WilmerHale's in-house AI tool Finch streamlines complex litigation by converting depositions into structured summaries

In complex litigation matters, WilmerHale attorneys faced a compounding time burden: depositions in major cases can run hundreds of pages each, and large matters routinely involve dozens of witnesses. Manually reviewing transcripts, extracting key testimony, and cross-referencing statements across related documents consumed significant attorney hours that could otherwise be directed toward substantive legal work. In litigation practice, where the ability to quickly surface contradictions, establish timelines, and connect facts across witnesses directly affects case outcomes, this manual bottleneck imposed real strategic costs — slowing the path from raw testimony to usable legal argument.

WilmerHale built Finch, a proprietary in-house generative AI system developed specifically for complex litigation workflows rather than adapted from a general-purpose tool. Powered by large language models, Finch ingests full deposition transcripts and converts them into structured summaries and chronological timelines, surfacing connections across related documents that would otherwise require hours of manual cross-referencing. By building the system internally, the firm retained full control over design choices, enabling it to tailor the tool precisely to how litigators actually work — prioritizing the outputs attorneys need to construct legal arguments and draft persuasive briefs. The in-house development model also allowed WilmerHale to iterate based on direct practitioner feedback.

The Financial Times named WilmerHale a "Standout" firm in the Digital Tools category as part of its 2025 Innovative Lawyers report, which evaluates North American law firms on client-focused innovation and internal process transformation. The recognition specifically cited Finch, with high marks for originality, leadership, and impact. Qualitatively, attorneys report a meaningful shift in how they allocate time on complex matters:

• Deposition review shifts from manual extraction to structured, AI-generated summaries
• Lawyers redirect effort toward strategy, argument construction, and brief writing
• Partner Jeffrey Dennhardt noted "much more rapid advancement than we might have predicted a couple of years ago"

• Custom-built AI tools outperform generic solutions when the workflow is specialized — litigation has distinct structure and output requirements that off-the-shelf products rarely address well.
• Deposition transcript summarization is a high-ROI AI application: the input is predictably structured and the output directly accelerates billable strategy work.
• External recognition (e.g., FT Innovative Lawyers) signals that AI tooling is now a competitive differentiator in BigLaw, not just an internal efficiency play.
• Firms building proprietary systems retain the ability to iterate based on practitioner feedback, which is critical for adoption in high-stakes legal environments.