ChatGPT vs. Casetext vs. Harvey: Picking the Right AI Tool for a Small NJ Law Firm

There's no shortage of AI tools pitching themselves to attorneys right now. The harder problem isn't finding one, it's figuring out which one is actually worth trusting with your clients' matters when you're a solo or two-attorney firm in New Jersey operating without a dedicated IT department or general counsel to backstop a bad decision.

This post compares three tools that come up most often in conversations with NJ small-firm attorneys: ChatGPT (OpenAI's consumer and API product), Casetext's CoCounsel (now owned by Thomson Reuters), and Harvey (the legal-specific model backed by several major law firm partnerships). The comparison isn't about which tool wins on a spec sheet. It's about which one fits the actual working conditions of a firm with fewer than five attorneys.

How the Three Tools Differ in Practice

ChatGPT (including the Plus and Teams tiers) is the most accessible entry point. Its strength is general drafting: summarizing documents, generating first-draft correspondence, rewriting dense passages for client-facing clarity. The weakness that matters most for NJ practitioners is that it has no built-in access to NJ-specific primary law. It doesn't query Westlaw or Lexis. When you ask it a question rooted in New Jersey case law or New Jersey court rules, it draws on training data that may be outdated or simply wrong. For a litigation firm that needs current citations, this is a serious limitation. For a transactional practice focused on contract drafting and document review, it's far less of a problem.

Data handling is the other variable to watch. OpenAI's Business API and Teams plans offer opt-out from training on your inputs, but they do not provide a HIPAA Business Associate Agreement, and they have no legal-sector-specific data processing terms. If your clients include healthcare providers or any party with protected health information, this matters immediately. For general commercial or family law matters, the risk profile is different, but NJ RPC 1.6's confidentiality obligations still require you to have thought through where your client data goes before it goes there.

Casetext's CoCounsel, operating through Thomson Reuters, is purpose-built for legal research workflows. It connects to Westlaw's database, which means it can actually surface current New Jersey case law, statutes, and court rules with citations you can verify. For litigation-heavy NJ practices, especially those working in Superior Court regularly, this is a meaningful advantage. The tool is also designed with law firm data governance in mind: Thomson Reuters has clearer data isolation commitments than most general-purpose AI providers, which makes the RPC 1.6 conversation somewhat easier to document.

The tradeoff is cost and scope. CoCounsel is priced above what a solo attorney on a tight margin wants to absorb for occasional research use, and its capabilities outside of research (document drafting, client communication) are narrower than ChatGPT's. If your firm already has a Westlaw subscription, the integration makes strong economic sense. If you don't, you're paying for both the underlying legal database and the AI layer simultaneously.

Harvey is the most enterprise-oriented of the three. It was designed initially for large firm workflows, and while the company has expanded its target market, its pricing and onboarding model still reflects those origins. Harvey's value proposition centers on complex document analysis, due diligence, and contract work at volume. For a solo NJ attorney handling, say, fifty residential closings a month or a steady diet of commercial lease reviews, the capacity to process large document sets quickly is genuinely useful. For someone with lighter and more varied caseloads, it's often more tool than the work requires.

Harvey's data handling terms are more negotiable than OpenAI's for firms that can meet their minimum thresholds, but that negotiation is less accessible to a solo than to a mid-size firm with bargaining power.

The Question to Ask Before You Subscribe

Before you evaluate features, answer one question: what is the single most time-consuming task in your practice that doesn't require legal judgment, only processing?

If the answer is research synthesis, CoCounsel is the strongest fit. If it's drafting and editing routine documents, ChatGPT (properly configured with opt-out settings) gives you the most flexibility per dollar. If it's high-volume contract review, Harvey deserves a closer look, but verify the pricing before you get attached to the demo.

What None of Them Replace

All three tools require you to verify their output before it goes out the door. NJ attorneys facing competence obligations under RPC 1.1 can't outsource the judgment call to any of these platforms. The citations CoCounsel pulls still need to be shepardized. The contract language Harvey flags still needs attorney review. The draft ChatGPT produces still needs to reflect your client's actual facts.

The practical step before signing any subscription: request the vendor's data processing addendum in writing, confirm how your firm's inputs are stored and for how long, and document that review in your client file protocol. That paper trail is what demonstrates reasonable diligence if a confidentiality question ever comes up later.

Start with a one-month trial of whichever tool aligns with your practice type, run it on non-sensitive matters first, and measure the actual time savings against the actual cost before you commit.