How Balfour Beatty used Reveal to Optimize their Litigation Process, Reduce Costs, & Accelerate Speed to Valuable Insights

Problem Statement

Balfour Beatty frequently faces repetitive legal challenges, particularly in construction defect cases involving common issues like water intrusion, soil grading, foundation defects, and MEP (Mechanical, Electrical, and Plumbing) complications. Rather than approaching each case from scratch, the firm partnered with managed review providers to build custom AI classifiers specific to each defect type. These AI models are narrowly focused on the recurring legal issues Balfour Beatty encounters.

For example, with water intrusion cases, the team built and reused AI classifiers that have been trained to rapidly identify responsive documents across new datasets, ensuring a high threshold of accuracy. This accelerates the team’s production obligations and significantly reduces the document sets the trial teams must review, improving efficiency and ensuring highly relevant materials support the firm’s legal arguments. In short, Balfour Beatty has developed reusable, AI-driven templates that dramatically cut review time and costs case over case.

Key Challenges

• Large volumes of data have a negative impact on processing speed
• Multiple relevant issues must to be identified by defect type
• Review costs typically increase when ensuring a high level of accuracy

How Challenges Were Addressed

Reveal’s AI-driven managed review solutions were used to build narrowly focused custom AI classifiers for recurring legal issues like water intrusion. These classifiers rapidly identified responsive documents in new datasets, ensuring accuracy and minimizing the number of documents that needed to be manually reviewed by trial teams. This expedited the discovery process and enhanced the relevance of the materials provided to support legal arguments.Reveal’s AI-driven managed review solutions were used to build narrowly focused custom AI classifiers for recurring legal issues like water intrusion. These classifiers rapidly identified responsive documents in new datasets, ensuring accuracy and minimizing the number of documents that needed to be manually reviewed by trial teams. This expedited the discovery process and enhanced the relevance of the materials provided to support legal arguments.

The ROI Results of Using Reveal

By using Reveal, Balfour Beatty was able to significantly reduce the time and cost associated with document review. In addition to the efficiencies gained through AI- driven review, Balfour Beatty’s legal teams benefited from Reveal’s ability to quickly adapt and reuse these models for similar cases, making the process highly scalable and reducing the strain on resources. These benefits have allowed for continued savings in both time and costs across multiple legal proceedings.

• Reduction in review time & cost
• Created Highly Scalable review workflow with AI Models
• Reduced strain on resources