Automated Conflict Checks: What I'd Build for a Law Firm

Every new client engagement at a law firm starts with the same bottleneck: someone has to run a conflict check before the representation can begin. At a lot of firms, that someone is a paralegal with a spreadsheet, a practice management login, and a stack of other tasks due today.

A missed conflict is a malpractice exposure. A slow conflict check is a lost client. And a manual process that depends on one person's memory of who was named in which matter three years ago is neither fast nor reliable. That's the problem I'd build against.

What the Manual Process Actually Costs

The firms I talk to describe a version of the same morning: intake form comes in, paralegal or office manager pulls up the matter list, searches by last name, tries variations of the name, checks adverse parties, maybe checks related entities, and writes up a summary for the partner. That's thirty to ninety minutes per intake, depending on the name's complexity and how clean the database is.

Multiply that by how many new matters a firm opens per week. Then add the ones that slip through because someone was out sick or the search was done in a hurry. The cost isn't just the staff time. It's the liability exposure when the process fails.

The honest truth is that most firms tolerate this because it's always been done this way, and no one has sat down to map out what an automated version would actually look like. So here's what I'd build.

The Pipeline: From Intake Form to Attorney Sign-Off

The trigger is the intake form submission. Whether that's a form on your website, a Typeform, a Clio intake, or a custom intake portal, the moment a prospective client submits their information, the conflict check pipeline starts. No one has to remember to kick it off.

The automation pulls the prospective client's name, any named adverse parties, related business entities, and any other names on the intake. It runs those against your matter database, checking current clients, former clients, adverse parties in closed matters, and any other fields your firm tracks. I typically build this against a Supabase layer that mirrors your practice management system, or directly against your system's API if Clio or Filevine is in play.

The search uses fuzzy matching, not just exact string lookups. John Smith and Jon Smith and J. Smith all come back as candidates. That's intentional. A conflict check that only catches perfect name matches is not a conflict check.

What the Output Looks Like

The pipeline assembles a structured conflict report: prospective client name, each potential match found, the matter number, the relationship type (current client, former client, adverse party), and the matter status. If there are zero matches, the report says that clearly. If there are five potential matches, each one is listed with enough detail for an attorney to clear it in under a minute.

That report routes to the responsible attorney via email, or into a task in your practice management system, depending on how your firm operates. The attorney reviews it and marks it cleared or flagged. That sign-off is the gate. Nothing in this pipeline skips the attorney's review.

The Compliance Architecture That Makes This Safe

Attorney-client privilege is not something to route around for the sake of a slick build. Every component in this pipeline runs against data the firm already controls. Client names and matter details do not get sent to a general-purpose AI API for analysis unless the firm has explicitly approved that and signed a DPA with the vendor.

The fuzzy matching logic and the conflict report assembly happen in a secure workflow layer, typically n8n or Make running on infrastructure the firm controls or that I've configured with appropriate access restrictions. No third party is seeing your client list. The system generates the summary document; the attorney reviews and signs off before any response goes to the prospective client.

If your firm has existing security requirements or an IT policy, I build to fit inside them. I'm not asking you to change your security posture to accommodate my stack.

The Honest Tradeoffs

Fuzzy matching will produce false positives. That's by design. The goal is to catch every real conflict, which means the attorney will sometimes clear a match that turns out to be a different person with the same name. That's thirty seconds of review, not thirty minutes of searching. The tradeoff is worth it.

This build also depends on your matter database being reasonably complete. If your firm has years of matters in a system but adverse parties were never consistently entered, the automated search can only work with what's there. Part of the scoping conversation is an honest look at data quality. Sometimes the first step is a one-time cleanup, and then the automation runs clean from that point forward.

And this does not replace a supervising attorney's judgment on ethically complex situations. A name match that involves a former client in a substantially related matter is a legal ethics question, not a search result. The system flags it. The attorney decides.

What You Own When It's Done

Every build I do is fixed price. You can see how that works on the pricing page. There's no monthly retainer for the conflict check pipeline, no ongoing access fee I charge you to keep using something I built for you. You own the workflow, the credentials, the documentation, and the logic.

If someone on your team needs to adjust the search fields six months from now because you opened a new practice area, the docs I hand over show them how. You're not calling me every time the firm adds a new intake field.

The legal automation work I do is detailed on the law firms industry page if you want to see what else is in scope. The conflict check pipeline is one of the faster builds to scope and deliver because the data structure is predictable. That makes it a good first automation for a firm that hasn't done this before.

What the Intake-to-Clearance Flow Looks Like in Practice

• Prospective client submits intake form with their name, adverse party names, and entity names.
• Pipeline triggers immediately, runs fuzzy-match search against your matter database.
• Structured conflict report is assembled: each potential match with matter number, relationship type, and status.
• Report routes to the responsible attorney via email or task in your practice management system.
• Attorney reviews, clears or flags, and logs the sign-off.
• If cleared, intake pipeline continues and a matter draft is created. If flagged, the matter is held for ethics review.

The whole sequence, from form submission to attorney-ready report, runs in under two minutes for a typical search. The attorney's review adds a few more. Compare that to the thirty-to-ninety-minute manual version, and the math on staff time alone justifies the build in the first month.

If your firm is still running conflict checks by hand, the risk isn't hypothetical. A missed conflict doesn't announce itself until it's already a problem. The free audit on the book page is where I look at your current intake process and tell you exactly what I'd build, what it costs, and what data prep is needed before we start.