zetic-ai/ZETIC_Melange_apps

NPU powered On-device AI Mobile applications using Melange

Swift

70

325 commits

updated Aug 25, 2026

See the code

README

📦 This repository has moved

Melange Applications is now → Awesome On-Device AI Apps

This repository is frozen and no longer maintained.

Every app here (plus many new ones, 36+ and growing) has moved to the new home, rebranded, documented in 7 languages, and easier to run.

👉 Go to the new repository: https://github.com/zetic-ai/awesome-on-device-ai-apps

Please open new issues and pull requests there. Existing links below are kept for reference only.


Melange Applications

Open Source, On-device AI Apps

License Platform ZETIC

Melange Documentation Melange Dashboard ZeticApp Play Store ZeticApp App Store Discord


Build Local, NPU-Accelerated AI Apps

Production-ready source code for on-device AI.
Automated conversion. Full NPU speed. Deployed in hours.

Quick Start • Available Models • Documentation • Contribute


📖 About This Repository

Welcome to the collection of open-source, on-device AI applications built with Melange. These are not just demos; they are production-grade apps running entirely locally. They demonstrate how to run AI models directly on user devices with full NPU acceleration. By using Melange's automated optimization, what used to require months of hardware-specific tuning now takes just hours.

What is Melange?

Melange is an NPU-native platform that takes your AI model and turns it into a production-ready mobile app automatically. At ZETIC, we built Melange to make AI Faster, Cheaper, Safer, and Independent.

Why Melange?

Here's what makes Melange special:

  • 🚀 Up to 60x Faster - Full NPU acceleration that delivers real-time, zero-latency performance.
  • 🔒 Private & Offline - Everything runs on-device. No internet, no cloud costs, no data leaks.
  • ⏱️ Deploy in 1 Hour - Automated conversion from raw model to mobile SDKs (no manual tuning required) in hours, not weeks.
  • 📱 Production Tested - Benchmarked on 200+ devices to ensure reliability.
  • 💻 3 Lines of Code - All you need to integrate with our unified Android/iOS API.
  • 📚 Multiple Model Sources - Support for custom model uploads, Hugging Face links, and our curated library.

Why This Repository?

We've put together real, working examples to help you build with Melange:

  • ✅ Production-Ready Code - Complete, deployable apps (not just toy demos) showing best practices
  • ✅ Multiple Use Cases - Computer vision, NLP, audio processing, and more
  • ✅ Universal Support - Learn patterns that work across both Android and iOS
  • ✅ Open Source - Apache 2.0 licensed. Use it however you want.

🚀 Quick Start

Get started with Melange in minutes:

# 1. Clone the repository
git clone https://github.com/zetic-ai/ZETIC_Melange_apps.git
cd ZETIC_Melange_apps

# 2. Get your free Melange API key
# Sign up at https://mlange.zetic.ai and get your personal access token

# 3. Configure your API key (automated)
./adapt_mlange_key.sh

# 4. Choose an app and run it
# Android: Open apps/<ModelName>/Android in Android Studio
# iOS: Open apps/<ModelName>/iOS in Xcode

💡 Getting Started: To run these applications, you'll need a free Melange Personal Access Token.

  1. Sign up or log in at the Melange Dashboard
  2. Navigate to Settings → Personal Access Token
  3. Generate your token and use it with the setup script

Melange automatically handles model optimization, NPU acceleration, and deployment. No manual configuration required!


