Global Life Sciences Organization Cuts DSAR Review Time by 50% Using Relativity aiR for Review

How did they do it?

• Replaced manual document-by-document DSAR review with AI-driven analysis
• Saved an average of 85 hours per request
• Extended the AI-powered process on a global scale to meet the needs of other European countries with strict statutory deadlines

The Challenge: Demanding Deadlines, Manual Burden

Teams that work on data subject access requests (DSARs) must find, validate, and produce responsive personal and patient data across multiple systems, often under strict one-month timelines. Those timelines can become even smaller, depending on when the team receives the request. With so much complex data involved, manual review often slows the entire process down. That was the case for a global life sciences organization – and the trigger to look for a modern AI solution.

The organization’s legal team relied on search terms to narrow the data sets, then manually reviewed the remaining documents one by one. Even after culling, analysts still had to open and assess each unique file. This workflow stretched turnaround times, added variability across DSAR projects, and made it harder to commit to tight deadlines with confidence.

The team needed a fast, consistent, and defensible approach. So, they turned to Relativity aiR for Review.

The Solution: An AI-Powered, Scalable Model for DSAR Projects

The team began with a DSAR matter involving nearly 5,000 documents. Instead of manually reviewing a narrowed document set, they leveraged aiR for Review to analyze content and surface relevant information, quickly and accurately.

To validate results, the privacy team conducted targeted sampling directly in RelativityOne and reviewed the aiR results report, which includes the AI‑generated ranking, rationale, and considerations. This allowed them to quickly navigate to the core, relevant content within each document through the aiR outputs, supporting efficient validation and confidence in the results.

Using Relativity’s DSAR Playbook, the team accelerated initial configuration, validation, and scaling and created a consistent, repeatable workflow. Within this framework, aiR analysis and prompts were used to identify the data subject’s personal data.

The Impact: Fast DSAR Turnaround, Higher Confidence

By leveraging aiR for Review for a DSAR project, the team:

• Completed personal data analysis in 2.5 days on average, compared to a 3-week manual timeline
• Reduced cost by avoiding extensive manual review
• Saved an average of 85 hours of review time per request
• Achieved 100% recall and 90% precision in identifying personal data
• Enabled consistent QC by capturing aiR’s outputs in structured custom fields
• Strengthened defensibility and auditability with AI-generated rankings and explanations, built directly into reporting

The team also found the prompting process straightforward, thanks to aiR for Review’s prompt kickstarter. The initial prompt performed strongly enough that no iterations were required, allowing the team to move quickly and apply the same approach to future DSAR matters.

"aiR for Review's prompt kickstarter produced a prompt that was already very accurate for a DSAR use case. We made only a very slight adjustment to further align, and after that refinement, the prompt required no further iterations."
eDiscovery expert, global life sciences company

After standardizing on aiR for Review for their DSAR workflow, the organization extended this process to meet the needs of other European countries with strict statutory deadline

Global implementation has enabled teams to better estimate DSAR completion times – enhancing planning, capacity management, and regional consistency. This streamlined workflow keeps the life sciences organization agile and responsive to evolving data privacy regulations.