Logistics data analytic startup LogiNext confirms $10M Series A funding from Paytm, plans to expand to SE Asia


Logistics has always been looked at as a chaotic, fragmented, and unorganized function of any business. However, with the rise of e-commerce and on-demand delivery companies, businesses and consumers are demanding deliveries and supply chain to be more organized, agile, and transparent.

Mumbai-based LogiNext is solving the aforementioned inefficiency by leveraging big data. The company has just confirmed to YourStory that it has secured $10 million Series A from Alibaba-backed Paytm. Earlier in April this year, LogiNext had raised little over a half million USD seed round from Indian Angel Network.

LogiNext aggregates the location data consumed from multiple clients with similar delivery networks, anonymizes it and then uses this power of real ‘big data’ to generate insights that helps companies predict delays, save cost and provide reliable customer service.

Speaking about where proceedings will be deployed, Dhruvil Sanghvi, Co-founder and CEO of LogiNext, said, “We will use the funds for customer acquisition, marketing, product development, and hiring more talent.”

Currently, it’s serving close to 50 clients hailing from large to small enterprise. With this capital bolster, the company also plans to hire 60 employees over the next six months. “We don’t want to make mistakes like other growth stage startups while hiring. We will hire gradually and sensibly. LogiNext believes in stable hiring,” added Dhruvil.

LogiNext offers SaaS-based pricing for software. “We typically sell one license per asset. An asset could be a vehicle, a bag of shipments, a delivery boy, a biker or even an individual shipment/transaction,” outlined Dhruvil.

The back story

In late 2013, Dhruvil and Manisha Rai Singhani observed a huge surge in e-commerce, hyperlocal commerce, and Uber kind of services where a lot of startups and even large companies were jumping in but most of them were making losses because of very high logistics cost, uncertainties, and frequent delays.

That is when the duo decided to use their previous big data experience to build a product which most companies in this segment can utilize and cut down on their cost while providing the best customer experience.

What’s on the platter?

The company offers cloud-based solution for e-commerce and hyperlocal in five areas -- last mile delivery (Intra-City: All models including door-to-door, hub-to-door, hub and spoke), Line Haul Movement (Inter-city), ad-hoc reverse logistics and pick-ups and analyzing the delivery timings, distances, locations, and delay trend analytics.

“We are currently catering to nine models of hyper-local deliveries, including groceries, food, pet care, child-care, alcohol, medicine, home services, laundry, electronics, and apparel,” stated Manisha.

Team LogiNext

Road ahead

LogiNext also has plans for global expansion and will eye China, South East Asia, and the Middle East regions. “We will test these markets next year and it’s easier for us after Paytm fund infusion,” concluded Manisha.

YourStory’s take

According to some rough estimate, the market size of technology in logistics in India is roughly $2 billion and is much larger in other markets like South East Asia and the Middle East. Globally, companies like ORION software, OnFleet, Bringg, Infor, and JDA software and Elementum are established players.

Visibility of a shipment is a big headache for digital startups (e-commerce, hyperlocal, travel etc.) Traditionally, all the planning and optimization is done using static and stale information. However, LogiNext is disrupting the ‘reactive’ aspect of logistics to a more ‘pro-active, predictive and preventive’ way.

The investment makes a lot of sense for Paytm which has identified logistics after payment as a big pain in India. The Noida-based company had also invested $5 million in hyperlocal logistics and transportation startup Jugnoo. The investment will also help Paytm to streamline its logistics for marketplace and hyperlocal aggregation arm.