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README.md

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+# 🛰️ ZETIC.ai — On-Device AI for Every Device
+
+**Build. Deploy. Run. Anywhere.**  
+ZETIC.ai helps AI engineers deploy models on *any* mobile device — without cloud GPU servers.  
+We transform your existing AI models into **NPU-optimized, on-device runtimes** in **under 24 hours**.
+
+---
+
+## 🚀 What We Do
+
+**ZETIC.MLange** — our core platform — enables **serverless AI** by:
+- **Automated Conversion**: Convert your PyTorch, ONNX, or TFLite model into a device-specific NPU library.
+- **Peak Performance**: Up to **60× faster** than GPU cloud inference, with zero accuracy loss.
+- **Broad Compatibility**: Supports Android, iOS, Linux; MediaTek, Qualcomm, Apple NPUs — more coming soon.
+- **End-to-End SDK**: From model optimization to app integration — no extra engineering required.
+
+---
+
+## 🛠 Key Features
+
+- **Zero GPU Costs** — Replace expensive GPU cloud servers with *free* NPU power in devices.
+- **Full Privacy & Security** — Data never leaves the device.
+- **Ultra-Low Latency** — Real-time AI experiences, even offline.
+- **Cross-Platform** — One model → All devices → Same performance.
+
+---
+
+## 📦 Example Use Cases
+
+- 🎙 **Speech Recognition (Whisper)** — Real-time, offline transcription on mobile.
+- 🦷 **Dental AI Diagnostics** — Instant tooth condition analysis via smartphone camera.
+- 🏌️ **Sports AI** — On-device golf swing analytics.
+- 🤖 **On-Device LLMs** — Chat & reasoning models running entirely offline.
+
+---
+
+## 📊 Benchmarks
+
+| Device | Task | Cloud GPU | On-Device NPU | Speedup |
+|--------|------|-----------|---------------|---------|
+| iPhone 16 Pro | Whisper-Small | 1.2s | 0.07s | **×17** |
+| Galaxy S24 Ultra | LLaMA-3-8B | 2.4s/token | 0.09s/token | **×26** |
+
+[🔗 See more benchmarks »](https://mlange.zetic.ai)
+
+
+### YOLOv8n — NPU Latency (ms)
+| Index | Device | Manufacturer | CPU | GPU | CPU/GPU | NPU |
+|-------|--------|--------------|-----|-----|---------|-----|
+| 1 | Google Pixel 7 Pro | Google | 205.43 | - | 404.93 | - |
+| 2 | Apple iPhone 16 | Apple | 126.27 | - | 8.98 | **2.03** |
+| 3 | Apple iPhone 16 Pro | Apple | 122.23 | - | 7.54 | **1.69** |
+| 4 | Apple iPad (2022) | Apple | 167.97 | - | 19.26 | **4.74** |
+| 5 | Apple iPhone 14 | Apple | 133.21 | - | 17.13 | **4.68** |
+| ... | ... | ... | ... | ... | ... | ... |
+
 ---
-title: README
-emoji: 💻
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+
+### Whisper-tiny-encoder — NPU Latency (ms)
+| Index | Device | Manufacturer | CPU | GPU | CPU/GPU | NPU |
+|-------|--------|--------------|-----|-----|---------|-----|
+| 1 | Apple iPhone 16 | Apple | 552.13 | - | 44.49 | **19.01** |
+| 2 | Apple iPhone 16 Pro | Apple | 540.04 | - | 42.43 | **18.15** |
+| 3 | Apple iPhone 16 Pro Max | Apple | 526.12 | - | 40.72 | **17.92** |
+| 4 | Apple iPhone 15 | Apple | 605.12 | - | 48.88 | **18.23** |
+| 5 | Apple iPhone 15 Plus | Apple | 632.67 | - | 49.20 | **23.35** |
+| ... | ... | ... | ... | ... | ... | ... |
+
+
+- **You can get runtime source code and benchmark report of your model with [ZETIC.MLange](https://mlange.zetic.ai)**
+
+---
+
+## 👨🏻‍💻 Plug-and-play To Your App
+
+- The runtime SDK is also provided for your AI model with ZETIC.MLange
+
+- **iOS Integration** (Swift)
+```
+import ZeticMLange
+
+// Load NPU-optimized model
+let model = try MLangeModel.load(from: "whisper_small_npu.mlange")
+
+// Prepare input
+let inputAudio = loadAudioTensor("sample.wav") // implement your loader
+
+// Run inference
+let output = try model.run(input: inputAudio)
+
+print("Transcription: \(output.text)")
+```
+
+- **Android Integration** (Kotlin, Java)
+```
+import ai.zetic.mlange.MLangeModel
+
+// Load packaged NPU runtime
+val model = MLangeModel.load(context, "llama3_small_npu.mlange")
+
+// Run text generation
+val prompt = "Tell me a short story about a fox."
+val output = model.run(prompt)
+
+println("🦊 AI says: $output")
+```
+
+
+## 📥 Try It Now
+
+- **MLange Dashboard**: [https://mlange.zetic.ai](https://mlange.zetic.ai)  
+- **Demo Apps**: [App Store](https://apps.apple.com/app/zeticapp/id6739862746) / [Google Play](https://play.google.com/store/apps/details?id=com.zeticai.zeticapp)
+
+---
+
+## 🧭 Supported Targets
+
+- **OS**: Android, iOS, Linux
+- **NPUs**: MediaTek, Qualcomm, Apple (more coming)
+- **Frameworks In**: PyTorch, ONNX, TFLite
+- **Artifacts Out**: NPU-optimized runtime libraries + SDK bindings (Kotlin, Java, Swift, Flutter, React Native)
+
+## 📬 Contact Us
+
+- **Website**: [https://zetic.ai](https://zetic.ai)
+- **Email**: [email protected]
+- **LinkedIn**: [linkedin.com/company/zetic-ai](https://linkedin.com/company/zetic-ai)
+
 ---
 
-Edit this `README.md` markdown file to author your organization card.
+**ZETIC.ai** — AI for All, Anytime, Anywhere.  
+Run your AI where it matters: **on the device.**