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Aurene.

Logistics

Real-time visibility across the supply chain

Designed a streaming data platform giving operations teams live shipment tracking and forecasting.

-90%
Reporting latency
4 mo
End to end
Real-time
Shipment visibility

The challenge

Operations ran on overnight batch reports. By the time a delay surfaced, it was already a customer problem, and forecasting was guesswork built on stale data.

  • Operations ran on overnight batch reports
  • Delays surfaced only after they became customer problems
  • Forecasting was guesswork built on stale data

Our approach

We designed a streaming platform to ingest events in real time, modeled the data for both live dashboards and forecasting, and put governance and quality checks in place so teams could trust what they saw.

  • Designed real-time streaming ingestion for live events
  • Modeled the data for both dashboards and forecasting
  • Added governance and quality checks teams could trust

The outcome

Reporting latency dropped by 90%, operations could act on delays as they happened, and forecasting accuracy improved enough to change how the team planned capacity.

  • Reporting latency down 90%
  • Operations act on delays as they happen
  • Capacity planning moved from guesswork to data

How it works

The path a request takes through the system.

  1. 1IoT & events
  2. 2Kafka stream
  3. 3Processing
  4. 4Warehouse
  5. 5Live dashboards

Results

  • Reporting latency down 90%
  • Live shipment tracking for operations
  • Forecast accuracy materially improved
  • Capacity planning moved from guesswork to data

What we delivered

Real-time streaming ingestion
Governed data models with dbt
Live operations dashboards
Forecasting service and alerts

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