Shipsy: Employing Big Data to Boost Logistics and Supply Chain Efficiency

Although relatively an untapped asset, Big Data is gradually emerging as a key instrument of change in the world of business. It is compelling companies to trade gut-feelings with accurate data driven insights to device smarter strategies, and achieve effective decision making.

This wealth of information has much to offer to an array of segments. Logistics being one of them, can reap a good deal by employing these sophisticated data analytics to transform itself from a traditionally fragmented sector to a more organized, consolidated and transparent one. Here’s a startup that has identified this opportunity, and holds an ambition to disrupt supply chain in India with the help of Big Data.

Shipsy teamFounded in June 2015, Shipsy is the brainchild of Soham Chokshi, Dhruv Agrawal, Maharshi Devraj and Himanshu Gupta. Driven by a team of computer scientists and electrical engineers from IIT Madras and IIT Delhi, the startup aims to create platforms for data driven decision making with the current vision of bringing visibility and operational efficiency to the Supply Chain industry.


Recalling the conception of this idea and inception of Shipsy, Soham maintained, “ Shipsy started off by solving problems around visibility and convenience in the logistics space. We soon realized that fundamental problem and value was lesser in physically picking and delivering parcels, but more in creating a platform that enables data driven decision making for companies in the Supply Chain industry. Having worked with big data at our previous companies like Deutsche Bank and Samsung Research, we could identify that the issue of not being able to use the ambient data in an enterprise to gain business insights was fundamental and persistent across organizations. That’s where we wanted to carve our niche”.

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What does Shipsy do?

Although most of the paying clients Shipsy has, are in the Supply Chain industry, the platform is generic and agile enough to sit on top of any company’s database collection, and using machine intelligence, explore all of a company’s databases, thereby  providing a single view across all of the systems.

Specific to the logistics industry, Shipsy addresses problems related to location intelligence, last mile delivery optimization and supply chain planning. The work done is divided into three broad categories:

ShipsyArchitecture Design for Business Intelligence

Create a business architecture that ensures a truly digital way of doing business. Maximize the value of all technology investments by ensuring all systems talk to each other and leverage business synergies. Visualize all future big data stack requirements to get a competitive business edge in a cost efficient manner.

Intelligent Systems for Critical Business Processes

Build systems with open APIs to allow communication between businesses and leverage missing synergies. Ensure robustness for these systems that are involved in critical processes of your business. Above and beyond automation of process, incorporate machine level intelligence that allows superior decision making compared to humans.

Analytics Platform for Actionable Insights

Getting the architecture and intelligent systems in place means a steady source of high quality ambient business data. Leverage all this data by using our analytics platform to generate actionable business insights. Increase your revenues, enter new business models, optimize current processes and increase customer engagement.

Business & Monetization Model

Shipsy works closely with enterprises and helps them with their digital transformation needs. This happens by extending services as described above. In terms of monetization, the company charges an upfront fee for the front end customization of its generic backend infrastructure. Along with this, there is a license based fee on a per unit basis for the products being used by these companies.

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Currently, the company is working with 10 enterprises.

Funding Status

The company raised Series A in April 2016.

Scope and Future Plans

Elaborating on the scope in this segment, Dhruv said, “With a surge in the number of sensors and available data in an organization, we see the need for using this data to make actionable business decisions as paramount. With very few players in this segments, we see the big data landscape as nascent in India, and wish to be industry leaders as the segment evolves”.


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