and review architecture the same way I review implementation. No binary files, no merge conflicts I can't resolve.

Speed is the other thing. A diagram that took me 30+ minutes in a GUI tool takes under 5 minutes now. I iterate as fast as I can type no dragging boxes, no fighting alignment. It also works well with AI-assisted development: I can generate and refine diagrams programmatically, which isn't possible with click-and-drag tools.

I use it daily for multi-agent orchestration flows, data pipelines, and system architecture. Review collected by and hosted on G2.com.

Layout control is limited. For dense diagrams the auto-layout sometimes puts nodes where I wouldn't, and there's no clean way to override it without restructuring the graph. Larger sequence diagrams can also get wide enough to be hard to read on a normal screen.

Minor, and I'd still pick it over the alternatives. But those are the two places I lose time. Review collected by and hosted on G2.com.

An external integration started causing confusion because we had three different explanations of the same flow. The ticket described one sequence, the documentation still showed an older diagram, and the code already included retry logic that appeared in neither. I opened Mermaid Live Editor, wrote a sequence diagram with our API, the provider, the queue, and the worker, and within a few minutes we were talking about the real behavior instead of spending the meeting dragging connectors around a visual canvas. That’s where Mermaid works best for me. Because the diagram is defined as text, adding another participant, changing the order of a call, or showing an alternative response is usually quicker than editing a traditional diagram. The Live Editor updates the preview as I write, and it lets me share either a view-only link or an editable one so someone else can adjust the diagram and send back a revised version. When the final output needs to look cleaner, we also export SVGs for documentation and presentations. Gantt diagrams are useful for lightweight technical timelines, too. I can show discovery, development, testing, and deployment in the same Markdown file and export the result as SVG, PNG, or a link. I wouldn’t replace a project management tool with it, but it’s enough when the timeline belongs inside a technical proposal or architecture decision rather than a full delivery plan. Review collected by and hosted on G2.com.

The automatic layout definitely saves time, but it also means I don’t always have precise control over where each element ends up. In a visual tool, I can nudge a box a few pixels and immediately improve the reading order. With Mermaid, I usually have to adjust the direction, sequence, subgraphs, labels, or configuration, and then accept whatever the renderer produces. Review collected by and hosted on G2.com.

Writing diagrams as code works really well for me. I can describe a class diagram or an activity flow in plain text and immediately get a clean, well-laid-out result, without wasting time on formatting, spacing, or alignment. Iteration is quick, which is important when a design changes several times before it’s final. The output looks professional with minimal effort, and since the diagrams are text-based, they’re easy to version, reuse, and update as things evolve. Review collected by and hosted on G2.com.

When I went looking for them, I couldn’t find support for use case diagrams, which felt like a real gap for academic work. The pricing plans also seemed geared toward heavy users. A lighter monthly option would be a better fit for people who only create diagrams occasionally. Review collected by and hosted on G2.com.

The simplicity of creating process flow diagrams from chat based description and the flexibility to customize without rigid formatting Review collected by and hosted on G2.com.

Sometimes the ai based chat interpreter can misinterpret instructions. The scaling of preview figures. Lack of seamless copy paste Review collected by and hosted on G2.com.

I write a lot of user-facing documentation as well as operational runbacks, and Mermaid makes it extremely simple to include graphics, charts, workflow visualizations, etc. I can include the raw code, which makes it easier for others (or Future Me!) to make changes to lt later on. I can use the web interface or IDE extensions (e.g., VSCode). There are also plugins for Confluence, etc.

The syntax isn't overly complicated--basically markdown--but as a lazy person, rather than memorize it, I started using third party AI tools (e.g., Gemini) to describe what I wanted in simple narrative descriptions, and let it create the code for me. Later, I found the native AI capabilities within Mermaid itself made this even easier for realtime chart creation within the mermaid.ai interface.

The price is minimal and worth it. I really couldn't have created these diagrams on my own - my skills stopped with MS Paint. The support is also top notch - very personable, responsive. Review collected by and hosted on G2.com.

Last year, I'd have said the file management/library of saved charts...it was clunky. But they've made huge changes and it's now quite intuitive. Review collected by and hosted on G2.com.

The clarity of the final result and the simplicity of use. Review collected by and hosted on G2.com.

Occasionally, it still presents some bugs that do not allow modifications to be made. Review collected by and hosted on G2.com.

I really like the programmability and easy user interface of Mermaid. It makes it easy for me to quickly iterate on diagrams, share them with colleagues, and save them in GitHub. It also lets me automate graphs using AI, which saves me a lot of time and manual work. The initial setup was very easy. Review collected by and hosted on G2.com.

Nothing Review collected by and hosted on G2.com.

I like Mermaid Charts best for their simplicity and flexibility in creating diagrams using plain text. You can write a few lines of code to generate flowcharts, sequence diagrams, Gantt charts, or mind maps, which makes them easy to version-control and integrate into documentation. They’re lightweight, easy to update, and ideal for technical teams who want to embed diagrams directly in Markdown, wikis, or code repositories without using heavy graphic tools. Review collected by and hosted on G2.com.

Complex diagrams can become hard to read or manage in plain-text format. Custom styling and advanced formatting options are limited compared to graphic design tools. Rendering performance may slow down with very large diagrams, and troubleshooting syntax errors can be tricky for beginners. Additionally, real-time collaboration features are minimal unless integrated with another platform. Review collected by and hosted on G2.com.