Thanks to state-of-the-art technology, this startup can cut transport costs by at least 7%.
You can read this article in 6 minutes
In order for a company to deserve the name of a start-up, it must be very innovative. The list of start-ups has been growing fast in recent years. Including those that operate in logistics and transport. TNX Logistics specializes in facilitating cooperation between supply chain actors using modern tools.
Transport is not only a major cost for operators but also often a problem. The way it is carried out largely influences the profitability of the logistics provider. Process participants admit that the execution of orders, both as a whole and in individual elements, is still often based more on intuition than on specialist knowledge. Technology, and in particular artificial intelligence, is about to change that.
TNX Logistics is a start-up founded in 2016 (operations were launched in 2017) by Alex Hoffmann, Josh Bryan and Jonah McIntire. It has customers in the USA, Europe and New Zealand. The creators of the start-up have combined their expertise in the supply chain, machine learning and financial markets. As a ‘pilot market’ they chose New Zealand, and soon afterwards, in addition to the Auckland headquarters, they opened a branch in Berlin. According to Crunchbase, Berlin is now the central base. TNX Logistics has also an office in Chicago.
TNX Logistics is a road transport contracting platform
The first experiences of companies using the solution indicate that it allows reducing transport expenses by at least 7%. It also virtually eliminates traditional invoice processing. In order to achieve such results, artificial intelligence was used.
Start-up customers are significant suppliers and buyers of road transport services: brokers, 4PL (logistics process integrators) or forwarders. They are the ones who spend tens and hundreds of millions on road transport every year, using different carriers and rates.
The creators of the start-up emphasize that TNX is not TMS, so it does not duplicate the errors that, as it happens, may result from poor data quality.
However, the application of the system requires profound changes in the way service providers are sought and reached. Smart procurement is at the heart of how procurement expenditure can be reduced and an example of how artificial intelligence can be applied in practice. The platform uses various tendering strategies that can be applied to daily orders. The strategies cover all elements of the tender, from the initial offer to the last moment when the offer can still be submitted, and include, for example, ways of responding to rejections.
TNX creates strategies both automatically through machine learning and manually with the help of experts. The platform selects in real-time, one of the ways that can be used in the given conditions for a specific cargo. Strategies are assessed primarily in terms of financial effectiveness, but also in terms of the speed of matching. The tendering process is driven by a number of artificial intelligence elements. This includes, for example, the possibility of grouping loads, market price estimates and tendering strategies. All of this is presented to the carriers.
After the order is accepted by the operator, the process is analyzed in terms of a specific job. It determines what else has to be done before the transaction is finalized. This includes, for example, answers to questions such as: is delivery confirmation necessary, should delivery notes be signed, should the carrier provide a copy of temperature readings? When a carrier completes its tasks, the platform generates invoices and distributes them. The automated process saves money on traditional workflows.
Chad Prevost in the material for Freight Wave defines TNX as an optimization and communication tool for external logistics companies and freight forwarders. Cloud-based technology is designed to help staff access a variety of possible transport options to find the most appropriate one for their situation. Many types of cargo are handled, in some cases, the key is low price, in others the safety of transporting particularly valuable goods.
In his interview for FreightWaves, Alex Hoffmann emphasizes that the key mission of the start-up is to solve problems of logistics companies, especially those carrying out road transport tasks. This involves transport planning, route mapping, arranging loading, etc.
Jonah McIntire points out that everything must be managed by specialist software. It is it that performs traditional transport planning, taking all available solution options. It also uses machine learning, which can aid in eliminating deficiencies in TMS software. On the one hand, there is TMS (cloud was ignored by TMS) and on the other hand, there is artificial intelligence. “Until now, there has been no way to combine these two things. Now, it is happening,” comment the creators of the start-up.