The Real Cost of Rebuilding an MVP Twice
Rebuilding your MVP is expensive — in time, money, and trust. Learn what drives costly do-overs and how to build your product right the first time.
During this webinar, we have talked about
Why so many startups rebuild their MVP
The hidden cost of rebuilding
What scalable MVP architecture actually looks like
How AI-assisted development is changing MVP timelines
A practical framework to launch a scalable MVP in 30 days
Case Studies
Developing a Data-Driven Presentation Builder MVP
Challenge:
The client needed to deliver a data visualization MVP before an investor demo.
Solution:
Integrated Google Sheets, Slides, and Drive APIs for real-time data sync and export.
Enabled automated slide creation and PowerPoint export with consistent chart rendering.
Restructured the app architecture for scalability and fast deployment via Heroku CI/CD.
Added GA4 event tracking to analyze user engagement and guide future improvements.
Result:
Delivered a fully functional MVP within 3 months, reducing presentation creation time from hours to minutes and providing actionable analytics for product validation.
Building an MVP for a UK Rail-Ticketing Startup in 12 Weeks
Challenge:
A UK startup needed a rail-ticketing product in front of partners within 12 weeks, and a platform that could keep trading once it launched.
Solution:
Scoped a 12-week mobile-first delivery plan across four discovery sprints
Stood up the mobile and backend foundations in 8 hours using pre-built solutions
Built the ticketing backend and the full booking flow, from search to wallet-ready e-ticket
Surfaced split-ticket savings and live travel information from a direct industry feed
Result:
Over £300,000 processed, over 10,000 active users, and demand from over 100 countries.
Creating an AI-Powered Talent Acquisition Platform
Challenge:
DBBS helped a startup improve its core product, an applicant tracking system, through new features, complete redesign, and scalable architecture.
Solution:
Implemented a modern front end using React, TypeScript, Next.js, Tailwind CSS, and Radix UI for intuitive UX.
Leveraged LLMs and cloud AI services to improve core functionality with AI.
Built out user management, data import/export, CI/CD pipelines, and automated testing.
Optimized performance and reduced AI-related operational costs.
Result:
Successful MVP launch with positive early-adopter feedback, better control over operational costs, and a robust, scalable architecture for future growth.
Replacing Bubble With a Custom Search Platform
Challenge:
A government-meeting platform had outgrown the no-code foundation its first version was built on, and needed search, data collection and administration it owned outright.
Solution:
Built a Boolean and fuzzy search service over meeting transcripts
Split storage between PostgreSQL for core data and MongoDB as the search engine
Rewrote the search service in Go after testing found a limit in the original Python engine
Migrated off Bubble to a normalized PostgreSQL schema on AWS with dual sync, with no downtime and data loss
Rebuilt data collection as a scraper per source site, and delivered a FastAPI and React admin panel
Result:
A wider range of queries, settings changed in one place, and more sites reached.
Ready to build it right the first time?
"Don't let your MVP become a costly do-over. We help founders get it right the first time so you can save your budget for scaling, not rebuilding.
Let's discuss your project. Fill out the form and book a free consultation!”
Mina Morkos
Business Development Manager
