NavAlgo startup – see how technology eliminates bottlenecks in logistics

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NavAlgo startup – see how technology eliminates bottlenecks in logistics

The list of innovative companies – that is startups – which operate in logistics and transport is growing. NavAlgo specializes in the optimization of flows and processes using state-of-the-art IT tools.

NavAlgo is a two-year-old startup from the R&D sector (research and development; scientific or technical activity building bridges between science and industry). It creates integrated solutions for intelligent resource allocation in logistics. It provides algorithms and develops internal artificial intelligence to optimize logistics business operations.

The solutions are addressed to many parts of the supply chain. In retail, they forecast demand and help automatically and dynamically optimize purchasing and distribution to achieve the desired level of sales. In transport, they help to forecast the ETA (estimated/expected time of arrival) and therefore the delivery time for shipments, improving process transparency and supply chain predictability. In distribution, NavAlgo helps companies to optimize their routes in order to reduce operating time on the one hand, and on the other hand, reduce fuel consumption and carbon emissions.

In practice, NavAlgo, therefore, aims to create solutions tailored to the needs of intelligent resource allocation in logistics. It creates methods for overall demand forecasting, navigation, flow planning and inventory management. It supports the company’s operations regardless of whether it introduces a new solution, optimizes an existing process or product, or enters a completely new market area. The process covers all stages from concept to ongoing maintenance. It also helps to attract experts who, after proper training, will be able to implement and develop a given project in the future.

The creators of the startup emphasize that the solutions are tailor-made and their final shape depends on customers’ preferences. In the first step, it is necessary to identify the customer’s needs and areas of potential development. It is on this basis that the task can be precisely defined, obviously taking into account specific industry and business conditions. Interdisciplinary experts, including active researchers, select the most appropriate data and propose the approaches best suited to the needs of a specific user.

We try to make our solutions simple and functional, knowing from experience that it pays off. Functional and structural quality is what counts here. Particular attention is paid to every ‘small decision’, from business logic to the implementation of the source code,” emphasize NavAlgo experts.

Everything is done in stages. Programmers, accompanied by a team of experts, implement the solution. They build the final product or its prototype. Among the tools that NavAlgo uses to solve a specific problem is thorough data analysis. Whether it’s about understanding the nuances of a specific supply chain, optimizing logistics or ensuring adequate infrastructure security, specially developed algorithms prove to be helpful.

Appropriate models are therefore developed to describe possible future scenarios. To perform predictive modelling (predictive analytics means using statistical data and algorithms to determine the probability of future results on the basis of this historical information), analyses of real data, as well as random variables (stochastic processes), are necessary. Startup specialists are able to perform this kind of analysis of data specific to logistics. In fact, it is a real transformation of the industry from human decision-making to data-based decision-making. And there are plenty of them.

The ultimate goal is to eliminate performance bottlenecks

This is helped by the use of operational research, but also… distributed processing. “We believe that we need to go beyond platform-focused systems towards a conscious logic of real-time information flows and causal relationships,” emphasize experts from NavAlgo.

The solutions are implemented in the user’s preferred environment. They make the most of the already existing data, in a way ‘verifying’ those uncertain or fragmented, and also eliminating the erroneous or missing ones.

Photo: Trans.INFO

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