client

Tech Tehran

An Android and Web application that works with Google Maps with offline storage and route functions connects Shippers, Brokers and Carriers together.

the organisation
O

Tehran Nasim has been providing a domestic and international transportation service in Iran for nearly 40 years. Headquartered in Tehran, they operate a full range of freight forwarding services and customs brokerage facilities in over 25 ports of entry and exit in Iran.

the challenge
C

Internet speed in Iran is limited in remote areas that makes tracking of the trucks very difficult. Data Gathering of route patterns for each category of fleet for optimisation needs to be done offline and transmitted to server when there is good internet connectivity. Here are a few example routes - A to B, A to B via C, A to B Time Charter, A to B via C time charter, A to B and B to A, A to B and B to A time charter, A to B via C and B to A via C, A to B via C and B to A via C time charter, time charter, fixed based on fixed sum/ variable distance.

A disruptive “Uber-like” platform for Freight Forward Company connecting Carriers, Shippers and Brokers via an App and a Web Platform

The solution has sealed Tehran Nasim to manage any company’s navigation chart virtually anywhere in the world. Our Technology combined with their 40+ years of experience compliments its global coverage and swiftness in their operations.

the solution
S

Shipper can request a specific type and quantity of Cargo to be shipped on a specific date between two points. Depending on Carrier availability, Shipping Rates and Reviews; the Shipper is notified of the options. The system creates a handshake between the two entities. A Broker can request on behalf of multiple Carriers with multiple points of pick up and drop.

The technology mix consisted of Google Suite Integration, Offline Tracking, Offline Data Synchronisation, Compression and Integration between providers, devices and central server. The bespoke algorithm for matching trucks with drivers with suppliers was state-of-the-art with machine learning.

The solution helped in Order fulfilment from 40% to 90%.
Manpower needed for fulfilling services reduced from 36 employees to 12 employees
Network of drivers grew from 2000 to 10,000 within 6 months
The product helped in a revenue growth of 40% within the 1st year of launch

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