A major company operating in the design and construction of large industrial plants needs to improve efficiency in preparing quotations and the accuracy of estimates for highly complex projects. Although manual preparation of quotations relies on the experience of technicians, it still requires a significant investment of time and resources. Optimising quotation management is therefore a strategic necessity, both to reduce processing times and to improve the accuracy of estimates for materials and resources required for projects.
At Moxoff, we have developed a mathematical estimator, a system that automates the forecasting of quantities and costs of materials required for the construction of large-scale plants, by leveraging Machine Learning models. This solution allows integration of the company's historical data with the expertise of the designers, generating precise estimates in significantly reduced timescales. Furthermore, the system offers operators the ability to review and optimise the estimates step by step, so that they accurately reflect the real needs of the project.
