AI-driven automation of a tender evaluation process in the construction industry using a Large Language Model

Our client encountered substantial challenges with the volume and complexity of construction and project tenders they processed. Each tender required a detailed analysis of vision documents, each approximately fifty pages long, a task that was both time-consuming and prone to human error. These errors had the potential to result in costly legal challenges. 
 
Moreover, the company’s commitment to providing fixed price guarantees and flexible project management under their Risk-Bearing Project Management (RPM) model necessitated a rigorous scrutiny of each submission to meet their high standards for cost, quality, and timeline assurances. The need for an automated solution became evident to maintain their high-quality standards while enhancing operational efficiency and reducing overhead.

Bright Cape introduced a cutting-edge solution utilizing a Large Language Model (LLM) to streamline the evaluation of construction and project tenders. The LLM was specifically deployed to handle the intensive review of vision texts within the tenders, which was a major bottleneck in the evaluation process. 
 
The implementation involved fine-tuning the LLM with numerous examples of past tenders evaluated by human experts. This fine-tuning enabled the LLM to recognize and assess the quality of submissions accurately. Special attention was focused on empowering the LLM to identify and prioritize the top-tier submissions effectively. Moreover, the model was enhanced to provide detailed justifications for each assessment, increasing transparency and aiding our client in understanding the basis of the automated evaluations. 
 
This strategic automation was aimed at reducing the workload on employees, thereby allowing them to concentrate on more strategic aspects of tender management, which in turn could enhance the overall workflow and efficiency.

The adoption of Bright Cape’s AI solution brought transformative results to our client. The automation of the tender evaluation process cut the time employees spent on initial reviews in half. This optimization allowed staff to engage in higher-value activities, significantly boosting operational efficiency and reducing the likelihood of human errors. 
 
Economically, the implementation has been highly beneficial, with our client witnessing a significant reduction in operational costs related to tender evaluations. The faster processing times and reduced need for manual intervention have enabled the company to reallocate resources more effectively, improving both productivity and profitability. 
 
This case study exemplifies how Bright Cape’s innovative data solutions can substantially decrease costs and enhance operational efficiency, providing our clients with a competitive edge in their industry. Feel free to contact us to talk more about this application’s possibilities in your organization.