Twendi - Multi-Role SaaS athlete discovery and campaign platform

Project Overview

Twendi is an athlete discovery and collaboration platform designed to connect athletes, brands, and fans in a structured ecosystem. The platform allows brands to discover athletes, initiate campaigns, manage offers and deliveries, and collaborate through real-time communication.

The goal of the MVP was to transform an early concept — originally a simple Framer-based UI — into a scalable, production-ready web application capable of supporting real workflows between multiple user roles.

The system was designed with four independent dashboards:

• Athlete Dashboard

• Brand Dashboard

• Fan Dashboard

• Admin Dashboard

Each role has clearly defined responsibilities and permissions, making Twendi a multi-tenant, role-driven SaaS application.

Platform Overview

Problem Statement

When the project began, the client:

• Had only a basic UI prototype

• Did not have clear functional requirements

• Had no defined workflow between athletes and brands

• Required iterative discovery during development

The challenge was not only technical — it was also product definition.

The MVP needed to:

• Define how brands interact with athletes

• Structure campaign and offer flows

• Enable real-time communication

• Provide analytics and approval workflows

• Remain scalable for future expansion

Solution Approach

I adopted an Agile development approach, starting with UI validation before backend implementation.

Development Strategy

1. Convert conceptual UI into functional flows

2. Validate each module with the client before backend work

3. Build modular APIs for flexibility

4. Introduce real-time architecture early

5. Optimize for scalability instead of shortcuts

This allowed continuous feedback while preventing major architectural rewrites later.

System Architecture

Frontend

• Next.js 16 (App Router)

• Cache Components

• SEO-driven architecture

• Server/Client component separation

• Dynamic filtering and search

Backend

• Node.js + Express.js REST APIs

• Supabase PostgreSQL

• Supabase Storage (Media Assets)

• Role-based access flows

Real-Time Layer

• Socket.io for real-time messaging

• Redis for event handling and chat performance

Background Processing

• CRON jobs

• Agenda (Job Queue)

• Scheduled processing and async operations

Communication

• Nodemailer

• EJS email templates

• Google Workspace SMTP

Platform Modules

1. Athlete Dashboard

Athletes can:

• Create and complete profiles (minimum 90% completion required)

• Submit profile for admin approval

• Receive approval or rejection with feedback

• View dashboard analytics:

• Campaigns

• Offers

• Earnings

• Followers

• Communicate with brands via real-time chat

• Submit campaign deliveries for approval

Workflow example:

Brand → Discussion → Campaign → Multiple Offers → Deliveries → Approval → Payment

2. Brand Dashboard

Brands can:

• Create and manage profiles

• Search athletes using filters

• Follow athletes

• Initiate real-time conversations

• Create campaigns

• Send multiple offers per campaign

• Approve or request delivery changes

• Track analytics

3. Fan Dashboard

Fans have simplified access:

• Discover athletes

• Follow athletes

• Build engagement metrics

4. Admin Dashboard

Admin controls include:

• Athlete approvals/rejections

• Platform moderation

• Data management

• System oversight

Public Platform Features

• Home landing page

• Athlete discovery page with advanced filters

• Dedicated sport pages

• Country analytics pages

• FAQ, Privacy Policy, Terms

• SEO optimized routing

Key Technical Challenges

1. Undefined Requirements

The biggest challenge was that requirements evolved during development.

Solution:

• Frequent review cycles

• UI-first validation

• Agile iteration

• Modular backend design

This prevented costly rewrites later.

2. Scope Management

New features were frequently requested outside the original agreement.

Approach:

• Delivered reasonable improvements when beneficial

• Maintained professional boundaries for out-of-scope work

• Ensured project timeline stability

This reflects real-world MVP development challenges.

3. AI Recommendation System (Unexpected Requirement)

During development, the client requested personalized recommendations.

• Learned and integrated OpenAI initially

• Later migrated to Gemini as requested

• Built working prototypes

Eventually the feature was removed due to budget constraints.

Outcome:

• Feature removed professionally

• Architecture preserved

• Gained experience in AI integrations which later influenced future work

4. External QA Coordination

The client hired an external QA team.

Challenges included:

• Slow testing cycles

• Mostly UI/UX feedback rather than functional issues

• Coordination delays

Solution:

• Iterative fixes

• Clear communication loops

• Stable release management

Performance & Architecture Decisions

Key MVP decisions that improved scalability:

• Redis for real-time events instead of database polling

• Background job processing via Agenda

• Next.js caching for performance

• Modular API structure for future microservices migration

• Supabase for rapid MVP delivery with strong database reliability

Results

• Platform successfully launched: 31 January 2026

• Delivered within ~3 months development cycle

• Fully functional multi-role ecosystem

• Real-time campaign collaboration system

• Production deployment completed

Post-launch support continued for one month.

Client feedback (5-star rating):

“Overall, the experience was good, but there is room for improvement. The project went well, however I had to repeatedly ensure alignment with the original contract. Some unnecessary features were added, extra tasks were requested outside scope, and the testing team hired by Adam was slower than expected.”

This reflects a real production environment where scope and expectations evolve — and demonstrates professional project delivery under changing requirements.

Key Takeaways

This project demonstrates:

✅ Ability to convert unclear ideas into structured products
✅ Full MVP architecture planning
✅ Real-time systems implementation
✅ Multi-role SaaS development
✅ Backend + frontend ownership
✅ Professional handling of scope changes
✅ Adaptability to changing technical directions

Why This Case Study Matters for MVP Clients

Twendi proves the ability to:

• Build complex MVPs from early-stage ideas

• Define workflows when requirements are unclear

• Deliver scalable architecture from day one

• Handle evolving product requirements professionally

This makes the development approach ideal for startups and founders building their first production MVP.