Small Enterprise speaks to Abhinav Chaudhary, the CEO of FERO, about the promises its technologies bring along to the regional logistics industry

Tell us about FERO.
FERO is an intelligent platform. There is a general misconception about intelligence. Usually, when a platform or technology is integrated seamlessly, it is deemed to be intelligent. This approach is an in-out approach. However, FERO explores technology dimensions as well, such as Artificial Intelligence, machine learning, computer vision, and natural language processing.

FERO has all the key ingredients of the framework platform. This includes the operational modules of the business, such as ordering, booking, answering to inquiries, contracts, invoicing, and the lifecycle tracking of any shipment by all the modes, like air, ocean, and road. We also have various AI subsets such as NLP, TIA (Transport Interactive Agent), which is available across the platform, on Google Assistant, Alexa, Cortona, and proprietary apps. This bridges these functional modules literally.

When was this project initiated?
We started conceptualising and developing FERO in 2018, and currently, the team strength is 20, which is spread across UAE and India. We also plan to build the team further in the coming months.

What is the USP of FERO, when compared to similar concepts on the market?
The USP of FERO is a two-pronged approach. The first one is NLP, which is powered by very powerful machine learning algorithms. These by default, assist humans in taking some decisions,  which are prone to faults and errors. TIA is one USP that we are proud of, and currently, no one across the globe has taken that approach.

The second aspect is the computer vision part. What we currently see is that the manual process of entry of data or the lifecycle of the shipment is prone to errors. So, the way we approach this problem is through computer vision, by making sure that the lifecycle and the actions that are completed such as loading of a truck, the building of a ULD, stuffing of a container, etc are done seamlessly. We are approaching these problems through computer vision and I think these are the very strong USPs which position us optimally for capturing the market very fast.

What sort of revenue models are you pursuing?
That essentially depends upon on how pro companies are towards the overall AI strategy. There are companies in the market, who, along with their business operations and marketing strategies, also have an AI strategy in place. For such companies, we are offering our subscription and our LPA (Logistics Process Automation) models, wherein we produce a customized solution according to their requirements. Of course, for those organizations, who have not adopted the AI strategy at the moment, we offer our fulfillment model.

How do you plan to onboard suppliers onto the platform?
We have a very close onboarding mechanism, wherein we handhold, train and even formulate the AI strategies through our LPA model. But mostly, this onboarding is done by TIA. This is where the power of AI actually shows, where a human has not required to handhold the companies for various jobs.