Data privacy
Your data never leaves your machines, whether embedded or served.
Why Local AI · Local vs Cloud
Your AI. Your data. On your infrastructure.
Cloud AI sends every query to someone else's servers. Local AI keeps everything on hardware you control, inside your application or on your own server. For privacy-first software, the choice is clear.
Ultra-low latency
10-50ms response times with no network delays.
Fixed costs
One license, unlimited inference. No per-token fees.
Offline ready
Deploy anywhere, even without internet access.
Choose your path.
Not sure which approach fits your project? Here's a simple guide to help you decide.
LM-Kit Local AI
- Data privacy: nothing leaves your device
- Zero latency: no network round-trips
- Works offline: no internet required
- Predictable costs: one-time license, unlimited inference
- Full control: customize, fine-tune, deploy anywhere
- No surprise deprecations: your models stay stable forever
- No provider outages: no network failures, no rate limits
Cloud AI
- Data exposure risk: queries sent to third-party servers
- Network latency: 100-500ms+ per request
- Internet dependent: offline means broken app
- Unpredictable costs: pay-per-token adds up fast
- Vendor lock-in: dependent on API changes and pricing
- Constant deprecations: models retired, behavior changes without warning
- Service outages: provider downtime breaks your app
When to choose Local AI
- You handle sensitive data (healthcare, legal, finance)
- You need to comply with GDPR, HIPAA, or similar regulations
- Your app must work offline or in air-gapped environments
- You want predictable costs without per-token billing
- Low latency is critical for your user experience
- You need stable, reproducible model behavior over time
- You want to fine-tune or customize models for your domain
When to choose Cloud AI
- You're building a quick prototype or proof-of-concept
- Data privacy is not a primary concern
- You always have reliable internet connectivity
- You need access to the largest frontier models
- You have minimal on-device compute resources
- You're okay with variable costs and potential API changes
- Latency of 200-500ms is acceptable for your use case
Side-by-side breakdown.
A detailed look at how local AI with LM-Kit compares to cloud-based solutions.
| Feature | LM-Kit (Local) | Cloud APIs |
|---|---|---|
| Data Privacy | Yes | No |
| Offline Capability | Yes | No |
| Latency | ~10-50ms | 100-500ms+ |
| Cost Model | Fixed license | Pay-per-token |
| Model Stability | Yes | No |
| Service Reliability | Bounded by your own infrastructure | Depends on provider |
| Model Customization | Yes | Limited |
| Supports GDPR/HIPAA programs | Yes | Varies |
| Vendor Lock-in | None | High |
| Air-gapped Deployment | Yes | No |
The local AI advantage.
Going local isn't just about privacy. It's a fundamental shift in how AI applications are built and deployed.
Complete data sovereignty
Your data never leaves your infrastructure. Process sensitive documents, customer data, and proprietary information without third-party exposure.
Predictable performance
No more waiting on API rate limits or dealing with service outages. Local inference means consistent, reliable performance every time.
Cost control
Stop watching tokens burn through your budget. With a fixed license, run unlimited inferences without per-call pricing surprises.
No deprecation headaches
Cloud providers constantly retire models and change behavior. With local AI, your models stay exactly as they are, forever stable and reproducible.
Ultra-low latency
Eliminate network round-trips entirely. Local inference delivers responses in milliseconds, enabling real-time AI experiences.
Always available
Network failures, provider outages, rate limits: none of this affects local AI. Your application works reliably, every single time.
Local, two ways.
One engine ships in two delivery forms; going local does not dictate your architecture.
Embed it
LM-Kit.NET, inside your app
A NuGet package that runs models, documents, RAG, and agents in your .NET process. Nothing to deploy beside the application.
Serve it
LM-Kit One, for every app
The Private AI Application Server: the same engine behind OpenAI, Anthropic, Ollama and MCP dialects, with documents, search, agents, and governance.
When local AI is the right choice.
Local AI isn't for everyone. But for these scenarios, it's the only option that makes sense.
Healthcare & medical records
Process patient data, clinical notes, and medical documents while supporting HIPAA programs.
Financial services
Analyze transactions, assess risk, and process sensitive financial data without external exposure.
Enterprise & corporate
Keep proprietary documents, contracts, and internal communications completely confidential.
Edge & IoT devices
Deploy AI on devices with limited or no connectivity. Perfect for industrial, automotive, and remote applications.
Air-gapped environments
Government, military, and high-security installations where external network access is prohibited.
Legal & law firms
Analyze contracts, briefs, and privileged communications with complete attorney-client confidentiality.
Ready to go local?
Join thousands of developers building privacy-first AI applications with LM-Kit. Start free, with no key and no signup.