The Pattern team attended MTMP Fall 2025 last month, connecting with firms, partners, and platform builders both familiar and new. Across sessions and booth conversations, one topic kept surfacing: how firms manage the daily work of building complete, consistent case files. Our Chief Product Officer, James Nix, joined a panel on AI in legal workflows that focused on what firms are using today and where gaps still remain.
Across the docket, the operational pressure was hard to miss.
MTMP sessions made the operational challenge clear.
A recent Camp Lejeune mediation illustrated how documentation gaps continue to slow progress. Of twenty-five cases mediated, nine reached settlement, reflecting movement but not broad resolution. These were relatively low-value settlements, and leadership emphasized the need to differentiate case categories and prioritize disease groups such as kidney, bladder, and blood cancers. One of the biggest obstacles was incomplete documentation, including missing exposure records, incomplete diagnostics, and offset data related to VA benefits. A huge amount of time is being spent not on arguing law, but on coordinating efforts to build strong core datasets on injuries and damages to provide the court with unified, complete packages of information to better facilitate a global resolution.
In Hair Relaxer, presenters described a litigation still deep in discovery but already revealing the same operational challenges seen across other MDLs. Scientific research, including The Sister Study and related analyses, is strengthening the evidentiary foundation, while firms work to organize product usage data, medical records, and regulatory documentation across multiple defendants. The work remains complex, requiring alignment between scientific evidence and the documentation needed to advance toward bellwether trials.
The Social Media MDL illustrates how case scale and complexity can create their own bottlenecks. The litigation now spans both personal injury and school district claims, each advancing toward early bellwether trials. After more than a million documents produced and over one hundred depositions completed, teams are now coordinating expert discovery while tracking appeals that could reshape the definition of a “product.” With two parallel case tracks, hundreds of experts, and overlapping data sources, the challenge lies in maintaining consistent, verifiable records across an evolving evidentiary landscape.
During the AI panel, James Nix described a challenge we see often: the biggest quality gaps appear late in the process. Settlement readiness is usually when firms discover what is missing, and by that stage, corrections come with high cost and delay.
That experience is shifting priorities. Firms are still interested in speed, but what they truly need is visibility. They want systems that can scan their dockets early and highlight risks before they become roadblocks.
The most effective tools are now those that flag:
The focus has moved from faster review to earlier detection, from reacting to problems to preventing them through predictive quality.
Across sessions and side conversations, one theme kept coming up. Legal teams want confidence not only in outcomes but in the process that gets them there. They want operational trust, the assurance that every case is handled with accuracy and consistency from start to finish.
That means:
Achieving that level of trust takes more than technology. It requires structure, repeatable workflows, and clear accountability across teams. The firms gaining ground are the ones building disciplined systems around the everyday work that moves litigation forward.
That is the challenge we are focused on, and the problem Pattern Data is purpose-built to solve.