Local AI foundations
Stabilizing model lifecycles, permission boundaries, storage, and device-level runtime proof.
CurrentR2H plans in evidence-backed stages. Directions evolve as products, runtimes, and device validation reveal better paths.
This roadmap communicates focus, not guaranteed dates or release commitments.
Stabilizing model lifecycles, permission boundaries, storage, and device-level runtime proof.
CurrentTurning verified internal capability into dependable Android and desktop experiences.
Near termExploring reusable local knowledge infrastructure without merging product trust boundaries.
DirectionTesting private, resource-aware adaptation that stays explainable and reversible.
ResearchSelective local interoperability with explicit ownership and capability truth.
Long termR2H builds local-first intelligent systems designed to remain capable, private, inspectable, and useful without depending on remote infrastructure.