How Apple's Foundation Models framework unlocks on-device AI

At the recent WWDC, Apple unveiled a key component of its AI strategy: the Foundation Models framework. This helps iOS app developers integrate powerful AI directly into their apps, fundamentally changing how to deliver intelligent features. 

It signals Apple's intent to strengthen the Apple Intelligence ecosystem by providing accessible, cost-efficient AI solutions that run seamlessly on its devices. It also marks a notable shift from Apple's historically controlled approach, empowering developers and businesses with previously hard-to-access advanced AI. 

The best news? We expect dramatically improved responsiveness, reduced latency, and enhanced user privacy, all without traditional cloud-based inference costs.

For our clients, Foundation Models is an opportunity to differentiate their app features, boost user engagement, and align with Apple's commitment to privacy and performance – all while benefiting from the trust, scale, and cost efficiency of Apple’s AI platform. In this post, we’ll explore how product leaders and their teams can leverage this framework to navigate privacy, optimize performance, and build more intelligent apps.

The Foundation Models framework symbol.

What is Apple's Foundation Models framework?

At its core, the Foundation Models framework is Apple's technical gateway to AI. It lets developers add specific AI capabilities right into their apps. This means an app can offer intelligent, privacy-preserving, and offline-capable AI experiences without incurring per-query inference fees. This reduces the need for setting up cloud infrastructure, cuts down on delays, and ensures features work even with poor connectivity.

Privacy and security benefits

Unlike many competing AI models that send data to remote servers, much of the AI processing with Apple’s Foundation Models happens directly on the user's device. This keeps sensitive data local, reducing the "data in transit" risk common with cloud AI. For any advanced tasks needing cloud processing, Apple offers Private Cloud Compute (PCC) which also doesn't store personal data by deleting it automatically after processing. This means no personal data is stored on external servers, and end-to-end encryption is used for cloud processing.

This privacy-first stance can be a major competitive edge and trust builder for your brand. You can position your app as a "privacy-first AI" solution and potentially reduce your efforts on compliance work (like GDPR, CCPA) while lowering your insurance liability from data breaches. Apps using Apple's Foundation Models leverage the same privacy-first technologies that power Apple's own ecosystem, offering a sense of trust for privacy-aware users.

Performance and cost efficiency benefits

Without needing to query a cloud-based AI model, your business avoids variable per-query costs from each user interaction of your app. You’ll still have the initial fixed costs for development and integration (which would be required for any AI model you integrate with), but unlike most cloud-based AI solutions, Apple does not charge developers for using its Foundation Models framework. So, AI costs will stay flat as your app grows, enabling feature growth without proportional cost increases.

On-device processing also means a faster, more responsive, and potentially more reliable user experience. By avoiding network trips, AI responses are quicker than with cloud processing. This creates immediate interactions for features like text suggestions and image recognition. And for offline or low-connectivity situations, these features work regardless of internet connection. While competitors' cloud-dependent features might fail, your app could maintain full functionality, offering a more consistent user experience.

Core benefits of using the Foundation Models framework.

Opportunities for your app: Quick wins and big ideas

Apple's Foundation Models framework offers important progress for Apple Intelligence, primarily by unlocking intelligent features and opening up new strategic opportunities for your app.

Quick wins

If you already have an app, using Apple's Foundation Models can give you some fast, easy wins that add immediate value for your customers. These can make your existing features better, and help you boost app engagement, increase user retention, and amplify revenue streams.

Here are some practical examples:

• Hyper-personalized content: Get real-time product recommendations based on browsing, dynamic playlist generation based on mood or history, or adaptive learning paths, all using local user data without privacy issues.

• Real-time contextual assistance: Offer context-aware writing help, smart suggestions during form filling, or instant language translation/pronunciation feedback, with AI processed locally for immediate feedback.

• Dynamic content generation: Create personalized texts, summaries, or responses on demand, potentially cutting API costs or delays. This includes meeting transcriptions or personalized study materials.

• Consistent offline functionality: Features that usually need the Internet now work offline, making AI support always available. For example, an in-app search for content or smart calendar scheduling can work even without a connection.

Bigger ideas: Build the next generation of apps

Beyond just improving what you have, direct access to Apple's on-device Foundation Models could help you build completely new kinds of apps and open up new business models. Consider redesigning core features around on-device AI, leveraging privacy as a differentiator, embracing an offline-first architecture, and exploring new revenue models like shifting to experience-based pricing or building “AI-native" apps.

• Personal AI assistants: Imagine apps that are truly private digital companions, learning user preferences without any data ever leaving their device.

• Hyper-local intelligence apps: Get instant insights about surroundings without sending location data to servers, or even when completely offline.

• Offline-first professional tools: Think full-featured design, writing, or analysis apps that work entirely disconnected, offering top-notch reliability and privacy for sensitive work.

Navigating Apple’s AI Foundation Models: Your path forward

While Apple's Foundation Models framework offers exciting opportunities, it is important to approach it with a clear understanding of the capabilities and limitations.

It significantly lowers barriers for on-device AI, aligning with Apple's strengths in privacy and performance. However, many believe Apple's AI models don’t match the raw performance of the largest cloud-based foundation models in all areas. They excel at context-specific, user-centric tasks (personalization, offline functions) but are not designed for general world knowledge or large, fast-changing data sets. It's a strategic tool for privacy-first, offline-capable intelligence — not a "silver bullet" for all AI needs.

Integrating these models requires investment in understanding the framework, designing the user experience, and integration development. Device compatibility is limited to newer hardware (iPhone 16, 15 Pro/Pro Max, M1 Macs/iPads or later) running recent OS versions. This impacts your target audience and rollout strategy. Consider analyzing your user base, planning gradual updates as the installed base shifts to newer devices, and offering graceful fallback options for older devices.

ArcTouch can help you navigate your AI opportunity

Navigating the fast-changing AI landscape requires deep expertise. ArcTouch has been building for the Apple ecosystem since the dawn of the App Store. We also have extensive experience using AI software to build lovable apps. Contact us to explore how Apple's latest tools can transform your app user experience.