🎯 Available Local AI Apps

FeatureModelDescriptionMelange Page
Conversational AIQwen3ChatOn-device large language model chatbot with real-time token streaming and dynamic context window.View
AI KeyboardLFM2.5-350MOn-device AI keyboard — rewrite with tones, smart replies, translation, and grammar fixes in any app. The small LFM2.5 model runs entirely inside the keyboard (iOS) / IME (Android); offline after the first download.View
Time Series ForecastingChronos BoltProbabilistic time series forecasting with quantile output; CSV import and interactive charts.View
3D ReconstructionDepth-Anything-V2-SmallSingle-photo on-device depth estimation with interactive 3D relief mesh and point-cloud views.View
Machine TranslationOffline Translator (HY-MT)Fully offline translation with text, voice (on-device STT), and visual/OCR input — real-time streaming and instant language swapping.View
Grammar Correctiont5-base-grammar-correctionRobust grammar correction based on T5 architecture for real-time text processing.View
Privacy / Anonymizationtanaos-text-anonymizer-v1Automatic detection and masking of PII (names, dates, locations, emails, phone numbers) for secure data processing.View
Object DetectionYOLO26Next-generation NMS-free object detection.View
Audio AnalysisYamNetClassification of environmental sounds and audio events.View
Object DetectionYOLOv8 NanoReal-time object detection and tracking in milliseconds.View
Face TrackingMediaPipe Face LandmarkerHigh-fidelity 468-point face mesh and landmark tracking.View
Motion AnalysisYOLO26n · RTMPose-s · MotionBERT-LiteOn-device human-pose tracking and 3D motion lifting for sports-form and swing-review workflows.Detect · Pose · Lift
Face DetectionMediaPipe BlazeFaceUltra-fast face detection optimized for short-range selfie cameras.View
Emotion AnalysisEmo-AffectNetReal-time facial emotion recognition.View
Speech RecognitionWhisper TinyHigh-accuracy automatic speech recognition (ASR) completely offline.View
Private AI NotepadGemma 4 E2BOn-Device AI Meeting Notes powered by Gemma. Granola, Pocket alternative. Private by design.View
Multimodal WellbeingWav2Vec2-Base_Emotion-Recognition · FaceEmotionRecognitionGuided on-device mood check-in that fuses live facial-emotion and voice-emotion analysis into an explainable, non-diagnostic well-being readout — camera and audio never leave the device.Voice · Face
Voice BiomarkerWav2Vec2-Base_Emotion-Recognition · YAMNETDual-tab on-device voice biomarkers — wav2vec2 speech-emotion plus YAMNet respiratory acoustic-event detection (cough, breathing, wheeze). Microphone audio never leaves the device.Emotion · Respiratory
Camera VitalsEfficientPhys-rPPGContactless heart-rate measurement from the front camera using the EfficientPhys rPPG model — fully on-device, no frames leave the phone.View
Medical ImagingEchoNet-DeepLab-v3On-device cardiac ultrasound LV segmentation with live mask overlays and device benchmark metrics.View
Skin ClassificationSkin Cancer ViTOn-device skin-lesion image classification (ViT, 7 HAM10000 lesion types). Reads a photo's pixels locally with confidence scoring and curated, severity-aware guidance — no images leave the device.View

🔮 Coming Soon

We're always adding new models. Here's what's on the way:

Use CaseModelDescription
Machine TranslationTranslateGemma-4B-ITInstruction-tuned multilingual translation model with 4B parameters.
TTSQwen3-TTS-12Hz-0.6B-CustomVoiceCustom voice Text-to-Speech synthesis with high-quality audio output.
Speech RecognitionMedASRMedical domain automatic speech recognition for healthcare applications.
Healthcare / VQAMedGemma-1.5-4b-itMultimodal medical question answering and image understanding.
TTSneutts-nanoCompact, high-quality Text-to-Speech synthesis.
Depth EstimationDA3-SMALLEfficient multi-view depth estimation for 3D understanding.
TTSpocket-ttsUltra-lightweight real-time speech synthesis.
Speech RecognitionOmniASRMultilingual automatic speech recognition supporting 100+ languages with CTC architecture.

[!TIP] Want to ship your own model? You can upload your model to Melange, convert it for on-device inference, and build an app from the generated code. No need to wait for a demo here.


📁 Repository Structure

ZETIC_Melange_apps/
├── apps/                          # On-device AI applications
│   ├── ChronosTimeSeries/        # Time series forecasting (Chronos Bolt)
│   │   ├── Android/              # Android implementation
│   │   ├── iOS/                  # iOS implementation
│   │   └── prepare/              # Model preparation scripts
│   ├── YOLO26/                   # Object detection app
│   ├── translate-tencent_HY-MT/  # Offline translation (text, voice, OCR)
│   ├── whisper-tiny/             # Speech recognition app
│   ├── TextAnonymizer/           # PII detection and masking
│   └── ...                       # More apps
├── res/screenshots/              # Demo GIFs and images for app READMEs
├── extension/                    # Melange Extension Library (submodule)
│   └── Helper extensions and utilities
├── adapt_mlange_key.sh           # Script to configure API keys
└── LICENSE                       # Apache 2.0 License

