# On-Device AI — Suvegasoft

> Privacy-first AI that runs entirely on your hardware. Local inference with WebGL, Ollama. Zero data leaves your infrastructure.

- Canonical: https://suvegasoft.co.uk/services/on-device-ai/

## Key Benefits

- Zero cloud dependency
- Complete data privacy
- HIPAA/GDPR compliant
- Works offline

## Why Choose This Service

### Complete Privacy

Data never leaves your device or infrastructure. No cloud APIs, no data transmission, no privacy concerns.

### Local Inference

Run models via WebGL in browsers or Ollama on servers. Full AI capabilities without external dependencies.

### Flexible Deployment

Browser-based for end-user devices, on-premise servers for enterprise, or edge devices for IoT. Your choice.

### Cost Effective

No per-token API costs. Once deployed, inference is essentially free. Scales without scaling bills.

### Works Offline

Full functionality without internet connection. Critical for healthcare, field operations, and secure environments.

### Your Models

Deploy fine-tuned models you own. No vendor lock-in. Full control over model updates and versions.

## Our Implementation Process

1. **Requirements Analysis** (1 week) — Understand your privacy requirements, hardware constraints, and performance needs. Define what AI capabilities you need locally.
2. **Model Selection & Optimization** (1-2 weeks) — Choose appropriate models (Whisper, Gemma, Llama, etc.) and optimize for your target hardware. Quantization and pruning as needed.
3. **Integration Development** (2-3 weeks) — Build the local inference pipeline integrated with your application. WebGL for browsers, Ollama for servers, or custom runtimes.
4. **Testing & Deployment** (1-2 weeks) — Validate on target hardware, optimize performance, and deploy. Training for your team on maintaining the system.

## Frequently Asked Questions

### What models can run on-device?

Speech-to-text (Whisper), small-to-medium LLMs (Gemma, Llama, Phi), embedding models, and specialized models. The limit depends on your hardware, but modern devices can run surprisingly capable models.

### How does browser-based AI work?

We use WebGL and WebGPU to run models directly in the browser using the device's GPU. No installation required, no data leaves the browser. Works on laptops, tablets, and even phones.

### What about performance vs cloud APIs?

Local models are typically smaller and may be less capable than GPT-4 for general tasks. However, for domain-specific applications with fine-tuned models, local can match or exceed cloud performance while maintaining privacy.

### Is on-device AI HIPAA compliant?

Yes. When data never leaves the device, there's no data transmission to secure. This simplifies HIPAA compliance significantly. Our dental documentation system serves 200+ practices with full GDPR compliance.

### What hardware do we need?

For browser-based: any modern device with a GPU (most laptops/desktops from 2018+). For server deployment: depends on model size and throughput needs. We help you spec appropriate hardware.

### Can we update models after deployment?

Yes. Models can be updated by deploying new versions. For browser-based solutions, users get updates automatically. For on-premise, you control the update schedule.

### What about internet-connected features?

On-device AI can work alongside cloud features. You might run sensitive processing locally while using cloud for non-sensitive operations. We help you design the right hybrid architecture.

### How do you handle model size limitations?

Through quantization (4-bit, 8-bit), pruning, and model distillation. A 7B parameter model can run on a laptop GPU. We optimize for your specific hardware and performance requirements.

## Work With Us

Book a discovery call to discuss your use case: https://suvegasoft.co.uk/contact/