A studio for vehicle product experiences, authored from a single brief — and a cabin that responds to who is in it.
A single authoritative graph: 11 Domains → 54 Features → 299 Product Functions → indexed Tech Functions. Search any term, the studio returns its parents and dependents.
Every PF inherits its lineage, status, and the team conversations that produced it. Every TF (TF-xxxxx) traces back to a Feature and a Domain. The library is the source of truth — not a brainstorming canvas.
A protocol, not a rule book — the depth at which each entity is allowed to live, and the dimensions along which it is allowed to stretch.
Reading depth — intent → scene → interaction → function → spec — sets which questions a team must answer to move on. Seven sensory dimensions and five system dimensions keep the language tight: nothing slips into "it depends".
Scene-Mode = f(User Intent, Situation Context, User State, Experience Goal). Three columns — Context & Scope, Scene Definition, Refine & Generate — compose against the Master Library, never outside its bounds.
Two dozen canonical Scene Modes seed the library — Morning Preparation, Commute, Arrival, Departure, Comfort Drive, Cinema, Gaming, Lock & Leave. Each Mode owns its scenes; scenes own their flowcharts; flowcharts ground every spec the studio emits.
A continuous feed of OTA releases, model launches, and competitive moves — auto-classified, summarised, and queryable against the Master Library.
"Did the new Xiaomi update ship a feature we have defined?" — the answer is one query away. AI Intelligent Analysis cross-references each item against the Feature catalog, surfacing gaps and overlaps in seconds, not weeks.
One click on a Feature emits campaign copy, persona prompts, and target-customer narratives — all grounded in the Master Library so the marketing language never drifts from engineering reality.
Define with intent. Build with confidence. Sell with the same vocabulary you built it with — no rebriefing the agency, no re-translating the spec.
For most of automotive history the cabin has assumed a single, average driver. The interesting question is not how to make the cabin smarter — it is how to make it humble enough to keep asking who, exactly, is in it.