Each app includes:

  • Android/ - Full Android Studio project (Kotlin)
  • iOS/ - Full Xcode project (Swift)
  • prepare/ - Scripts to prepare and export models
  • README.md - Documentation for each app

💻 Deploying Models in Your Own App

Want to use these NPU capabilities in your own app? The Melange SDK makes it simple. You don't need to write complex hardware code, just initialize the SDK and start running inference instantly.

Android

1. Add Dependency

In your build.gradle.kts:

dependencies {
    implementation("com.zeticai.mlange:mlange:+")
}

2. Initialize and Run

import com.zeticai.mlange.core.model.ZeticMLangeModel
import com.zeticai.mlange.core.tensor.Tensor

// Initialize model
val model = ZeticMLangeModel(
    context = this,
    tokenKey = "YOUR_PERSONAL_KEY",
    modelName = "Team_ZETIC/YOLO26"
)

// Prepare inputs
val inputs: Array<Tensor> = // ... prepare your tensors

// Run inference
val outputs = model.run(inputs)

iOS

1. Add Package

Add via Swift Package Manager:

  • Repository URL: https://github.com/zetic-ai/ZeticMLangeiOS.git

2. Initialize and Run

import ZeticMLange

// Initialize model
let model = try ZeticMLangeModel(
    tokenKey: "YOUR_PERSONAL_KEY",
    name: "Team_ZETIC/YOLO26",
    version: 1
)

// Prepare inputs
let inputs: [Tensor] = // ... prepare your tensors

// Run inference
let outputs = try model.run(inputs: inputs)

Learn More

  • Melange Dashboard - Upload your models, get NPU-optimized SDKs, see how they perform on 200+ devices
  • Melange Documentation - Full API reference and step-by-step guides
  • ZETIC - Everything you need to know about Melange

🤝 Contributing New Examples

We love seeing what developers build! This repository is an open-source collection of demo apps, and we welcome new additions to the gallery.

How to Contribute

  1. Fork the repo and create a branch (git checkout -b feature/amazing-app)
  2. Build your app:
    • Option A: Use one of the pre-optimized models available on the Melange Dashboard
    • Option B: Have a custom model you want to showcase? You can upload your model to Melange, convert it for on-device inference, and generate production-ready code automatically. Or join our Discord and let us know, we'd love to help you get it running.
  3. Follow the Standards
    • Keep code structure consistent with existing apps.
    • Include both Android and iOS versions if possible.
  4. Document It
    • Add a README.md inside your app folder explaining what it does.
    • Don't forget: Add your app to the main table in the root README.md.
  5. Test it: Verify it works on real devices (not just simulators).
  6. Open a Pull Request:
    • Include a clear description, screenshots, or a demo video.
    • Mention which Melange model you used.

Need Help?


📚 Resources

  • Website: zetic.ai
  • Melange Dashboard: mlange.zetic.ai - Get NPU-optimized SDKs, view benchmarks, and upload custom models
  • Documentation: docs.zetic.ai - Full API reference and guides
  • Discord: Join our Discord - Get help, share what you're building, meet other developers

Check Out Our Demo App

  • ZeticApp: Android | iOS - Our official Melange showcase app

📄 License

This repository (the source code and example apps) is licensed under the Apache License 2.0.

⚠️ Note: The Melange SDK is a proprietary library subject to the ZETIC Terms of Service.

You can:

  • ✅ Use it commercially (Apache 2.0)
  • ✅ Use it privately
  • ✅ Modify and share the example apps

Just remember to:

  • 📋 Keep the license and copyright notice
  • 📋 Mention any big changes you make
  • 📋 Include the NOTICE file if it's there

🙏 Acknowledgments

  • Big thanks to all our contributors who keep making this project better
  • Shoutout to the model providers and the amazing open-source AI community

ai
ai-computing
ai-infrastructure
aiinfrastructure
edgeai
edge-computing
npu
on-device-ai
vibe-coding

zetic-ai/ZETIC_Melange_apps

NPU powered On-device AI Mobile applications using Melange

Swift

70

325 commits

updated Aug 25, 2026

See the code

README

📦 This repository has moved

Melange Applications is now → Awesome On-Device AI Apps

This repository is frozen and no longer maintained.

