The Direct Comparison
Local AI (On-Premise)
Cloud AI
Hybrid (Recommended)
Process sensitive data locally, optionally handle non-sensitive processes in the cloud – maximum flexibility with full data control.
Decision Guide: What Suits You?
You process personal data
GDPR requires data sovereignty
You want to start quickly without hardware
Ready immediately, no infrastructure effort
You have sensitive and public data
Best combination of security and flexibility
You operate in regulated industries
Full audit control and data storage in DE/EU
Local Models for Enterprise
NVIDIA Nemotron
High-performance language models optimised for enterprise use, operable on-premise.
Llama 3.x (Meta)
Open-source language model, operable locally, no licensing costs.
Mistral / Mixtral
Efficient European models with strong performance at low resource requirements.
Frequently Asked Questions
Do I need powerful hardware for local AI?
It depends on the model and use case. Many applications run on standard server hardware. For performance-intensive models NVIDIA GPUs are recommended. Wito AI dimensions the hardware to match your use case.
Is local AI really cheaper than cloud AI?
In the long run, often yes. After the initial hardware investment there are no more API costs. At high volumes the investment typically pays off within 12–18 months.
Can cloud AI be used in a GDPR-compliant way?
With the right contracts (data processing agreement, EU hosting) cloud AI can be partially GDPR-compliant. For highly sensitive data (personnel files, health data) we still recommend local AI.
What exactly is a hybrid AI model?
Sensitive processing takes place locally; non-sensitive processes can optionally use cloud services. Defined routing rules automatically decide what is processed where.