Case Study
Physician Life Care Planning needed to give law firms a defensible projection of lifetime medical costs before those firms committed years of capital to a catastrophic injury case. Over six months, Roko Labs built Range Finder. This AI system places every new subject into a high-dimensional clinical vector space and returns a peer-matched cost projection grounded in real historical outcomes.

Industry
Project Duration
The Challenge
Plaintiff law firms decide whether to take a catastrophic injury case before they know what the long-term medical care will cost. The cases run for years and the numbers are large, so a wrong call is expensive in both directions.
Three pressures converge at intake:
Volume of evidence. A spinal cord or traumatic brain injury file can run thousands of pages of records, expert reports, and historical settlements, none of it queryable at intake speed.
Capital at risk. A case with limited recovery will burn years of funding before that becomes obvious.
Noisy estimation. Conventional projections rely on expert judgment and small comparable sets. Hard to reproduce, harder to defend, easy to attack in deposition.
Two senior partners read the same file and reach different conclusions, with no shared framework underneath the disagreement.
The Vision
The brief was specific. Build a system that takes a new injury profile and returns a defensible projected cost range, grounded in genuinely comparable historical cases, fast enough to be useful at intake.
That meant three things in practice:
Every historical case had to live inside a single analytical space, not a folder of PDFs.
A new subject had to be placed into that space using the same diagnostic and clinical features as the historical cohort, not surface-level demographics.
The output had to be transparent. A partner had to be able to look at the underlying peer set and see why the projection came out where it did.
Range Finder had to give law firms an answer at intake that they would still defend at trial.
End-to-End Pipeline
The Range FInder
Customer Outcomes



