The Evaluations framework in iOS 27 lets developers iteratively improve AI-powered features by running structured evaluations, scoring outputs with a model judge, and measuring alignment between model and human ratings using Cohen's kappa coefficient. This hill-climbing workflow enables systematic prompt and feature quality improvement with confidence.
ā¢ Provides a scientific, repeatable process for improving AI prompt quality ā replacing guesswork with measurable alignment scores (Cohen's kappa)
ā¢ Catches model judge 'drift' early by quantifying how much the AI rater diverges from your own expert human ratings
ā¢ Integrates directly into Swift Testing and Xcode's Evaluations report, making AI quality a first-class CI/CD concern
Foundation Models is a new Apple framework introduced in iOS 27 that gives developers on-device access to the same Apple Intelligence language model powering system features, enabling text generation, structured output, and tool-calling entirely on-device without a network connection.
Visual Intelligence brings iOS 17's Visual Look Up capabilities to a new developer-facing API surface in iOS 27, letting apps pipe live camera frames or static images through on-device scene understanding to extract subjects, text, barcodes, and rich semantic labels without any cloud round-trip.
iOS 27 opens the Foundation Models framework to third-party LLM providers via a new public LanguageModel protocol, enabling anyone to integrate custom, server-based, or open-source models using the same Swift API as Apple's on-device system model.
In-depth guide
iOS 27 On-Device AI & Apple Intelligence āApp Schemas let developers describe their app's content and actions using pre-defined domain schemas (like the Calendar domain) so Siri can understand, search, and act on app data without custom NLP. Entities conforming to IndexedEntity are donated to Spotlight's semantic index, enabling natural-language queries over app content.