SAIE vs open source vs hyperscaler
A comparison of three approaches
We have published a comparison on the SAIE website showing how our approach differs from open-source solutions and hyperscaler services. When choosing an AI platform, an organisation in a regulated sector quickly discovers that two of the three available paths have built-in limitations that cannot be bypassed
- Open source limits accountability: The code is open, but maintenance, security, compliance and development fall entirely on the organisation's team. There is no support service, no guarantee and no counterparty to a contract. For a company, this is not a platform — it is a project it must keep running itself indefinitely
- Hyperscalers limit control: Data flows through the provider's infrastructure, model selection ends at its catalogue, and the other party can change pricing and licensing terms at any time. For an organisation that cannot send data outside, this path is closed by definition — however convenient it may seem
- We built SAIE as business AI without these limitations: Open architecture and freedom to choose models as with open source; support, predictability and a contract as with an enterprise solution — while data stays in the client's environment
Seven dimensions of comparison
The comparison examines these three approaches in seven dimensions:
- Cost control
- Data protection
- AI Act compliance
- Vendor lock-in
- Freedom to choose LLM models
- Software support
- Integration with the client's environment
See the full comparison and find out which approach best suits your organisation