Sanction teardown · C.D. California, USA · 2025-05-05
Flowz Digital v. Caroline Dalal
What happened
In C.D. California, USA, a filing relied on Lexis+AI to help draft legal argument. The court identified the following problems with the citations in that filing:
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Misrepresented (Case Law)Plaintiff cited In re Daou Systems to support a direct-vs-derivative principle, but the Court noted the case did not address that distinction.
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Misrepresented (Case Law)Plaintiff cited S.E.C. v. Cross Financial Services for a pleading-stage proposition on corporate control, but the Court found it addressed subject-matter jurisdiction over a nominal defendant and questioned relevance.
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Fabricated (Case Law)Plaintiff cited a case the Court could not locate after multiple searches and ordered Plaintiff to attach it.
Which AI tool
Lexis+AI. Note: Charlotin's public database records tool attribution only where a court order, brief, or reporting on the matter states it explicitly; "unidentified" or "implied" means the record indicates AI use but does not name a specific product — we do not guess.
Outcome
Monetary Sanction; Bar Referral
Additional detail
In their Response to the Order to show Cause, Counsel specified that they used Lexis+AI, and stressed that "LexisNexis itself has publicly emphasized the reliability of its Lexis+ AI platform, marketing it as providing “hallucination-free legal citations” specifically to avoid citation errors."Case was eventually jointly dismissed.
How Citation Safe would have caught this
Citation Safe runs three deterministic layers before a brief is filed: (1) does the citation exist against CourtListener's database of published opinions, (2) if quoted, does that exact language appear in the source, (3) does the cited case actually support the proposition it is cited for. Fabricated case citations fail Layer 1. Fabricated or misattributed quotations fail Layer 2 even when the underlying case is real. Misrepresented holdings — a real case cited for a proposition it does not support — are the target of Layer 3. None of these checks involve asking another language model whether the citation looks right; they are lookups and text-matches against the actual source, which is why a hallucinated citation has to survive a direct lookup against the authoritative source — not another model's opinion — to earn a VERIFIED stamp; our measured false-verify rate is published live at /quality.
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Source: https://www.damiencharlotin.com/documents/443/Flowz_Digital_v._Caroline_Dalal_C.D._California_USA_May_5_2025.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).