A polished UI can make a product feel completely different, but getting there usually takes more than changing a few colors or swapping out an old chart. Modern design to code tools can now handle much of that work, from redesigning an existing interface to generating the frontend code behind it.
Instead of testing each tool with a different project or judging them from a demo, I wanted to put them on equal ground. So I took the same outdated SaaS analytics dashboard, gave the same dashboard screenshot to five popular tools, and used the same redesign prompt for every test.
I wanted to see how each one handled the same real-world UI problem: modernizing an old dashboard while keeping its core information and functionality intact.
I also looked at the generated frontend code, because a beautiful interface doesn’t help much if the code underneath it becomes a mess that developers have to rebuild.
So, how different were the results when every tool started with exactly the same design and instructions?
I tested five design to code tools, Flowstep, Anima, v0 by Vercel, Lovable, and Bolt.new, using the same outdated SaaS analytics dashboard and the same redesign prompt.
The original dashboard had the kind of interface you might recognize from older analytics products: dense navigation, dated typography, limited visual hierarchy, tightly packed content, and a layout that could use a serious UX refresh.
The challenge for each tool was to preserve the dashboard’s core information while giving it a modern 2026 interface.
I evaluated the results across several areas, including visual design, hierarchy, spacing, typography, component quality, UX, and frontend code quality.
Flowstep → Strongest overall redesign, with a modern visual system, clear hierarchy, polished spacing, and well-structured frontend code. Anima → Produced a cleaner interface with good code, although the final design still felt fairly basic. v0 by Vercel → Stayed close to the original dashboard while improving its presentation; the result still needed more visual refinement. Lovable → Delivered a clean, well-designed dashboard with solid frontend code and a good overall balance. Bolt.new → Created a well-structured interface with good hierarchy and typography, although the result needed some additional updates.
The test also showed something that can get lost in AI tool comparisons: design to code tools are not equally good at the same parts of the workflow.
A tool can produce impressive code while delivering an average visual redesign, while another can create a polished interface but leave more work for the developer.
That’s why I’m not treating this as a competition to discover which tool generated the prettiest UI. What matters more to me is how much each tool improved the starting design and how usable the result would be for a real frontend project.
Design to code tools are platforms that help turn visual designs, screenshots, UI concepts, or product requirements into frontend interfaces and code.
The category has changed quite a bit with the rise of AI. Traditional design to code workflows often started with a finished design file, such as a Figma project, and focused on translating that design into HTML, CSS, React, or another frontend stack.
You might give a tool a Figma design and ask it to generate the implementation. You might provide a screenshot and ask it to recreate or redesign the interface. Or you might describe the product you want and have the tool generate the UI and application code from a prompt.
That makes design to code tools useful for several different workflows, including:
Figma to code screenshot to code AI UI generation prompt to UI development AI app building