Every app here (plus many new ones, 36+ and growing) has moved to the new home, rebranded, documented in 7 languages, and easier to run.

👉 Go to the new repository: https://github.com/zetic-ai/awesome-on-device-ai-apps

Please open new issues and pull requests there. Existing links below are kept for reference only.


Melange Applications

Open Source, On-device AI Apps

License Platform ZETIC

Melange Documentation Melange Dashboard ZeticApp Play Store ZeticApp App Store Discord


Build Local, NPU-Accelerated AI Apps

Production-ready source code for on-device AI.
Automated conversion. Full NPU speed. Deployed in hours.

Quick Start • Available Models • Documentation • Contribute


📖 About This Repository

Welcome to the collection of open-source, on-device AI applications built with Melange. These are not just demos; they are production-grade apps running entirely locally. They demonstrate how to run AI models directly on user devices with full NPU acceleration. By using Melange's automated optimization, what used to require months of hardware-specific tuning now takes just hours.

What is Melange?

Melange is an NPU-native platform that takes your AI model and turns it into a production-ready mobile app automatically. At ZETIC, we built Melange to make AI Faster, Cheaper, Safer, and Independent.

Why Melange?

Here's what makes Melange special:

  • 🚀 Up to 60x Faster - Full NPU acceleration that delivers real-time, zero-latency performance.
  • 🔒 Private & Offline - Everything runs on-device. No internet, no cloud costs, no data leaks.
  • ⏱️ Deploy in 1 Hour - Automated conversion from raw model to mobile SDKs (no manual tuning required) in hours, not weeks.
  • 📱 Production Tested - Benchmarked on 200+ devices to ensure reliability.
  • 💻 3 Lines of Code - All you need to integrate with our unified Android/iOS API.
  • 📚 Multiple Model Sources - Support for custom model uploads, Hugging Face links, and our curated library.

Why This Repository?

We've put together real, working examples to help you build with Melange:

  • ✅ Production-Ready Code - Complete, deployable apps (not just toy demos) showing best practices
  • ✅ Multiple Use Cases - Computer vision, NLP, audio processing, and more
  • ✅ Universal Support - Learn patterns that work across both Android and iOS
  • ✅ Open Source - Apache 2.0 licensed. Use it however you want.

🚀 Quick Start

Get started with Melange in minutes:

# 1. Clone the repository
git clone https://github.com/zetic-ai/ZETIC_Melange_apps.git
cd ZETIC_Melange_apps

# 2. Get your free Melange API key
# Sign up at https://mlange.zetic.ai and get your personal access token

# 3. Configure your API key (automated)
./adapt_mlange_key.sh

# 4. Choose an app and run it
# Android: Open apps/<ModelName>/Android in Android Studio
# iOS: Open apps/<ModelName>/iOS in Xcode

💡 Getting Started: To run these applications, you'll need a free Melange Personal Access Token.

  1. Sign up or log in at the Melange Dashboard
  2. Navigate to Settings → Personal Access Token
  3. Generate your token and use it with the setup script

Melange automatically handles model optimization, NPU acceleration, and deployment. No manual configuration required!


