How a connected-vehicle AI feature can move from a 200-car pilot fleet to a governed, multi-market production rollout
A European OEM or tier-1 context with a connected-vehicle platform, pilot-scale telemetry and an unresolved path through OTA delivery, fleet operations and market-specific constraints.
Size: Representative: a European OEM or tier-1 with a connected-vehicle platform
A driver-behaviour AI feature performs well on a pilot fleet, but the path to a multi-market production rollout — OTA delivery, type-approval constraints, back-end scale — is undefined.
An indicative starting point: a feature validated on ~200 vehicles that must scale to hundreds of thousands, across markets with different connectivity and regulatory profiles
Model updates delivered ad hoc to the pilot fleet; production requires signed, staged OTA campaigns with rollback
Cloud inference acceptable in the pilot; production latency and data-sovereignty budgets would push inference into the vehicle or to the edge
UNECE R155/R156 software-update and cybersecurity management obligations not yet mapped to the ML lifecycle
Telemetry pipeline sized for a pilot fleet, not for fleet-wide event volumes with lawful consent handling under GDPR
No explicit acceptance criteria for what 'ready for rollout' means — the decision would currently be taken on demo impressions
A representative engagement would deliver a production architecture for the feature — an in-vehicle inference budget, signed OTA model delivery, fleet observability — and a rollout plan gated by explicit acceptance criteria.
Readiness review first, then production architecture, staged hardening, and transfer to the OEM's team — each phase gated, nothing obliges continuation.
The pilot assessed across architecture, data, integration, reliability and governance — producing the prioritised blocker map and the rollout decision basis.
Weeks 1–2In-vehicle/edge inference split against the latency and sovereignty budget; signed OTA model-delivery pipeline aligned to R155/R156 processes; telemetry consent architecture.
Weeks 3–6Shadow-mode validation on the pilot fleet, market-by-market rollout gates, automated rollback criteria written down before the first campaign.
Weeks 7–10Fleet dashboards, drift monitoring and campaign runbooks handed to the OEM's engineering organisation.
Weeks 11–12The intended outcome is a staged rollout behind explicit proceed, hold and rollback gates for each market, with the OEM team operating the system.
Every engagement starts with a 30-minute diagnosis. Describe your situation, and I will tell you — honestly — whether I can help and how fast.