Automotive & Mobility

Connected experiences and intelligent operations.

Connected vehicle services, manufacturing analytics, fleet operations and the engineering data that connects them.

How this sector runs

Where the work starts, and where it is decided

Every sector has a different shape. The node in gold is the decision the whole flow turns on — it is rarely in the same place twice.

The product keeps reporting after it ships. What comes back from the field is an input to the next revision, which makes the loop the architecture.

Sector pressures

These are the constraints we most often find when we start work in this sector.

Software-defined vehicles
Value migrating from mechanical engineering to software, requiring capabilities the industry did not traditionally need.
Connected services
Vehicles as a digital touchpoint, with the platform and data obligations that follow.
Manufacturing complexity
Variant proliferation and supply volatility straining production planning.
Engineering data volume
Design, simulation and test data at a scale that constrains iteration speed.
Fleet and aftersales
Service and fleet operations expected to be predictive rather than reactive.

Use cases

Connected vehicle services
Telemetry ingestion, service delivery and over-the-air update infrastructure.
Manufacturing analytics
Quality and throughput analysis across production data.
Fleet operations
Utilization, condition and predictive maintenance across a vehicle fleet.
Engineering data management
Product data connected across design, simulation, manufacturing and service.
Aftersales digital experience
Service booking, history and parts availability.

Every connection below is recorded in the content itself, and each one says why it is here.

Open the guided finder with this sector already selected. Four questions, and an explanation of why each capability came up.

Start from a goal

Questions

What does a connected vehicle platform need to handle?: High-volume telemetry ingestion, per-vehicle identity and security, over-the-air update with staged rollout and rollback, data residency across jurisdictions, and a long support lifetime — vehicles remain in service far longer than typical consumer devices, which makes update path longevity a first-order architectural constraint.
How is automotive engineering data different from other product data?: Volume and regulatory retention. Simulation and test data run to petabytes, and homologation and safety records must be retained and retrievable for very long periods. Storage tiering and lineage matter more than in most product data environments.

Tell us what you are trying to change and we will connect you with people who have worked on that specific problem.