Pipi three-data-centre model revisited

Mike's Notes

I was greatly influenced by a recent article by Gennaro Cuofano in The Business Engineer about how Apple ensures Privacy.

Gennaro wrote ..."

Apple’s response is not to win training. It is to dominate inference

Apple’s strategy is internally coherent:

Tier 1: On-device inference

• Small local models handle personal and contextual tasks.
• These run without network dependency and with minimal privacy leakage.

Tier 2: Private Cloud Compute

• Apple Silicon-based servers handle workloads beyond device capacity.
• The architecture is stateless and privacy-preserving.

Tier 3: Third-party frontier models

• Apple relies on external model providers such as Google and OpenAI for world knowledge and advanced reasoning.
• These models are treated as backend commodities underneath Apple’s interface layer.

..."

Resources

• https://www.blog.ajabbi.com/2025/05/a-three-data-centre-model-for-pipi.html
• https://businessengineer.ai/p/beyond-apple-the-end-of-the-mobil

References

• Reference

Repository

• Home > Ajabbi Research > Library > Subscriptions > The Business Engineer
• Home > Handbook > 

Last Updated

29/03/2026

Pipi three-data-centre model revisited

By: Mike Peters

On a Sandy Beach: 29/03/2026

Mike is the inventor and architect of Pipi and the founder of Ajabbi.

Data Centres

Because of its unusual architecture and the priority given to privacy and security, Pipi needs three separate data centres that work together in a chain.

Rendering > Staging > Cloud

• Rendering: Build enterprise applications.
• Staging: Send updates, localise and deploy enterprise applications.
• Cloud: Hosting of enterprise applications for scaling and integration.

I like the way Apple ensures privacy for people using AI on their iPhone. Any extra AI work is offloaded to Apple's cloud servers for processing, which are stateless and store nothing. That got me thinking.

Could part of Pipi be made stateless to add extra privacy like Apple?

The way Pipi is designed;

• Rendering: Unable to see any customer data.
• Cloud: Unable to see any Pipi config data.

This is to be done by using separate databases hosted in separate data centres.

Possible data centre model

• Rendering: This is stateful; each agent-engine has its own database. Each enterprise customer has a separate physical server to host a digital twin.
• Staging
• Inwards-server: Receive anonymised logs
• Outwards-server: Send updates, localise and deploy enterprise applications.
• Cloud: This would be stateful using customer-eyes-only databases.

Would that work? How?

This might only be discovered during wild ML experiments in a future startup AI Accelerator.