ALBERO
Engineering ambitious products
Case study · Logistics · Hyderabad

Mid-market Logistics
Built a custom analytics platform replacing 6 dashboards. Surfaced ₹2.4 Cr/yr in route-optimization savings.

Built a custom DataPulse-powered platform aggregating GPS, fuel, dispatch, and customer data into a real-time ops console. Added AI route-optimization that learns from delivery patterns weekly.

₹2.4 Cr
Annual savings
−2 days
Decision lag
−17%
Empty returns
+12 pts
SLA adherence
The challenge

A 1,200-truck logistics company ran ops on 6 disconnected dashboards and Excel exports. Decisions lagged 2–3 days behind reality. Fuel waste from route inefficiency was an unmeasured ₹2+ Cr leak.

The solution

Built a custom DataPulse-powered platform aggregating GPS, fuel, dispatch, and customer data into a real-time ops console. Added AI route-optimization that learns from delivery patterns weekly.

Outcomes
  • Identified ₹2.4 Cr/yr fuel + idle savings in first 6 months
  • Dispatch decisions now made in real-time vs 2-day lag
  • 17% reduction in empty-return trips
  • Customer SLA adherence improved from 84% to 96%
Architecture

Straight answers

Mid-market Logistics — the details

What challenge did Mid-market Logistics face?

A 1,200-truck logistics company ran ops on 6 disconnected dashboards and Excel exports. Decisions lagged 2–3 days behind reality. Fuel waste from route inefficiency was an unmeasured ₹2+ Cr leak.

How did Albero Technologies solve it?

Built a custom DataPulse-powered platform aggregating GPS, fuel, dispatch, and customer data into a real-time ops console. Added AI route-optimization that learns from delivery patterns weekly.

What were the measurable results?

Identified ₹2.4 Cr/yr fuel + idle savings in first 6 months Dispatch decisions now made in real-time vs 2-day lag 17% reduction in empty-return trips Customer SLA adherence improved from 84% to 96%

What technology stack was used?

The solution was built with DataPulse, ClickHouse, Kafka, Python, AWS, Mapbox.

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