Routle.ai Methodology

Routle.ai does not depend on individual carrier offers. It uses averaged and reconstructed parameters of cost, time and infrastructure performance across countries. This gives logistics professionals a flexible tool for building and rebuilding multimodal routes without being limited to linear paths or single-provider options.

Yes, you've heard us. Routle is a proper 'helicopter view' solution for your logistics arsenal. We will not provide you with the rates from the 'usual suspects.' We believe that we fill the gap in the toolbox of every logistics professional. By deriving our methodology from macroeconomic analysis and decades of transportation geography theory, we are able to get you a key service to support high stakes decisions.

As a result, users can explore the fastest or cheapest variants, set required ports or borders, avoid certain countries and design circular or triangular routes that improve asset utilisation. Routle.ai supports this process by revealing many routing possibilities instead of just one. It helps teams discover better routes, test new corridor ideas and work with greater freedom, alternative choices and creative control over how cargo moves.

Routle.ai works similarly to familiar maps services that allow users to build passenger routes from home to work or between cities – but for cargo. Routle.ai builds routes using a global transport-network map, in which every segment contains aggregated and averaged data on transport speed and cost.

Routes are constructed between major cities and regions and do not include last-mile delivery.

A similar set of route types can be generated for containerised cargo, bulk, and liquid bulk, depending on the product. If a user changes anything in the query, e.g. avoiding countries or routing via selected transport nodes, all these routes will consider these changes.

Time-and-cost optimal routes are based on an assessment of inventory costs. The more expensive the product, the higher the contribution of delivery time to the optimal route choice. A user may enter the product value manually or leave the field blank. In that case, the system will use an average product value for the given origin and destination.

During routing, we account for a variety of constraints, for example, closed borders between certain countries or restrictions on specific cargo types. Information on softer or contextual constraints along the route can be provided by our AI-agent, Sinbad. We update our data regularly and also introduce adjustments in response to rapid changes in tariffs or new long-term transport restrictions.

Routle.ai is designed for full global coverage, including regions where publicly available data is scarce or fragmented. Limited data availability does not impede modelling: through controlled estimation techniques, cross-source validation, and AI-assisted reconstruction, the platform ensures that even data-poor geographies are represented with coherent, high-quality parameters suitable for routing, benchmarking and strategic scenario analysis.

This results in a coherent, continuously updated global dataset that underpins all routing and modelling outputs.

Routle.ai's modelling framework is supported by Sinbad, our AI agent designed specifically for multimodal transport analytics.