Sanction teardown · M.D. Florida, USA · 2026-06-09
Leafwell, Inc. v. The Doc App, Inc. (2)
What happened
In M.D. Florida, USA, a filing relied on an unnamed/unconfirmed AI tool to help draft legal argument. The court identified the following problems with the citations in that filing:
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Misrepresented (Case Law)Castro overstated the breadth or holdings of four cases, presenting authorities as supporting broader propositions than they did.
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Fabricated (Other)Castro discussed a non-existent count in his motion (an invented cause of action).
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False Quotes (Case Law)Prior filings included citations that purportedly contained quoted language which the cited authorities did not actually contain.
Which AI tool
an unnamed/unconfirmed AI tool. 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
Decline to add new sanctions
Additional detail
The court noted prior filings contained numerous fabricated citations but observed Castro had nominally improved by citing existing authority. Because existing sanctions from a prior order remained and the court found additional sanctions excessive, it denied the plaintiff's motion for further sanctions. The court attributed much of the problem to Castro's failure to review AI-generated material rather than prohibiting AI use outright.
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.
Check a brief before you file it → · See our live false-verify rate
Source: https://www.damiencharlotin.com/documents/2405/Leafwell_Inc._v._The_Doc_App_USA_9_June_2026.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).