AI-Powered Portfolio Manager

I’m ready to bring my vision for “V Wealth AI Personal” to life and need a full-stack developer (or team) who can own the build end-to-end. The goal is a robust Web application with a companion Android app, both sharing a single codebase where possible for efficiency.

Core experience should include React (or similar modern front-end framework), responsive design patterns, Android packaging, and secure back-end work—Node, Python, or comparable stacks are all fine so long as the architecture scales. I plan to keep user sign-in straightforward with email-and-password authentication at launch; social logins and 2FA can remain optional future upgrades.

Key capabilities I expect the first production release to cover:

• Unified portfolio dashboard pulling live holdings from Zerodha and Dhan for India, and INDmoney for U.S. assets
• AI-assisted “Portfolio Doctor,” swing and intraday scanners, plus F&O analytics that surface actionable insights in plain, simple Hindi when requested
• Auto-averaging logic, realised / unrealised P&L calculation, dividend tracking, and 52-week high/low visual cues
• Candlestick chart rendering with dark-mode support across Web and Android, using a performant charting library of your choice
• Clean Excel import for any broker not yet integrated
• Mobile-first UX that gracefully expands to desktop screens

Deliverables
1. Source code repository with README and environment setup scripts
2. Deployed Web build (AWS, GCP, or similar) and signed Android APK on the Play Console (internal testing track is fine)
3. Post-launch hand-off: brief video walk-through, API keys rotated, and two weeks of bug-fix support

Acceptance criteria:
• All linked accounts sync correctly and totals reconcile to broker statements
• Candlestick charts load in under one second on a standard 4G connection
• Responsive layout maintains usability down to a 360 × 640 viewport
• Hindi explanation toggle produces context-aware summaries without untranslated jargon

If you have shipped fintech dashboards, trading-related scanners, or AI-driven insights before, please share links or screenshots. Let’s discuss a milestone plan that gets an MVP in users’ hands quickly and iterates from there.