Case studies from firms that switched from manual records review to AI-augmented workflows.
We're launching named-firm case studies in Q3 2026. Pilot firms get featured (with permission) and receive 6 months free in exchange for sharing their results.
Each published case study will document a single firm's before-and-after switch to MedLegal AI — with real numbers, not vendor marketing language. Here's what every study will show:
Named firm (with permission), attorney + paralegal headcount, practice areas, typical case complexity.
How records review, chronology build, and expert prep worked before. Avg hours per case + dollar cost (LNC fees, attorney time).
Same metrics, after the switch. Specific tools used (timeline-builder, daubert-challenge, etc.) and how they replaced or augmented existing steps.
Dollars, hours, and cycle-time deltas. Per-case + annualized. Calculated from the firm's own data, not modeled estimates.
On-record statement from the lead attorney — what changed in their day-to-day, what they'd tell a peer firm considering the switch.
Case won, settlement amount, or time-to-resolution. Anonymized at the client level as needed; never fabricated, never modeled.
In the meantime, here's what good plaintiff-PI AI case studies look like — and where the industry-wide numbers currently sit.