A demand letter is more than a formality. It is your first (and sometimes only) chance to set the anchor, control the narrative, and signal trial readiness. Small drafting errors can quietly shave thousands off a case by weakening credibility, inviting lowball counters, or creating “easy outs” for the adjuster.
A strong demand letter can move a claim toward settlement quickly, but a rushed demand letter draft can also lock you into bad numbers, misstated facts, or an avoidable credibility hit. This one page checklist is designed for the final pass, the 10 to 15 minutes before you hit send.
Using AI in litigation support can be a genuine force multiplier, but it also changes your risk profile. For law firms and AI to work well together, you need workflows that preserve privilege, protect private information, and create a defensible process your team can repeat case after case. Why privilege
AI is now table stakes in litigation, but “law firms AI” can mean everything from a general chatbot to a workflow that turns a document pile into case-ready work product. If you are buying for a litigation team, the goal is not novelty, it is defensible speed: faster drafting and
Courts are making it clear that “AI drafted” does not mean “AI excused.” If you file a brief, demand letter, or discovery response with incorrect citations or invented quotes, the responsibility is still yours. The widely cited sanctions in Mata v. Avianca (S.D.N.Y. 2023) were not about
Exhibit chaos is one of the fastest ways to lose time (and credibility) at trial. The goal of trial support is simple: any document, photo, or record should be findable in seconds, by anyone on the team, under pressure. This guide lays out a practical, courtroom-tested system to organize exhibits
If your firm is experimenting with generative AI, you are not alone. But the real differentiator for law firms using AI is not who has the newest tool, it is who has the policies and controls that prevent bad outputs from reaching a client, a carrier, or a court. Bad
When deadlines compress and fact patterns sprawl, litigation research often breaks down in the same predictable way: you start from scratch, chase the same sources, and still worry you missed something controlling. A repeatable source list fixes that. It gives you a vetted, jurisdiction-aware set of places to look first,
Missed details in legal intakes rarely come from “carelessness.” They come from predictable pressure: a client who is stressed, a caller who talks in circles, interruptions at the front desk, and different staff members asking different questions each time. A simple, repeatable script solves most of this. It creates consistency,
Verdict research is one of the fastest ways to sanity-check case value, pressure-test your theme, and anticipate what a neutral decision-maker has actually done in similar fact patterns. The challenge is that “similar” is rarely obvious, and digging through outcomes can quickly turn into a time sink. Below is a
Most firms start evaluating litigation support companies for one reason: time. When deadlines stack up, the real question is not “Who has AI?” It is “Who reliably turns our documents into work product we can file, negotiate with, or take to deposition, without creating new risk?” Below is a practical,
AI can draft a memo in seconds, but litigation is not a demo. Your work product has to survive internal review, client expectations, opposing counsel, and sometimes a judge who will not tolerate “the model said so.” The safest way to adopt AI legal services is to focus on use