AI Multi-Platform Streaming App

I’m building an entertainment app that streams video on Android, iOS, LG webOS, and Samsung Tizen. The core experience centres on both live streaming and an on-demand catalogue, with an AI layer that surfaces personalised recommendations and smart search results in real time.

The flow I have in mind is straightforward: users sign in once, land on a home screen tailored by the recommendation engine, and can jump between live channels or the on-demand library without friction. Playback must support adaptive-bitrate HLS/DASH, multiple audio tracks, and subtitles. Because this spans mobile and smart-TV ecosystems, the UI needs to scale gracefully from touch interactions to remote-control navigation.

I’ll provide brand assets, sample content feeds, and access to the existing CDN. What I need from you is an end-to-end codebase, a lightweight Node/Python backend that drives the AI recommender, and store-ready builds for each platform.

Deliverables
• Unified code repository with modular front-end targets: Android (Kotlin/Java), iOS (Swift/Objective-C), LG webOS (web-app), Samsung Tizen (Tizen Studio)
• Backend microservice powering recommendations, user profiles, and playback entitlements
• API documentation & Postman collection
• CI/CD scripts that produce release builds and run automated tests
• Short video demo and installable binaries for acceptance

Acceptance criteria
1. Live and on-demand streams play smoothly at varying bandwidths on all target devices.
2. Recommendation engine returns results within 200 ms for typical queries.
3. Remote-control navigation on LG/Samsung passes provided UX checklist.
4. Code passes automated unit tests and a basic security scan.

If any platform-specific constraints need clarification, let me know early so we can keep the timeline realistic.