Conflict Checks That Actually Happen: A Small-Firm System

What a real check screens (more than the named parties)

• Current and former clients - the former-client rule (1.9) is where small firms slip, because memory fades faster than duties do.
• Adverse parties and their affiliates: subsidiaries, principals, d/b/a names, spouses in family matters.
• Related players: witnesses, co-counsel, opposing counsel, insurers, key corporate officers - relationships that create positional or personal conflicts.
• Name variants: the check is only as good as its fuzzy matching - 'Bob Smith,' 'Robert Smith,' and 'R. Smith Holdings LLC' must all surface.

When it runs (three triggers, not one)

At intake, before substantive information flows - the check everyone knows. At party changes - new defendants added, a witness becomes adverse, a corporate party restructures; live matters grow conflicts the intake check never saw. And at lateral events - new hires arrive carrying their former clients' conflicts with them. A system that only checks at intake is a third of a system.

The data problem, and what AI changed

A check is a search of your records - which means it fails silently when the records are thin. The historical weakness: party lists assembled by hand from whatever intake captured, searched against a database only as complete as past data entry. Small firms 'checked conflicts' against a fraction of the names actually implicated.

AI extraction changes both sides. On the incoming side, every party, alias, counsel, and affiliate mentioned in the intake documents is extracted automatically - the screen list stops depending on what a busy human typed. On the database side, every prior matter's documents have been read too, so the book you search reflects the files, not the filing discipline. The check's judgment - does the overlap disqualify, is consent available, is a screen required - remains entirely the lawyer's. The system's contribution is that the overlap surfaces at all.

The minimum viable conflicts system

• One searchable book of record: every client, adverse party, and related player across all matters, past and present.
• Extraction-fed lists: parties pulled from documents at intake, not typed from memory.
• Fuzzy matching with human review of hits - overlap surfaced with context, decided by the lawyer.
• Re-checks wired to events: party changes and laterals trigger screens automatically.
• A written record of every check: what was searched, what surfaced, what was decided, by whom. The check that isn't documented didn't happen.

How do small law firms run conflict checks?

The defensible minimum: a single searchable record of all clients, adverse parties, and related players across the firm's history; screening at intake, at party changes, and at lateral hires; fuzzy name matching; and documentation of every check and decision. The historical weak points - hand-assembled party lists and incomplete databases - are what AI extraction now fixes, by reading the parties out of the documents on both sides of the search.

Can AI run a conflicts check?

AI runs the screen; the lawyer makes the call. Extraction assembles the complete party list from intake documents (including affiliates and name variants humans skip), searches it against the firm's book, and surfaces overlaps with context. Whether an overlap disqualifies, whether consent cures it, whether a screen suffices - that judgment is non-delegable. The AI's contribution is making sure the check actually happens, completely, on every matter.

What happens if a law firm misses a conflict?

Consequences scale from awkward to severe: disqualification motions (with the fees and delay they carry), disgorgement of fees, bar discipline, and malpractice exposure - plus the client-relationship damage that outlasts all of it. Most misses trace to process gaps rather than judgment errors, which is why the fix is systemic: complete data, automatic triggers, documented decisions.