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Ashish Yadav v. Anoshan Ahangama and Ahangama Law Professional Corporation

Court
ON SCSM
Jurisdiction
Canada
Decided
2026-05-04
AI tool
Implied
Outcome
—
Monetary penalty
None reported

What was hallucinated

Misrepresented: Exhibits & Submissions | Defence counsel produced a one-page 'Database Document' labeled 'page 1 of 5' but initially withheld the other pages; court found the exhibit incomplete and misleading. || Misrepresented: Case Law | Database Document listed 'Schroder v. All Languages' as awarding 1 week notice when the actual award was about $6,000; court found the description inaccurate. || Misrepresented: Case Law | Database Document listed 'Bryczkowski v. Dennison Associates' as a 3-month notice award though that action was dismissed; court identified the entry as inaccurate. || Fabricated: Case Law | Multiple cases listed in the Database Document could not be located in reported law and 'may not even exist', suggesting fabricated entries.

Details

Defence counsel (Mr. Gorrin) submitted a one-page 'Database Document' listing cases relevant to notice. The court discovered it was page 1 of 5, and the full 5-page document (later produced) contained additional cases and showed inconsistent search criteria. The court found many case descriptions in the Database Document inaccurate, some cases could not be located (and may be fabricated), and therefore the document was unreliable and was not given weight. No professional sanction or monetary penalty was imposed; the court simply rejected the document as an unreliable exhibit.

Sanction teardown · ON SCSM, Canada · 2026-05-04

Ashish Yadav v. Anoshan Ahangama and Ahangama Law Professional Corporation

What happened

In ON SCSM, Canada, 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:

  • Misrepresented (Exhibits & Submissions)
    Defence counsel produced a one-page 'Database Document' labeled 'page 1 of 5' but initially withheld the other pages; court found the exhibit incomplete and misleading.
  • Misrepresented (Case Law)
    Database Document listed 'Schroder v. All Languages' as awarding 1 week notice when the actual award was about $6,000; court found the description inaccurate.
  • Misrepresented (Case Law)
    Database Document listed 'Bryczkowski v. Dennison Associates' as a 3-month notice award though that action was dismissed; court identified the entry as inaccurate.
  • Fabricated (Case Law)
    Multiple cases listed in the Database Document could not be located in reported law and 'may not even exist', suggesting fabricated entries.

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

Not specified in source record.

Additional detail

Defence counsel (Mr. Gorrin) submitted a one-page 'Database Document' listing cases relevant to notice. The court discovered it was page 1 of 5, and the full 5-page document (later produced) contained additional cases and showed inconsistent search criteria. The court found many case descriptions in the Database Document inaccurate, some cases could not be located (and may be fabricated), and therefore the document was unreliable and was not given weight. No professional sanction or monetary penalty was imposed; the court simply rejected the document as an unreliable exhibit.

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/2223/Yadav-v-Ahangama-2026-CanLII-48313-ON-SCSM.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).

Source: https://www.damiencharlotin.com/documents/2223/Yadav-v-Ahangama-2026-CanLII-48313-ON-SCSM.pdf

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