Taxi & mobility
A national taxi-fleet operator runs the operating layer behind a large share of the country's taxi fleet. That is three product lines spanning driver settlement, dispatch and B2B booking, and the data and processes that drive them had outgrown a one-team setup. Rather than fragmenting work across more developers, Foundry helped re-shape the organisation to be AI-leveraged: a Foundry-team Linear footprint, an agent-ready bridge into their existing stack, and Claude put into the hands of the people closest to operations.
- One-team ceiling
A national taxi-fleet operator runs three product lines: driver settlement, dispatch, B2B booking. The data and processes behind them had outgrown a one-team setup.
- Headcount would have fragmented
The obvious move was hiring more developers. That fragments the work without addressing why a single team had become the bottleneck.
- Reshaped as AI-leveraged org
Foundry instead reshaped the organisation to be AI-leveraged: a Foundry-team Linear footprint, an agent-ready bridge into the existing stack, and Claude in the hands of the people closest to operations.
- Driver dashboard live, rolling out
The first concrete output is a driver dashboard turning Databricks-resident ride and earnings data into a per-driver view of how the night went. The pattern is rolling out across the group.
More cases. More proof.
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