History as system state
Symptoms, observations, decoded evidence, repairs, outcomes, and learned baselines stay associated with the specific vehicle over time.
KRAI is being built as an aftermarket, vehicle-independent intelligence layer—not a generic chatbot attached to live OBD data.
Symptoms, observations, decoded evidence, repairs, outcomes, and learned baselines stay associated with the specific vehicle over time.
Diagnostic hypotheses should remain traceable to the evidence and transformations that produced them, with uncertainty kept visible.
A repair is not treated as the end of the story. KRAI's target loop compares what happened afterward and updates the vehicle baseline.
The active engineering priority is making this longitudinal case reproducible before expanding KRAI's feature surface.
Development diagnostic interfaces are read-only today; no public vehicle-control features are offered while evidence handling and diagnostic reasoning are validated.
Any future vehicle interaction must pass deterministic capability, authorization, safety, and audit boundaries separate from conversational personality.
Future action paths are intended to require explicit capability checks, independent confirmation where appropriate, watchdogs, and auditable execution.
KRAI development prioritizes keeping important vehicle history and core reasoning close to the user where practical. This is an architectural direction, not a claim that every planned capability is already fully offline.
If your work intersects diagnostics, vehicle data, embedded AI, security, service operations, or aftermarket tooling, Kilzar welcomes a technical conversation.