The Smart TV Experience,
Reimagined with AI

A next-generation framework for building broadcasting apps across every screen — from phones to set-top boxes to smart TVs. Powered by Flutter, with AI-driven developer tooling that accelerates your entire workflow.

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What We're Building

One codebase. Every screen. Built for broadcasting.

FlutterTV is a unified platform that lets developers create beautiful, high-performance broadcasting applications for phones, set-top boxes, smart TVs, and beyond — all from a single Dart codebase.

But this isn't just another cross-platform toolkit. It's built from the ground up with AI tooling for developers — LLM gateways, an agent orchestration layer, a skill/tool registry, and prompt management — so teams ship faster, reuse more, and stop rebuilding the same thing for every platform.

The result: over 90% shared code across targets, a dramatically shorter time-to-market, and a framework that grows with your device fleet — not against it.

Key Features

Everything you need to ship faster

🧠

AI Tooling for Developers

Not AI-as-a-feature — AI as a force multiplier. Built-in LLM gateway (DeepSeek, GPT, Claude, on-device models), agent orchestration, skill/tool registry, context management, and prompt engine. Developers wire up intelligent behaviour without starting from scratch.

📺

Write Once, Run Everywhere

A single shared Dart core with over 90% code reuse across phones, set-top boxes, and smart TVs of every kind. Platform-specific optimizations live at the embedder level — native performance where it counts, shared logic everywhere else.

🎨

Adaptive UI Per Platform

Layouts that adapt to the device, not the other way around. TV-optimized grid navigation on the big screen, touch-friendly lists on mobile. Per-platform theming, responsive breakpoints, and accessibility adjustments — all driven by configuration, not hardcoded rules.

🔌

Plugin-First Architecture

Every external concern — players, CMS, analytics, new components, even new target platforms — is a plugin. The core framework stays lean. Plugins register through a central registry with typed contracts and dependency resolution. Add Hisense or tvOS support without touching framework internals.

⚙️

Runtime Configuration & Personalization

UI structure, content layout, and theming are configurable at runtime via a CMS abstraction layer. Personalization rules — who sees what, when — are driven by configuration, not code deploys. Update the homepage layout for a new campaign without rolling a build.

Performance-First from Day One

TV devices are resource-constrained. The framework is designed for low-latency rendering, lazy component loading, on-device model support, and background prefetching. Every millisecond of startup time is accounted for.

Platforms

Built for the devices people actually watch

Our initial Proof of Concept targets three key platforms — with an architecture designed to expand across the full landscape of connected-TV devices.

Platform Devices Status
Android Mobile Phones, tablets POC
Android TV Set-top boxes, Fire TV, Chromecast, NVIDIA Shield, operator STBs POC
LG webOS LG Smart TVs (all recent models) POC
Coming Next
Samsung Tizen Samsung Smart TVs, monitors Planned
Apple tvOS Apple TV HD, Apple TV 4K Planned
Roku Roku streaming players, Roku TV Planned
Gaming Consoles Xbox, PlayStation Planned

The plugin architecture means every new platform is additive — no rewrites, no forks. The same Dart business logic, a new embedder.

Why This Matters

The cross-platform tax is real

Building broadcasting apps today means maintaining separate codebases for each platform — Android (Java/Kotlin), webOS (JavaScript), tvOS (Swift), Tizen (C++/JS), and more. Each with its own UI toolkit, its own player integration, its own analytics pipeline, its own release cadence.

A single feature — a new content row on the home screen — can take three sprints to land everywhere. Platform quirks multiply regression risk. Delivery timelines stretch because there's no shared foundation.

FlutterTV gives teams a single codebase with a single delivery pipeline. Business logic lives in shared Dart. UI adapts per platform through configuration, not duplication. AI tooling — LLM gateways, agent orchestration, context management — is baked into the framework so developers can wire up intelligent behaviour on day one, not month six.

Less code. Fewer bugs. Faster delivery. That's the point.

The Vision

Quick start. Write once. Ship everywhere.

Imagine spinning up a new broadcasting app project and having a working three-platform build — Android Mobile, Android TV, LG webOS — within the first hour. A scaffolded project with navigation, theming, player abstraction, and AI plumbing already wired in.

Imagine writing your content recommendation logic once — in Dart — and having it run identically on a $30 streaming stick, a flagship phone, and a premium OLED TV. No per-platform rewrites. No lowest-common-denominator UX.

That's what FlutterTV is building. A framework where business logic is written once, where AI tooling isn't a separate project but the foundation, and where expanding to a new platform means writing an embedder — not rewriting your app.

What's Next

Proof of Concept roadmap

We're building in phases, validating the architecture at each step.

  1. 1

    Foundation

    Core framework, plugin system, theming engine, and context management.

  2. 2

    AI Developer Experience

    LLM gateway abstraction, agent orchestration, skill/tool registry, prompt management, and on-device model support — all exposed through clean APIs. Define skills once, register them, and any agent in the framework can call them — no per-platform wiring, no model lock-in.

  3. 3

    Platform Support

    Embedders for Android Mobile, Android TV, and LG webOS with native player and input integration.

  4. 4

    UI Components

    Adaptive component library with TV-optimized navigation and responsive grids.

  5. 5

    Integration

    CMS-driven layouts, configuration-based personalization, player abstraction, and analytics pipeline.

  6. 6

    Performance & Polish

    Rendering benchmarks, startup-time optimization, memory profiling on constrained devices, and comprehensive test coverage.