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QWED-Legal

The Paralegal for AI-Powered Contract Review 🏛️
When lawyers used ChatGPT and cited 6 fake court cases (Mata v. Avianca), QWED-Legal would have caught them before the $5,000 fine.
QWED-Legal is a deterministic verification layer for AI-generated legal document analysis. It catches:
  • Date calculation errors (30 business days miscalculated)
  • Contradictory clauses (Clause A says X, Clause B says Not X)
  • Liability miscalculations (200% of 5M≠5M ≠ 15M)
  • Hallucinated citations (fake case names, invalid reporters)
pip install qwed-legal
GuardEngineUse Case
DeadlineGuardpython-dateutil + holidaysBusiness days, leap years, jurisdiction holidays
LiabilityGuardDecimal + SymPyCap %, tiered liability, indemnity limits
ClauseGuardZ3 SMT SolverContradiction detection, termination conflicts
CitationGuardRegex + BluebookCase citations, reporter validation
JurisdictionGuardRule-based logicChoice of law, forum selection, CISG
StatuteOfLimitationsGuardDate calculationsClaim periods by jurisdiction

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Quick Example

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Verify a Deadline Calculation

from qwed_legal import DeadlineGuard

guard = DeadlineGuard()
result = guard.verify(
    signing_date="2026-01-15",
    term="30 business days",
    claimed_deadline="2026-02-14"  # LLM claimed this
)

print(result.verified)   # False!
print(result.computed_deadline)  # 2026-02-27 (correct)
# ❌ ERROR: Deadline mismatch. Expected 2026-02-27, but LLM claimed 2026-02-14.

from qwed_legal import CitationGuard

guard = CitationGuard()
result = guard.verify("Brown v. Board of Education, 347 U.S. 483 (1954)")

print(result.valid)  # True - valid Bluebook format
print(result.parsed_components)
# {'plaintiff': 'Brown', 'defendant': 'Board of Education', 'volume': 347, 'reporter': 'U.S.', 'page': 483, 'year': 1954}

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Architecture

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High-Level Flow

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Guard Selection Flow

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Audit Log: Real Hallucinations Caught

Contract InputLLM ClaimQWED Verdict
”Net 30 Business Days from Dec 20”Jan 19🛑 BLOCKED (Actual: Feb 2)
“Liability Cap: 2x Fees ($50k)“$200,000🛑 BLOCKED (Actual: $100,000)
“Seller may terminate with 30 days notice” + “Neither party may terminate before 90 days""Clauses are consistent”🛑 BLOCKED (Conflict detected)
“Smith v. Jones, 999 FAKE 123”Valid citation🛑 BLOCKED (Unknown reporter)

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Why Not Just Trust the LLM?

LLMs are probabilistic. They can:
  • Hallucinate case citations (Mata v. Avianca scandal)
  • Miscalculate business days (ignore holidays, weekends)
  • Miss contradictory clauses (termination notice vs minimum term)
  • Get percentage math wrong (200% of 5M≠5M ≠ 15M)
QWED-Legal uses deterministic verification:
LLM OutputQWED VerificationEngine
”Deadline is Feb 14”Calculate business dayspython-dateutil
”Liability cap is $15M”Decimal mathSymPy
”Clauses are consistent”Z3 satisfiabilityZ3 SMT
”Citation is valid”Bluebook regexPattern matching

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Jurisdiction Support

DeadlineGuard supports jurisdiction-specific holidays: 
from qwed_legal import DeadlineGuard

# US holidays (default)
us_guard = DeadlineGuard(country="US")

# UK holidays
uk_guard = DeadlineGuard(country="GB")

# California-specific holidays
ca_guard = DeadlineGuard(country="US", state="CA")

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Next Steps