A data pipeline that pulls your TMS, telematics, carrier and port feeds into one shipment record, and an operations dashboard that shows what is late, what it costs and why.
Pilot pricing from ₹15,000 per month. Built for shippers, 3PLs and fleets across India, the Gulf and the US.
Fleetora is a data pipeline and an operations dashboard for logistics teams in India, the Gulf and the US. It reads your TMS, warehouse and ERP systems, telematics, carrier and courier APIs, port and customs status and the spreadsheets in between, and joins them into one shipment record in a warehouse you own. The dashboard, the alerts and the AI layer all read that record, and every metric is shown with the definition that produced it.
Design targets and capacity, measured on demo data — not results from client deployments.
Feeds land raw, are cleaned and deduplicated, and are modelled into one shipment record with tests on every join, so a broken source fails loudly instead of quietly. The pipeline covers:
One screen for what is moving, what is late and what is about to be, filtered by region, lane, carrier or customer. The dashboard shows:
Built from the same events as the dashboard, so a carrier is scored on what actually happened and a delay is charged to whoever caused it. Analysis covers:
Shipments at risk, dwell above the lane norm and cost anomalies become rows in an exceptions queue, each with a reason and an owner. Alerting includes:
Fuel, tolls, driver time and carrier invoices joined to the trips they paid for, so cost is measured per lane and per shipment rather than per month. Cost analysis covers:
Emissions estimated per shipment and per lane from distance, mode and load, with the method printed beside every figure rather than buried in a footnote. Estimates cover:
Ask “which lanes from Jebel Ali slipped last week?” and get a table and a chart, with the query that produced them shown underneath so an analyst can check it.
Every AI feature in Fleetora reads the same published tables as the dashboard, shows the query or the reasons behind its answer, and leaves the decision with your team.
An operation already runs a TMS, an ERP and several telematics and carrier systems. Fleetora reads from them and writes to a warehouse you own, so nothing has to be migrated first.
Orders, loads, stock movements and proof of delivery from SAP, Oracle NetSuite and the TMS and WMS you run, read on a schedule or from exports.
The exceptions queue for their region, shipments at risk ranked by impact, and dwell at the hubs they run, refreshed through the shift.
Vehicle positions, driver hours and the loads due out next, with the shipments that need a rebooked slot marked first.
Cost per kilometre and per shipment, carrier invoices matched to the trips they bill, and detention charges that should not have been paid.
OTIF, utilisation and cost by region and customer, the weekly written summary, and the carriers and lanes that moved most.
Carrier scorecards built from events rather than impressions, with delays charged to whoever caused them, ready for a quarterly review.
A shared view of their own shipments and OTIF, with the same definitions your team uses, so service reviews start from one set of numbers.
Fleetora is built so that every number can be traced back to the feed that produced it, and so that the data stays in your account, in the region you choose.
Ownership
Tables live in your own Snowflake, BigQuery or Postgres account, in India, the UAE, Saudi Arabia or the US.
Modelling
Every transformation is code in a repository you can read, with tests on keys, freshness and accepted values.
Definitions
OTIF, dwell, utilisation, cost and CO₂ each have one written, versioned definition shown beside every figure.
Ingestion
Batch reads for ERP and TMS, event streams for telematics, and labelled freshness on every source.
Access
A regional manager, a carrier or a customer sees only their own rows, on the dashboard and in the AI answers.
Openness
The same published tables feed Power BI, Looker or a spreadsheet, so nobody is locked into one screen.
Six modules that assume a real logistics stack rather than a clean demo: messy carrier feeds, three time zones, two currencies and a metric definition someone will eventually dispute.
Scheduled and streaming ingestion from TMS, WMS and ERP, GPS and ELD telematics, carrier and courier APIs, port and customs status, and the spreadsheets nobody has replaced yet.
Feeds deduplicated, time zones normalised and IDs reconciled into one shipment record, modelled in dbt with tests on every join so a broken feed fails loudly instead of quietly.
OTIF, shipments at risk, dwell at hubs and ports, fleet utilisation and cost per kilometre, with lane, carrier and customer filters and an exceptions queue that has an owner per row.
Carrier scorecards built from the same events as the dashboard, lanes ranked by delay and cost, and the week-on-week change on each so a slipping lane is visible before the monthly review.
Plain-language questions answered from the warehouse with the query shown, delay prediction on open shipments, anomaly alerts on dwell and cost, and a written weekly summary.
Cost per kilometre and per shipment from fuel, tolls and carrier invoices, and CO₂ estimates per lane from distance, mode and load, with the method printed beside every figure.
Six things we built for operations, finance and data teams, from how a feed is joined to who owns the warehouse.
A dashboard on top of unjoined feeds shows three versions of the same shipment. Fleetora builds the record before it draws the chart.
Every metric is written down, versioned and shown beside the figure, so reviews argue about the operation rather than the arithmetic.
The warehouse is in your account and region. If you stop using Fleetora, the tables and the models stay with you.
E-way bills and FASTag in India, ports and border crossings in the Gulf, ELD and LTL carriers in the US, on one model.
Three to five sources and one region are enough to start, alongside the TMS and BI tools you already run.
One engineer connects the feeds, agrees the definitions with your team and stays with you through the pilot.
The core metrics a pilot starts with. Each has one written definition, a target refresh and a named source. Open any card to see how it is measured.
OTIF
On-time-in-full
Dwell
Dwell at hubs and ports
Utilisation
Fleet utilisation
Cost / km
Cost per kilometre
Carrier score
Carrier scorecard
CO₂
Emissions per shipment
We are a new team, and we would rather show than claim. We are taking a small number of pilot partners to turn our demo builds into measured, named results.
One process, one team, a written scope and a fixed end date before any work starts.
An evaluation report on your real cases: accuracy, escalation rate, speed and cost per task.
Below our standard rates, in return for honest feedback and a decision at the end.
Nothing is published without your written approval — not your name, not your numbers.
Client stories will appear here once pilots finish — real names, with permission.
What operations, finance and data teams ask before a pilot: systems, data ownership, messy carriers, prediction and price.
Still have a question?
Thirty minutes with an engineer who builds Fleetora pipelines. No deck, no discovery form.
No. Fleetora reads from the systems you already run and writes to a warehouse. If your team prefers Power BI or Looker, they can point it at the same published tables the Fleetora dashboard uses.
Tell us which systems you run, which lanes matter most and which numbers you report today. We come back with a walkthrough on a sample of your own data, not a generic demo.
Book a walkthrough
Thirty minutes on your lanes, your systems and the numbers you report today.
Connect a few sources
Three to five feeds and one region, landed in a warehouse in your own account.
Agree the definitions
OTIF, dwell and cost written down with your team before the dashboard goes live.
Extend region by region
Add sources, lanes and markets as each one is modelled, with a named lead throughout.
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