Manual Model Override
Dynamically route queries between the on-device 3B Core model, the 20B Advanced model, or offload massive context windows to Apple's Private Cloud Compute.
Apple Intelligence Agentic RAG
An agentic reasoning loop built around Apple's 3B foundation model. Private Cloud Compute routing, native Vision OCR, and on-device Metal SIMD4 vector embeddings. Built to bypass token limits and answer exhaustively.
Dynamically route queries between the on-device 3B Core model, the 20B Advanced model, or offload massive context windows to Apple's Private Cloud Compute.
Seamlessly synced and optimized across iOS 27 and macOS Golden Gate. A true native Swift engine built for iPhone, iPad, and Mac.
Hallucinations are blocked via Verification Gates, and every answer is injected with interactive citations that link directly to the source document.
A native multi-modal pipeline that automatically extracts and generates embeddings from complex PDFs, DOCX files, and raw visual data via Vision framework.
Stitches together multiple reasoning sessions utilizing the RAPTOR Summary Router to overcome token limits and synthesize exhaustive answers.
Powered by SQLite FTS5 and Accelerated by threadgroup-level Metal pipelines across the CPU, GPU, and Neural Engine (ANE).
On-Device Technical Trace
The agentic RAG orchestration relies on a 23-step query loop. Here is a live simulation of the engine processing local documents directly against the foundation model.
Click on any node in the architectural diagram above to inspect how that processing step operates inside the native Swift engine.
Understanding each phase of on-device RAG is critical to optimizing memory, latency, and context limitations.
Select a node to see technical implementation details, Swift API methods, and algorithmic settings.
No active log trace.
// Select a step to inspect source code.
Public Roadmap
This roadmap is synced automatically from our Notion database, giving you full transparency into what is currently being built and what has shipped.
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