🎯 Available Local AI Apps

FeatureModelDescriptionMelange Page
Conversational AIQwen3ChatOn-device large language model chatbot with real-time token streaming and dynamic context window.View
AI KeyboardLFM2.5-350MOn-device AI keyboard — rewrite with tones, smart replies, translation, and grammar fixes in any app. The small LFM2.5 model runs entirely inside the keyboard (iOS) / IME (Android); offline after the first download.View
Time Series ForecastingChronos BoltProbabilistic time series forecasting with quantile output; CSV import and interactive charts.View
3D ReconstructionDepth-Anything-V2-SmallSingle-photo on-device depth estimation with interactive 3D relief mesh and point-cloud views.View
Machine TranslationOffline Translator (HY-MT)Fully offline translation with text, voice (on-device STT), and visual/OCR input — real-time streaming and instant language swapping.View
Grammar Correctiont5-base-grammar-correctionRobust grammar correction based on T5 architecture for real-time text processing.View
Privacy / Anonymizationtanaos-text-anonymizer-v1Automatic detection and masking of PII (names, dates, locations, emails, phone numbers) for secure data processing.View
Object DetectionYOLO26Next-generation NMS-free object detection.View
Audio AnalysisYamNetClassification of environmental sounds and audio events.View
Object DetectionYOLOv8 NanoReal-time object detection and tracking in milliseconds.View
Face TrackingMediaPipe Face LandmarkerHigh-fidelity 468-point face mesh and landmark tracking.View
Motion AnalysisYOLO26n · RTMPose-s · MotionBERT-LiteOn-device human-pose tracking and 3D motion lifting for sports-form and swing-review workflows.Detect · Pose · Lift
Face DetectionMediaPipe BlazeFaceUltra-fast face detection optimized for short-range selfie cameras.View
Emotion AnalysisEmo-AffectNetReal-time facial emotion recognition.View
Speech RecognitionWhisper TinyHigh-accuracy automatic speech recognition (ASR) completely offline.View
Private AI NotepadGemma 4 E2BOn-Device AI Meeting Notes powered by Gemma. Granola, Pocket alternative. Private by design.View
Multimodal WellbeingWav2Vec2-Base_Emotion-Recognition · FaceEmotionRecognitionGuided on-device mood check-in that fuses live facial-emotion and voice-emotion analysis into an explainable, non-diagnostic well-being readout — camera and audio never leave the device.Voice · Face
Voice BiomarkerWav2Vec2-Base_Emotion-Recognition · YAMNETDual-tab on-device voice biomarkers — wav2vec2 speech-emotion plus YAMNet respiratory acoustic-event detection (cough, breathing, wheeze). Microphone audio never leaves the device.Emotion · Respiratory
Camera VitalsEfficientPhys-rPPGContactless heart-rate measurement from the front camera using the EfficientPhys rPPG model — fully on-device, no frames leave the phone.View
Medical ImagingEchoNet-DeepLab-v3On-device cardiac ultrasound LV segmentation with live mask overlays and device benchmark metrics.View
Skin ClassificationSkin Cancer ViTOn-device skin-lesion image classification (ViT, 7 HAM10000 lesion types). Reads a photo's pixels locally with confidence scoring and curated, severity-aware guidance — no images leave the device.View

🔮 Coming Soon

We're always adding new models. Here's what's on the way:

Use CaseModelDescription
Machine TranslationTranslateGemma-4B-ITInstruction-tuned multilingual translation model with 4B parameters.
TTSQwen3-TTS-12Hz-0.6B-CustomVoiceCustom voice Text-to-Speech synthesis with high-quality audio output.
Speech RecognitionMedASRMedical domain automatic speech recognition for healthcare applications.
Healthcare / VQAMedGemma-1.5-4b-itMultimodal medical question answering and image understanding.
TTSneutts-nanoCompact, high-quality Text-to-Speech synthesis.
Depth EstimationDA3-SMALLEfficient multi-view depth estimation for 3D understanding.
TTSpocket-ttsUltra-lightweight real-time speech synthesis.
Speech RecognitionOmniASRMultilingual automatic speech recognition supporting 100+ languages with CTC architecture.

[!TIP] Want to ship your own model? You can upload your model to Melange, convert it for on-device inference, and build an app from the generated code. No need to wait for a demo here.


📁 Repository Structure

ZETIC_Melange_apps/
├── apps/                          # On-device AI applications
│   ├── ChronosTimeSeries/        # Time series forecasting (Chronos Bolt)
│   │   ├── Android/              # Android implementation
│   │   ├── iOS/                  # iOS implementation
│   │   └── prepare/              # Model preparation scripts
│   ├── YOLO26/                   # Object detection app
│   ├── translate-tencent_HY-MT/  # Offline translation (text, voice, OCR)
│   ├── whisper-tiny/             # Speech recognition app
│   ├── TextAnonymizer/           # PII detection and masking
│   └── ...                       # More apps
├── res/screenshots/              # Demo GIFs and images for app READMEs
├── extension/                    # Melange Extension Library (submodule)
│   └── Helper extensions and utilities
├── adapt_mlange_key.sh           # Script to configure API keys
└── LICENSE                       # Apache 2.0 License

