Share your Replit creations and inspire others! Whether it’s a web app, AI project, or creative experiment, show off what you’ve built and help others learn from your journey.
Overview
This category is all about celebrating and learning from each other’s projects built on Replit. It’s not just about showing off the final product - we want to hear about your development process, the tools you used, and the challenges you overcame. Your experiences can inspire and guide others in the community.
What Makes a Great Showcase Post
Description of your project and its purpose
Technologies and Replit features used (AI Assistant, Deployments, etc.)
Key challenges faced and how you solved them
Live demo links or screenshots
Code highlights or interesting implementation details
Future plans or potential improvements
How This Category is Different
Focusing on completed or in-progress projects rather than questions or issues
Encouraging detailed technical write-ups about implementation
Creating a space for community inspiration and learning
Facilitating discussion about real-world applications of Replit’s features
Best Practices
Include deployment links if your project is live
Tag your post with relevant technologies
Be responsive to questions from interested community members
Share both successes and learning experiences
This category is essential for building a vibrant community where members can showcase their work, get feedback, and inspire others to create amazing things on Replit!
I’ve been using Replit to help me build a gift recommendation app! I write a weekly blog on gift giving and wanted to build a complementary product to help my readers.
I’ve been incredibly impressed with my AI Agent’s output and now I just need to take the leap toward getting real world outputs in the final recommendation.
I have built www.dashdiary.co.uk which is a platform that allows the public to ‘report’ bad driving or inconsiderate road users. The idea is to create awareness of bad driving and hopefully a bit of a social conscious when people view reports on the platform. It also allows for insight, such as which car brands are the ‘worst’ drivers, and where the hotspots are.
The app was entirely built with the Replit agent and Assistant. There are some libraries in use e.g. to compress uploaded images (which are stored using UploadThing. I tried S3 buckets but really struggled setting up access properly.). I also used Firebase for authentication.
In terms of futures, I would like to implement some form of gamification i.e. badges for using the platform and also licence plate validation via API. More immediately though (i.e. today) I am trying to hook up Firebase to Mailerlite to automate user onboarding and engagement.
And this is a joint venture with my 12-year old nephew. An AI training tool form students, aimed in particular with children who suffer with neuro diversity.
It is your smart, AI-powered contract assistant that helps you stay on top of all your agreements, from subscriptions and leases to insurance and service contracts. It automatically identifies key dates, renewal terms, and notice periods, and even creates ready-to-send termination letters.
This is my first project I launched with Replit.
Does anyone have some tips on how to market/showcase to get some traction?
Hi everyone, so I am currently using replit to build StoryTracker. An AI powered civic discourse and public engagement platform. If you have ever had the issue of staying on top of developing stories in an intelligent and efficient manner, this platform is for you.
Explore here: https://storytracker.news You might end up learning something new — and having a bit of fun along the way.
I’m a retired school teacher and longtime digital content and course creator since 2020. I am also a beginner in real estate investing. I don’t want to lose my shirt in real estate. So I wanted to find a way that helps me protect my capital. So I did a lot of research on what was the best way to view deals, what were good ones and what were not. I also wanted to participate in the AI wave but didn’t come from a technical or coding background at all.
Vibe coding turned out to be the bridge.
My goal was simple: find real niches where I could solve practical problems. Flip Guardian came from seeing how many beginner real estate investors, like myself, struggle to quickly evaluate value-add deals without second-guessing themselves.
What surprised me most is how accessible the process became once I was clear about what the app needed to do. Because the core purpose was tight, it kept me from bloating the product with unnecessary features.
Flip Guardian Overview
Tech Stack & Integrations
React + TypeScript frontend (Vite)
Express + Node.js backend
PostgreSQL with Drizzle ORM
Passport.js authentication
Stripe subscriptions
TanStack React Query
Tailwind + shadcn/ui
A few key things I learned building this:
When you define the user outcome first, the architecture becomes much clearer
Building the working framework early makes it far easier for the agent to generate backend routes and schemas correctly
Constraint and clarity beat complexity, especially for first-time builders
Stripe and webhooks will humble you — but they are figure-out-able
I built and deployed Flip Guardian in about two weeks. It could have been faster, but I hit friction on the Stripe and webhook setup. Working through that was actually part of the learning curve that made the project real.
Replit made this process far simpler than I ever thought possible. Instead of fighting local environments and tooling, I was able to stay focused on the product logic and user problem.
If someone is curious about vibe coding but unsure where to start, my experience is proof that you don’t need a traditional technical background to ship something real.
And yes — I’m already thinking about the next niche to solve.
BetLens helps sports bettors on FanDuel and DraftKings find high-confidence picks without hours of research (NBA, NFL, College Basketball, College Football, MLB, NHL, & WNBA). It uses real-time data and AI models to highlight value bets based on stats like EPA, success rates, and player efficiency.
Built entirely on Replit using Python, Flask, JS, and SQLite with integrations from sports data APIs and OpenAI for AI-driven insights. Replit’s AI assistant and Deployments made it possible to build a production-ready app without hiring a developer.
Managing multiple sports APIs was tricky, but Replit’s debugging tools made data normalization smooth. I also learned the power of better prompt engineering and adopted a more agile approach — building, testing, and shipping fast.
Replit let me handle backend, frontend, and hosting in one place. The AI tools accelerated development, helping me go from idea to launch in weeks instead of months.
Next:
Building a community showing leaders boards, share bets, etc. Additionally broaden player prop insights for each sport.
Augmenta was created with a simple goal: to make language translation and learning accessible to everyone, anywhere. Whether you’re traveling to a new country, communicating with someone in a different language, or learning a new tongue from scratch, Augmenta is your AI-powered companion designed to make the journey natural and effortless.
Built on cutting-edge language models, we provide instant translation across 20+ languages, voice interaction with native pronunciation, and a structured learning platform that adapts to your skill level.
