What inspired you to build FluoTest?
I noticed that many teams in HR, consulting, and education were manually screening responses or using generic form tools that didn't support weighted scoring or automated decision workflows. I wanted to create a platform that could handle complex scoring logic without requiring custom development, so teams could focus on interpreting results rather than building infrastructure.
How did you approach building the platform?
I started with the core scoring engine, making sure it could handle weighted questions and conditional branching. Then I layered on branding customization, automated email notifications, and analytics. The stack is TypeScript, Next.js, and Supabase, which allowed me to iterate quickly while keeping the backend scalable.
What early feedback or traction have you seen?
Early users have been excited about the ability to create multi-score decision models, where different question sets contribute to separate scores. They appreciate the flexibility to customize branding and automate follow-up actions. I'm now exploring which decision workflows provide the highest value across different industries.
What are you currently working on or stuck on?
I'm trying to understand whether users prefer score-based outcomes (like a numeric threshold) or answer-based outcomes (like specific response patterns). I'm also exploring demand for multi-score models and the most effective ways to automate actions after a decision is made. Feedback from testers and advisors would be very helpful.
How is FluoTest different from other quiz or assessment tools?
Most form tools treat all questions equally and don't support weighted scoring or conditional logic that triggers different outcomes based on responses. FluoTest is built specifically for decision automation, where the scoring model drives next steps like sending tailored emails, updating CRM records, or triggering internal notifications.