FRP Advisory Turned Data Overload into £415K in Savings with Relativity aiR for Review

How did they do it?

• Reduced 1.7 million documents to approximately 100,000 through structured culling and aiR-driven analysis
• Curated targeted prompts to surface financial-related materials and automatically categorise them across seven key issue areas
• Prioritised a focused, issue-based review approach – without compromising quality or accuracy
• Accelerated insight and delivered £415K in total cost savings while meeting strict investigative deadlines

The Challenge: Managing Significant Scale Under a Strict Deadline

FRP Advisory – a Relativity partner specialising in restructuring, forensics, corporate finance and advisory services – was appointed on a complex restructuring investigation with a tight timeline. The matter involved over 750GB of data from 11 custodians – totalling to more than 1.7 million documents in need of key issues review.

Typically, FRP relied on traditional human review – amplified by technology-assisted review through machine learning models – as well as legal review teams provided by their legal advisors. While effective in smaller matters, this approach would have been slow, resource-intensive, and prohibitively expensive at such scale. Timeframes were stretched, and with statutory deadlines in play, completing the review through their usual processes alone would have been unfeasible without substantial increases in cost and resourcing.

The team needed a way to quickly reduce scope, surface key financial materials early, and structure the investigation around defined issue areas from the outset.

The Approach: Strategic Reduction and aiR Analysis

Working with Relativity’s product consultants, FRP implemented a structured and repeatable sequence:

The Impact: Measurable Efficiency Gains and Savings

Overall performance can be summarised in four data points:

• 1.7+ million documents at project start
• ~100,000 documents remaining after targeted reduction
• Seven clearly defined issue categories pertinent to the investigation
• ~£415,000 in total estimated cost savings

The savings, garnered from both the reduced review population and the rapid and strategic categorisation of material, included:

• £375,000 saved on first-pass review (approximately 90% savings versus traditional human-led review)
• £40,000 saved on second-pass review (approximately 50% savings due to improved relevance in the refined data set)

These results were achieved without compromising quality or accuracy, and with delivery completed on time under strict investigative deadlines.

Why It Matters: A Scalable, Repeatable Model

The issue-based categorisation aligned documents to important financial themes from the outset. Rather than treating the data as one undifferentiated mass:

• Focused sets were assembled by topic
• Parallel review tracks progressed simultaneously
• Specialists worked within clearly defined subject areas and queues
• Reporting aligned directly to the investigation’s key financial questions

Since this initial matter, FRP has utilised aiR for Review on several further cases and achieved similar levels of cost savings and accuracy. For example, they’ve leveraged aiR for Review in DSAR projects to reduce average response times from 30 days to 20.

Relativity aiR for Review was not a one-off success for the FRP team – it gave them a scalable, repeatable approach that could be adopted consistently across their business.

“Relativity aiR for Review amplifies the expertise and judgement of our skilled investigators across investigations, disputes, and high-volume document reviews. On this project, the efficiency gains and reduction in review effort were immediate, helping our team reach defensible insights faster without compromising quality. Those savings created momentum internally, and we are now scaling aiR across the business as a core part of how we approach intelligence gathering on complex matters.”
Harry Trick, Director, FRP Advisory