build · 2026 · Full-stack mobile product
StreamFlow
Income-stream coach app for Myanmar builders
Flutter engineer · product & AI integration · Personal product · Myanmar beta
12 paths
Streams
EN + MY
i18n
Firebase
Backend
Gemini
AI
Challenge
Aspiring earners in Myanmar get generic “hustle” advice. They need guided paths, daily execution, and tools that speak Burmese — not English-only dashboards.
Approach
- 01Built AI onboarding with Gemini to assess skills, time, and resources.
- 02Mapped 12 income streams with Learning → Applying → Earning checklists.
- 03Added Daily Grind tasks, streaks, earnings charts, badges, and beta feedback.
- 04Wired Firebase Auth/Firestore/Storage + Cloud Functions for scalable backend AI quota.
Outcomes
- ▸Production-shaped Flutter architecture (Riverpod, go_router, Firebase)
- ▸AI-assisted coaching without abandoning human-guided roadmaps
- ▸Bilingual product thinking for a real local audience
StreamFlow (income_stream) is more than a tracker — it’s a coach. Users get assessed, choose a stream, follow checklists, and log earnings with gamification.
The stack is intentional: Flutter for mobile speed, Firebase for auth/data, Gemini via Cloud Functions so AI quota stays server-side.
This is the hire signal for teams that need AI-native mobile products with local-language UX — not demos that only work in English.
Stack
Building an AI-guided mobile product for a local market? Let’s scope StreamFlow-class architecture for your use case.