🎙️ Ep. #131, Supercharging Litigation With AI: How StrongSuit Helps Lawyers Transform Research, Doc Review, and Drafting 💼⚖️

My next guest is Justin McCallan, founder of StrongSuit, an AI-powered litigation platform built to transform how litigators handle legal research, document review, and drafting while keeping lawyers firmly in control. In this episode, Justin and I dig into practical, real-world workflows that solos, small firms, and big-firm litigators can use today and over the next few years to change the economics, pace, and strategy of litigation—without sacrificing accuracy, ethics, or the quality of advocacy.

Join Justin and me as we discuss the following three questions and more!

  1. What are the top three ways litigators should be using AI tools like StrongSuit right now to change the economics and pace of litigation without sacrificing accuracy, ethics, or quality of advocacy?

  2. What are the top three mistakes lawyers make when adopting AI for litigation, and what practical workflows help lawyers stay in the loop and use AI as a force multiplier instead of a risk? 

  3. Looking ahead to 2026 and beyond, what are the top three AI-driven workflows every litigator should master to stay competitive, and how can platforms like StrongSuit help build those capabilities into day-to-day practice? 

In our conversation, we cover the following

  • 00:00 – Welcome and guest introduction

    • Justin joins the show and shares his current tech setup at his desk. 

  • 00:00–01:00 – Justin’s current tech stack

    • Lenovo laptop, ultra-wide monitor, and regular use of StrongSuit, ChatGPT, and Gemini for different AI tasks.

    • Everyday tools: Microsoft Word and Power BI for analytics and fast decision-making.

  • 01:00–02:00 – Android vs. iPhone for AI use

    • Why Justin has been on Android for 17 years and how UI/UX familiarity often drives device choice more than AI capability.

  • 02:00–05:30 – Q1: Top three ways litigators should be using AI right now

    • Using AI for end-to-end legal research across 11 million precedential U.S. cases to build litigation outlines and identify key authorities.

    • Scaling document review so AI surfaces relevant documents and synthesizes insights while lawyers focus on strategy and judgment.

    • Leveraging AI for drafting and editing—improving style, clarity, and consistency beyond traditional spelling and grammar checks.

  • 05:30–07:30 – StrongSuit vs. basic tools like Word grammar check

    • How StrongSuit aims to “up-level” a lawyer’s writing, not just catch typos.

    • Stylistic improvements, clarity enhancements, and catching subtle inconsistencies in legal documents.

  • 06:00–08:00 – AI context limits and scaling doc review

    • Constraints of large models’ context windows (around ~1M tokens ≈ ~750 pages).

    • How StrongSuit runs multiple AI agents in parallel, each handling small page sets with heuristics to maintain cohesion and share insights.

  • 08:00–09:00 – Handling tens of thousands of documents

    • How StrongSuit can handle between roughly 10,000–50,000 pages at a time, with the ability to scale further for enterprise matters.

  • 09:00–11:30 – Origin story of StrongSuit

    • Why Justin saw a once-in-a-generation opportunity when large language models emerged and how law, with its precedent and text-heavy nature, is especially suited to AI.

    • StrongSuit’s focus on litigators: supporting lawyers from intake through trial while keeping them in the loop at every step.

  • 11:30–13:30 – From intake to brief drafting in minutes

    • Generating full litigation outlines, research, and analysis in about ten minutes, then moving directly into drafting memos, briefs, complaints, and motions.

    • StrongSuit’s long-term goal: automating 50–99% of major litigation workflows by the end of 2026 while preserving lawyer control and judgment.

  • 12:00–14:30 – How StrongSuit tackles hallucinations

    • Building a full database of all precedential U.S. cases enriched with metadata: parties, summaries, holdings, and more.

    • Validating citations by checking whether the Bluebook citation actually exists in StrongSuit’s case database before surfacing it to the user.

    • Why lawyers should still review cases on-platform before filing, even when AI has filtered out hallucinations.

  • 14:30–16:30 – Coverage and jurisdictions

    • Coverage of all U.S. jurisdictions, federal and state, focused on precedential cases.

    • Handling most regulations from administrative agencies, and limits around local ordinances.

    • Uploading your own case files and using complaints and prior research as inputs into StrongSuit workflows.

  • 15:00–17:00 – Security and confidentiality for litigators

    • SOC 2 compliance and industry-standard encryption at rest and in transit.

    • No model training on user data.

    • Optional end-to-end encryption that can even prevent developers from accessing case content, using local encryption keys.

  • 16:30–20:30 – Q2: Top mistakes lawyers make when adopting AI for litigation

    • Mistake #1: Talking about AI instead of diving in with structured experiments and sanitized documents.

    • Using a framework to identify high-impact tasks: high volume, repetitive work, and heavy data/analysis (e.g., doc review, research, contract drafting).

    • How to shortlist tools: look for SOC 2, real product depth, awards, and a focus on your specific workflows.

    • Mistake #2: Expecting immediate mastery instead of moving through predictable adoption stages—from learning the tool, to daily use, to stringing workflows together.

  • 20:30–22:30 – Building firm-wide AI workflows over time

    • Moving from isolated experiments to integrated, low-friction workflows, such as automatic intake-to-research pipelines.

    • Using client intake audio or transcripts to automatically extract facts, issues, and research paths.

