Velox Built for the Bubble #PromptAndCircumstance Challenge.

Velox is a modern operations dashboard that gives teams a single place to manage projects, track business metrics, and monitor performance in real time. Instead of juggling spreadsheets, analytics tools, and task boards, teams can visualize their entire workflow from project pipelines to revenue trends in one clean workspace.

Built on a Bubble AI-generated foundation and taken the rest of the way by hand.

Started with a single prompt to Bubble AI. Bubble AI generated the initial pages, database structure, and dashboard layout.

From there, I refined the workflows, analytics, navigation, and project management experience, then redesigned the interface into a clean, modern dashboard with interactive charts, KPI cards, Kanban boards, and responsive layouts.

Features

1. Real-time business dashboard with KPI tracking 2. Revenue analytics and performance trends 3. Kanban-style project management 4. Task prioritization and workflow tracking

The goal was to transform Bubble AI's starting point into a polished operations platform that feels like a production-ready SaaS product rather than a dashboard template. This was my first time building with Bubble AI, and it was impressive to see how quickly a single prompt became a functional application.

Try Velox: https://krishkhati0007king-19565.bubbleapps.io/version-test

A founder from Silicon Valley came to us with a product that was already working. The AI logic was solid. The backend did what it was supposed to. DataScoop could analyze metric changes, find the root causes and explain them in plain language - which, honestly, is genuinely hard to build. The problem was everything the user actually saw. The interface hadn't kept up with the product. There were Figma designs ready, a completely new visual direction, but no one had translated them into a working frontend yet. The existing code wasn't built to carry them. And the data visualization layer, the part that makes analytics actually readable, needed to be rebuilt from scratch. So the ask was clear on the surface: rebuild the frontend, implement the new design, make it fast. In practice, it was more nuanced than that. Complex data files needed to be parsed and turned into charts that told a story, not just displayed numbers. Performance had to hold up so that insights landed in seconds, not after a loading spinner that made you forget what you were looking at. And all of it had to feel like it belonged together: the AI output, the visualizations, the interface, the Slack and email delivery. We rebuilt the frontend in React.js and TypeScript, applied strict code quality standards from the start and worked through the Figma designs screen by screen, not just implementing them, but pressure-testing how they behaved with real data. The hardest part wasn't any single technical problem. It was maintaining coherence, making sure that as the pieces came together, they felt like one product, not a patchwork. The result is a platform where a data analyst can open it, see a metric move, and understand why, in plain language, in seconds, delivered wherever they actually work. That's the version DataScoop's users have now. Check it out

Great job