Zoomcar isn’t just for solo car owners anymore. It's grown to include large business partners. We are talking about hosts managing fleets of 200+ cars. Each of these organisations has multiple managers, each managing a slice of that fleet. But the current “My Cars” tab on the app just wasn’t built for that scale. Tasks like updating bookings or finding car details become frustratingly inefficient at fleet scale. What we needed was a smarter, faster way to manage lots of cars without pulling our hair out.

A vendor dashboard for the web. Think: data management at scale, batch operations, and an interface that stays clean even when the data gets messy.

To be fully honest, I have used this project to go full AI-nerd. I tested different text-to-design tools and documented everything. What worked, what sucked, what surprised me. This blog is a reflection of that learning journey.

I was only provided a vague business requirement doc initially. No direction, no design—just a list of features that needed to be on the dashboard. So I turned to Claude.

The prompt was essentially just the doc and some more context about the problem.

Claude gave me a decent skeletal structure, some good ideas, some bloated extras. But it was enough to get me started. AI's only as good as your prompt, and this made that very clear.

Building off Claude’s structure, I whipped up a first draft of the dashboard focused on **Bookings, Cars, and Pricing (**the core v0 functionality).

We ditched the homepage (not enough to show yet) and kept things minimal, with alerts and filters for fast nav. This version worked, but felt off still.

round this time, Google launched Stitch, their AI UI explorer. I tossed in my newly acquired PRD (finally) and waited for a better direction.

It didn’t blow my mind, but it did help push me towards a cleaner layout.

This was also when we introduced a key feature “Swap Car”. Instead of Zoomcar auto-assigning a backup car from another host, managers could now offer a replacement from their own fleet. Super useful.

After a backend convo, we dropped search for a filter form to reduce API calls. This form would bundle all filtering into one clean action, with bonus features like multi-car license input.

To prototype this, I used Bolt and learnt how to prompt engineer via ChatGPT (I tried to squeeze into this project as many things I could try my hands on. Find the prompt engineering prompt <a href="https://x.com/iannuttall/status/1929110784719589413">here</a>).

Bolt got the job done. The structure was usable, though not super designer-friendly. Still, it helped me arrive at our final v0 draft:

Phase 4: Special appearance ft. Figma Make

Figma finally released Make in beta. This was the tool I was desperately waiting for. It uses Claude Sonnet under the hood but feels way more tailored for designers (finally, someone thought of us first and not just devs).

Using the same prompt I gave Bolt, here’s what Figma Make gave me:

From here on, I fully adopted Figma Make for the project and kept evolving the prototype for v1.

It also generated extended flows, like this side panel for car details + pause booking functionality, with zero struggle:

<a href="https://www.figma.com/make/4Ll4aX46oEZkNwbQel1eIu/Vendor-Dashboard-Booking-List--Copy-?fullscreen=1">🔗 Full prototype exploration (built in Figma Make)</a>

This isn’t a dig at any one AI tool. It’s not a “which one’s better” showdown—it’s a curiosity-fueled field test. And what I’ve learned is this: different AI tools shine in different contexts. Claude gave me a solid jumpstart. Bolt helped with structure. Figma Make felt like a creative partner. Even the less helpful tools taught me something.

The truth is, there’s no perfect one-size-fits-all solution. But that’s what makes this moment so exciting.

So keep experimenting. Keep prompting. Keep pushing buttons just to see what happens.

It’s a wild, adventurous time to be building, and if you’ve got even a little spark of curiosity, now’s the time to let it run wild.

You can email me @ shivanisingh54996@gmail.com or reach out to me on&nbsp;<a href="https://x.com/rooftopsodapop">X</a>&nbsp;/&nbsp;<a href="https://www.linkedin.com/in/ishivanisingh/">LinkedIn</a>

Used AI tools like Claude, Bolt, and Figma Make to design Zoomcar’s vendor dashboard. Explored what works, what doesn’t, and how to design smarter.

