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Smartphone on wooden table displaying an online shopping app with plants and crystals nearby.
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Development

Scentwise

In ProgressStarted 202516

Overview

An ongoing fragrance discovery project built with Next.js and Supabase. I’m developing structured fragrance data, search and clear detail pages, with an initial focus on a small, usable first version.

At a glance

  • Concept: a fragrance discovery platform — search, explore, and understand scents without the usual retail clutter.
  • Status: in development since August 2025, starting with a focused first version.
  • Stack: Next.js, Supabase, TypeScript, deployed on a modern serverless pipeline.
  • Audience: fragrance lovers who want better tools, and curious newcomers who need a gentler on-ramp.
  • Current focus: the core data model, search and a clear, readable interface.

The idea

I want fragrance discovery to offer more useful context about scents. Scentwise explores two questions: what might I like, and why? The aim is to make fragrance information easier to browse and understand.

What I am building

The first version is deliberately narrow. I am not trying to be a full retailer or a social network on day one. The MVP is about discovery mechanics: structured fragrance data, search that respects how people actually talk about scent, and pages that explain a fragrance in plain language.

  • Fragrance catalog with consistent metadata — notes, families, and context that survives a search.
  • Discovery flows tuned for browsing, not just filtering by brand.
  • A fast, readable UI — mobile-first, minimal chrome, no dark patterns.
  • Auth and user data via Supabase — lightweight accounts when they earn their keep.

Stack & approach

Next.js for the app shell and rendering strategy, Supabase for database and auth, TypeScript throughout. The architecture bias is boring on purpose: fewer moving parts, easier to iterate while the product shape is still fluid.

Where it is now

The project is in active development. The first version focuses on the data model, search and fragrance detail pages; the wider feature set is still being shaped.

What is next

  • Tighten the core search and detail experience before adding social or recommendation layers.
  • Validate the data model against real catalog imports — edge cases always show up late.
  • Ship a usable MVP, then decide what "version two" actually needs based on feedback, not assumptions.