Velora

#01 The product

Velora is a premium self-discovery app for reflecting on relationship and emotional patterns. Categories like Attachment Style and Communication Style group quick checks and deep-dive assessments, all drawing from a shared bank of hundreds of Likert-style questions.

Results combine dimensional scores, primary and secondary narrative archetypes, strengths and blind spots, and guidance sections for relationships, communication, stress, and growth — framed as reflective guidance, explicitly not clinical diagnosis. A compatibility feature lets users invite a partner by email or deep link and compare results.

#02 Engineering

The content model is the interesting system: versioned tests map ordered questions from the shared bank; every option carries normalized 0–100 score values, a construct (dimension), optional reverse scoring, and a weight. Scoring profiles and archetype mappings turn dimension scores into narrative results via category-ordered rules — all seeded through ordered SQL migrations in Supabase Postgres.

The Expo app renders one question per screen with Reanimated transitions, stores answers locally in AsyncStorage, and syncs to user-scoped tables under row-level security. Client-side scoring computes weighted means per construct with confidence heuristics. An Edge Function generates AI result insights with contract-shaped JSON and logged generations; premium sections gate through a RevenueCat entitlement, with Sentry for observability.

Full theming (light/dark/system) and localization in English, German, and Turkish are in from day one.

#03 Status

In active development — schema, quiz engine, scoring, archetype resolution, results UI, and compatibility invites are implemented; AI insight generation, RevenueCat products, and store release are the remaining path to launch.