  • 22:30–24:30 – Time constraints and “no-time” lawyers

    • Why lawyers don’t need to be “technical” to use StrongSuit.

    • Reframing AI as text-based tools where lawyers’ writing skills and analytical thinking are assets, not obstacles. 

  • 24:00–26:00 – Practical workflows beyond intake

    • Using AI to prepare for expert depositions, including reviewing valuation analyses, flagging departures from market consensus, and generating targeted questions.

    • Reinforcing the value of AI-enhanced legal research and drafting as core litigation workflows.

  • 26:00–29:30 – Q3: 2026 and beyond – AI-driven workflows every litigator should master

    • Rapid improvement of baseline models (e.g., jumping from single-digit to high double-digit performance on difficult benchmarks year over year). 

    • The idea of “tipping points,” where small performance gains turn AI from marginally useful to essential in specific tasks.

    • Why legal research is a great training ground for understanding where AI excels, where it falls short, and how to divide labor between human and machine.

    • The value of learning basic prompting skills to get more from AI systems, even when platforms offer visual workflows.

  • 29:30–32:30 – Will workflows actually change—or just get better?

    • Why Justin expects familiar litigation workflows (doc review, research, drafting) to remain structurally similar, but become far faster and more sophisticated.

    • AI agents handling the grind work while lawyers focus on synthesis, judgment, and strategy.

    • A future where “AI + lawyer vs. AI + lawyer” resembles high-level chess: same rules, but much deeper thinking on both sides.

  • 32:30–End – Where to find Justin and StrongSuit

    • How to connect with Justin and learn more about StrongSuit’s litigation tools.

Resources

Connect with Justin

Hardware mentioned in the conversation

Software & Cloud Services mentioned in the conversation

Word of the Week: Vendor Risk Management for Law Firms in 026: Lessons from the Clio–Alexi CRM Fight ⚖️💻

Clio vs. Alexi: CRM Litigation COULD THREATEN Law Firm Data

“Vendor risk management” is no longer an IT buzzword; it is now a core law‑practice skill for any attorney who relies on cloud‑based tools, CRMs, or AI‑driven research platforms.⚙️📊 The Tech‑Savvy Lawyer.Page’s February 2, 2026 editorial on the Clio–Alexi CRM litigation showed how a dispute between legal‑tech companies can reach straight into your client list, calendars, and workflows.⚖️🧾

In that piece, Clio and Alexi’s legal fight over data, AI training, and competition was framed not as “tech drama,” but as a live test of how well your firm understands its dependencies on vendors that control client‑related information.🧠📂 When the platform that hosts your CRM, matter data, or AI research tools becomes embroiled in high‑stakes litigation, your risk profile changes even if you never set foot in that courtroom.⚠️🏛️

Under ABA Model Rule 1.1, competence includes a practical understanding of the technology that underpins your practice, and that now clearly includes vendor risk.📚💡 You do not have to reverse‑engineer APIs, yet you should be able to answer basic questions: Which vendors are mission‑critical, what data do they hold, how would you respond if one faced an injunction, outage, or rushed acquisition.🧩🚨 That is vendor risk management at a level that is realistic for lawyers with limited to moderate tech skills.🙂🧑‍💼

LawyerS NEED TO Build Vendor Risk Plan for Ethical Compliance

Model Rule 1.6 on confidentiality sits at the center of this analysis, because litigation involving a vendor can expose or pressure the systems that hold client information.🔐📁 Our February 2 article emphasized the need to know where your data is hosted, what the contracts say about subpoenas and law‑enforcement requests, and how quickly you can export data if your ethics analysis changes.⏱️📄 Vendor risk management, therefore, includes reviewing terms of service, capturing “current” versions of online agreements, and documenting export rights and notice obligations.📝🧷

Model Rule 5.3 requires reasonable efforts to ensure that non‑lawyer assistance is compatible with your professional duties, and 2026 legal‑tech commentary increasingly treats vendors as supervised extensions of the law office.🧑‍⚖️🤝 CRMs, AI research tools, document‑automation platforms, and e‑billing systems all act as non‑lawyer assistants for ethics purposes, which means you must screen them before adoption, monitor them for material changes, and reassess when events like the Clio–Alexi dispute surface.📡📊

Recent legal‑tech reporting has described 2026 as a reckoning year for vendors, with AI‑driven tools under heavier regulatory and client scrutiny, which makes disciplined vendor risk management a competitive advantage rather than a burden.📈🤖 Practical steps include maintaining a simple vendor inventory, ranking systems by criticality, reviewing cyber and data‑security representations, and identifying a plausible backup provider for each crucial function.📋🛡️

LAWYERS NEED TO SHIELD THEIR CLIENT DATA FROM CRM LITIGATION AS MUCH AS THEY NEED TO PROTECT THEIR EthicS DUTIES!

Vendor risk management, properly understood, turns your technology stack into part of your professional judgment instead of a black box that “IT” owns alone.🧱🧠 For solo and small‑firm lawyers, that shift can feel incremental rather than overwhelming: start by reading the Clio–Alexi editorial, pull your top three vendor contracts, and ask whether they let you protect competence, confidentiality, and continuity if your vendors suddenly become the ones needing legal help.🧑‍⚖️🧰