AI in the Enterprise

The Paradigm Shift

Cloud AI is fast to start, but not always the right default. Local AI gives you data sovereignty, predictable costs, and control over access and operations.

Benefits of Local AI

1. Data Sovereignty

Your data never leaves your network. Less compliance risk, fewer GDPR headaches. You control access and what happens with your data.

2. Costs

No pay-per-token fees. After the initial setup, ongoing costs are predictable and often 70-90% lower than cloud alternatives.

3. Latency

Local models respond in milliseconds. No network dependency, no downtime due to internet issues.

4. Customization

You can fine-tune models, create own embeddings, implement RAG - all without external dependencies.

Typical Use Cases

• Customer Support: Automated German-language responses
• Document Processing: Contract analysis, invoice parsing
• Internal Search: Search knowledge base
• Code Assistance: Custom coding model for your team

Requirements

• At least 16GB RAM (better 32GB+)
• Modern CPU or GPU for fast inference
• Basic understanding of Docker / Linux
• IT resources for maintenance

Cost Comparison (Example)

Conclusion

Local AI is not for everyone. If you take privacy seriously, want cost control, and can run the stack, local is often the better option. Break-even is frequently around 20,000-50,000 API calls per month.