Each app includes:

  • Android/ - Full Android Studio project (Kotlin)
  • iOS/ - Full Xcode project (Swift)
  • prepare/ - Scripts to prepare and export models
  • README.md - Documentation for each app

💻 Deploying Models in Your Own App

Want to use these NPU capabilities in your own app? The Melange SDK makes it simple. You don't need to write complex hardware code, just initialize the SDK and start running inference instantly.

Android

1. Add Dependency

In your build.gradle.kts:

dependencies {
    implementation("com.zeticai.mlange:mlange:+")
}

2. Initialize and Run

import com.zeticai.mlange.core.model.ZeticMLangeModel
import com.zeticai.mlange.core.tensor.Tensor

// Initialize model
val model = ZeticMLangeModel(
    context = this,
    tokenKey = "YOUR_PERSONAL_KEY",
    modelName = "Team_ZETIC/YOLO26"
)

// Prepare inputs
val inputs: Array<Tensor> = // ... prepare your tensors

// Run inference
val outputs = model.run(inputs)

iOS

1. Add Package

Add via Swift Package Manager:

  • Repository URL: https://github.com/zetic-ai/ZeticMLangeiOS.git

2. Initialize and Run

import ZeticMLange

// Initialize model
let model = try ZeticMLangeModel(
    tokenKey: "YOUR_PERSONAL_KEY",
    name: "Team_ZETIC/YOLO26",
    version: 1
)

// Prepare inputs
let inputs: [Tensor] = // ... prepare your tensors

// Run inference
let outputs = try model.run(inputs: inputs)

Learn More

  • Melange Dashboard - Upload your models, get NPU-optimized SDKs, see how they perform on 200+ devices
  • Melange Documentation - Full API reference and step-by-step guides
  • ZETIC - Everything you need to know about Melange

🤝 Contributing New Examples

We love seeing what developers build! This repository is an open-source collection of demo apps, and we welcome new additions to the gallery.

How to Contribute

  1. Fork the repo and create a branch (git checkout -b feature/amazing-app)
  2. Build your app:
    • Option A: Use one of the pre-optimized models available on the Melange Dashboard
    • Option B: Have a custom model you want to showcase? You can upload your model to Melange, convert it for on-device inference, and generate production-ready code automatically. Or join our Discord and let us know, we'd love to help you get it running.
  3. Follow the Standards
    • Keep code structure consistent with existing apps.
    • Include both Android and iOS versions if possible.
  4. Document It
    • Add a README.md inside your app folder explaining what it does.
    • Don't forget: Add your app to the main table in the root README.md.
  5. Test it: Verify it works on real devices (not just simulators).
  6. Open a Pull Request:
    • Include a clear description, screenshots, or a demo video.
    • Mention which Melange model you used.

Need Help?


📚 Resources

  • Website: zetic.ai
  • Melange Dashboard: mlange.zetic.ai - Get NPU-optimized SDKs, view benchmarks, and upload custom models
  • Documentation: docs.zetic.ai - Full API reference and guides
  • Discord: Join our Discord - Get help, share what you're building, meet other developers

Check Out Our Demo App

  • ZeticApp: Android | iOS - Our official Melange showcase app

📄 License

This repository (the source code and example apps) is licensed under the Apache License 2.0.

⚠️ Note: The Melange SDK is a proprietary library subject to the ZETIC Terms of Service.

You can:

  • ✅ Use it commercially (Apache 2.0)
  • ✅ Use it privately
  • ✅ Modify and share the example apps

Just remember to:

  • 📋 Keep the license and copyright notice
  • 📋 Mention any big changes you make
  • 📋 Include the NOTICE file if it's there

🙏 Acknowledgments

  • Big thanks to all our contributors who keep making this project better
  • Shoutout to the model providers and the amazing open-source AI community

ai
ai-computing
ai-infrastructure
aiinfrastructure
edgeai
edge-computing
npu
on-device-ai
vibe-coding