VINCI RITHMS: Automating TSL Queries

Machine Learning

Automation of queries in the TSL industry

Vinci Rithms is a software designed for the automatic analysis of tender queries using machine learning algorithms. The tool efficiently and automatically conducts in-depth analysis of tender queries received by companies in the transportation industry, as well as extracts parameters for further stages of the processes.

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Vinci Rithms
case study

Implementation details - project description


Tender queries received by freight companies are not structured, and each of them comes in a different format, which excludes automation. Larger freight companies analyze tens of thousands of such queries every month manually.


Da Vinci Studio has developed a tool that, using machine learning, will recognize key elements necessary for preparing a quotation. By integrating with the client's quotation system, it will automatically generate responses to customers, fully automating the quotation process. As a result of our work, a proprietary algorithm was created, and extensive efforts were made in selecting, configuring, and integrating several other algorithms. Together, they enable us to deliver a high-performance tool to the market.


Vinci Rithms offers the ability to analyze queries formulated in any form and generate an immediate response. This provides a concrete optimization of the process for customers in terms of time and cost. Additionally, there is the possibility of integration with other customer channels, such as chatbots, voicebots, and forms. Currently, there is no direct competition for the proposed solution on the market.

Used technologies



Our fund is keen to support projects in the area of machine learning and artificial intelligence. They have incredible growth potential, so we are happy to support Da Vinci Studio in realizing their vision. We believe that Vinci Rithms will be a breakthrough, thus providing new opportunities for companies in the transportation industry to build a market advantage.

Szymon Janiak, Managing Director, Czysta3VC 4.9

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