SimpleSeverance

Problem

Most employees who get a severance package don't know if the offer is fair. Lawyers cost a lot, HR isn't there to help, and online advice is usually too generic to fit each person's situation. As a result, people often sign whatever they're given, missing out on money or protections.

I realized there was an opportunity to create a tool that gives employees real, personalized guidance without having to pay a lawyer up front.

Approach

I began by researching employment law, talking to people who had gone through severance negotiations, and figuring out which risks really matter in a package. Then I built an assessment system that changes its questions based on earlier answers, so users only see what matters to them.

On the technical side, I chose Next.js and Supabase to move fast as a solo builder. I designed the database schema around multi-tenant isolation using Row-Level Security policies, built complex triggers for automated scoring and state management, and implemented a full authentication flow with session handling.

Solution

SimpleSeverance guides users through a smart assessment with more than 90 questions to evaluate their severance package against different risks. The system uses branching logic to skip questions that don't matter, keeping things focused. At the end, users receive AI-powered risk scores, advice on weak spots in their package, and clear guidance on whether to negotiate, consult a lawyer, or accept the offer.

My Role

I did everything myself as a solo founder. I handled market research, user interviews, product design, UX in Figma, database setup, backend and frontend coding, and the scoring algorithms. I also planned the go-to-market strategy and launch. This project shows what I mean when I say I take full ownership of the outcome, not just the task.