// logistics & mobility

Operations analytics across every city.

Fleet utilisation, delivery SLAs, city-level ops and cost per order — from vehicle telemetry, order systems and field apps, modelled once on your own warehouse. Sprinkle is how Yulu runs data for teams across five cities.

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// trusted by Yulu Swiggy
// the metrics that matter
// fleet
Utilisation, idle time, availability and maintenance downtime per asset
// service
On-time delivery, SLA breaches and time-to-fulfil by hub and route
// city ops
Demand vs supply by zone, rebalancing and hub throughput
// cost
Cost per order, per km and per trip; fuel, energy and rider payouts
// the questions

The questions city heads ask every morning.

Why did on-time delivery in Hyderabad fall below 92% yesterday?
Which hubs have vehicles sitting idle while demand goes unserved nearby?
What is driving the rise in cost per order in the Pune zone?
Which routes are consistently breaching SLA — and since when?

Ops teams ask in plain English. The Analyst Agent works off your Domain Model, investigates what changed, and shows the SQL behind every answer.

See the Analyst Agent

// pipelines

Telemetry, orders and field data in one model.

Operations data lives in a dozen systems — vehicle IoT, order management, rider apps, maintenance logs, payments. Sprinkle ingests them all and lets your team build the models in days, not quarters.

  • Ingestion from databases, event streams, files and SaaS apps
  • Transformations the agent builds, tests and schedules
  • Models that took weeks in Spark, done in a fraction of the time
  • Delivery to dashboards, Slack and email on a schedule
// scale

Warehouse-native. No second copy.

High-frequency telemetry and order events queried directly on your own warehouse. Nothing is extracted into a vendor silo, and geo-level access is enforced by row.

Your warehouse
Snowflake, BigQuery, Redshift, Databricks or Postgres — in your account.
Row-level security
City and hub teams see only their own geography, from one shared model.
// customer

Actual development time for models, reports, flows and dashboards has come down to just 1–2 days. Time to deliver has become quite fast. Setting up a new ingestion job is just a matter of minutes with Sprinkle.

Jaideep Dhok
Head of Data Engineering · Yulu
Yulu

How Yulu enables teams across five cities with data

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Swiggy

How Swiggy runs thousands of analyses a month on hyperlocal ops

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