Designing with AI: Zoomcar Dashboard Exploration

- Revamped the host onboarding landing page to be more structured and user-friendly, from a clunky single page into a clear, step-by-step journey
- Audited and improved copy/design across the app in various existing flows to aid anxiety mitigation
- Built (and currently expanding) a fleet management dashboard from scratch for hosts with 100+ cars to track, manage, and optimise their fleet with ease

- Designed creatives for paid ads, app banners, CRM campaigns, and illustrations
- Created investor decks, whitepapers, and presentations for internal and external use
- Helped establishing a brand tone and voice for the host side (a fairly new concept for Indian audience)

- Led the redesign of Apty’s website to align with the new GTM strategy
- Built high-conversion landing pages, social ads, eBooks, and event collateral alongside demand-gen
- Created pitch decks and sales enablement material for leadership and board meetings
- Started as Junior Graphic Designer (Apr – Dec 2022), working on blog visuals, merch, emailers, and more

Zoomcar’s evolution brought in large fleet partners, but the tools weren’t keeping up. So we built a vendor dashboard from scratch: starting with a minimal brief, leveraging AI for early scaffolding, and designing a clean, scalable interface for high-volume operations. The v0 release focused on visibility, clarity, and a single powerful action: car swapping. With positive feedback in hand, v1 is now underway with deeper controls, alerts, and bulk workflows.

The Shift: From Individual Hosts to Fleet Powerhouses

Zoomcar started with individual car owners listing their vehicles. But over time, a new kind of host entered the picture: businesses managing hundreds of cars, each with its own internal hierarchy of managers and operations.

The platform was still trying to speak the same language to solo car owners and to organisations managing fleets of 200+. And that wasn’t working. The “My Cars” tab on the app originally designed for a single car or two crumbled under scale. Hosts couldn’t easily find booking details, pricing setups, or even which cars were live.

We needed a better way to talk to this new user.

There was no legacy system to fix, no outdated dashboard to update. This was a true zero-to-one design problem. What we had was a barebones business requirements doc cobbled together from multiple calls with product managers and enterprise clients. That was our north star.

To move faster, I turned to AI. I fed the initial requirements into Claude to get a rough draft of what a functional dashboard might look like. It wasn’t perfect—but it helped me frame the skeleton and clarify what questions still needed answers. From there, the design process kicked off in earnest.

If you're curious about how I used AI throughout the project - from ideation to early layouts. I’ve documented it all in <a href="https://shivanionrooftop.designfolio.me/project/687cebce7d5b533380ad589e">this companion case study</a>.

For our first release, we intentionally kept the dashboard lightweight but powerful where it mattered. The goal was to build trust, prove value, and make large-scale data manageable.

Each of the three primary views was designed with clarity and speed in mind:

Under the Hood: Designed for Admins, Not Just Interfaces

This wasn’t just about pretty screens. We designed for real-world workflows:

And most importantly: speed without confusion.

v0 is currently live with key partners. While we’re still waiting on deeper usage analytics, the initial demos with stakeholders were validating.

What’s Next: Building v1 With Feedback in Mind

We’re already in motion for the next version. Based on early conversations, here’s what we’re cooking:

This dashboard wasn’t just about showing data, it was about respecting the people behind that data. Fleet hosts aren’t just users, they’re businesses, with operations and urgency. By speaking their language, giving them control, and designing for scale (not just aesthetics), we’ve taken the first real step in turning Zoomcar into a platform that works with them and not around them.

Built a scalable dashboard for Zoomcar’s large fleet partners to manage cars, bookings, and actions efficiently. Designed from scratch for real impact.

Building Zoomcar’s Vendor Dashboard from the Ground Up

It’s been a pleasure working with Shivani. Her impact on product design and marketing has been outstanding. She brings fresh, from-scratch thinking to every challenge, consistently delivering unique solutions on time. Her deep understanding of design, beyond aesthetics to core principles like UX and brand identity, is what truly sets her apart. Shivani’s work ethic is unmatched; she goes above and beyond with a proactive, dependable attitude that made collaborating with her an absolute joy.

Rahul Paul

Working with Shivani was a delight. Her thoughtful approach to web design, strong grasp of UX, visual hierarchy, and responsive design consistently impressed me. She strikes the perfect balance between aesthetics and functionality, delivering clean, intuitive work. What sets her apart is her empathy—she designs with accessibility in mind, creating inclusive, user-friendly experiences. It’s this intention that elevates her work from good to great. A truly talented designer and mindful human being.

Designing with AI: Zoomcar Dashboard Exploration

Shivani Singh