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Apple Chose Gemini: What It Teaches Teams Facing a Build vs Buy Decision

Published on June 9, 2026

Apple Chose Gemini: What It Teaches Teams Facing a Build vs Buy Decision

Apple decided to use Gemini as the foundation for its next generation of Foundation Models. The decision matters to teams weighing build against buy because even a company able to fund either route chose to concentrate control on data, orchestration and product experience.

The models run partly on-device and partly through Private Cloud Compute. Apple keeps the experience, privacy controls and request routing inside its own system while relying on an external foundation.

Where Control Remains

A founder asked us to build his proprietary AI. Before discussing models, we separated two forms of ownership: owning the weights, and owning the problem, data and rules that make the system useful. The second group was where the company could build a defensible advantage.

The orchestration layer decides which data enters, which model handles the task, what happens when a service fails and which actions require approval. That layer allows a provider to be replaced without rebuilding the product.

We have seen the opposite. One client invested in the model while neglecting messy data, exceptions and fallbacks. The model worked; the system did not.

Three Questions Before You Choose

  1. Is the model the product, or does it support a problem your company understands better than the providers?
  2. Can you replace the provider without rebuilding workflows, permissions and interfaces?
  3. Have you defined what data the model may receive, who approves its actions and what happens when the service fails?

The answers determine where to invest: a proprietary model, an external integration or an architecture that can use multiple providers. Before integrating, document the data, permissions, fallbacks and replacement strategy.

Related Services

If you're weighing a build vs buy decision around AI components, explore our approach to AI development in Turin. When AI needs to become part of a scalable product, the work moves into SaaS product engineering and requires a software company in Turin that can design architecture, integrations and governance.


Built by Worksdem, a product engineering studio specialising in custom software, AI workflows and enterprise apps. If you're working on something like this, let's talk: no slide decks, no strings attached.