Benchmarks

Citation-accuracy and reliability benchmarks for AI legal research and drafting tools, framed as risk assessment rather than product endorsement. Each entry discloses the benchmark source type (peer-reviewed academic study, vendor-published report, or independent test), the tool name and version tested, the test date, and a methodology summary, and visually separates independent findings from vendor-coordinated ones. Entries cross-link to any Risk Digest case naming the same tool. Does not contain case outcomes (Risk Digest) or how-to guidance (Workflows), though it links to both.

ToolVendorSourceHallucination rateVersion testedTest date
Burger King's Whopper Guarantee: A Legal Terms Analysis
Why ASHRAE 188 Changed Legionnaires' Disease Lawsuits
AI Contract Review ROI: Building the Business Case for In-House Legal Teams
AI Replace Lawyers? A Task-by-Task Breakdown of What’s Actually Being Automated — and What Isn’t
Aramark Kiosk Case: Automated Accusation and Defamation Per Se
How Australia Is Reshaping AI Copyright Protection for Creatives
Beyond the Benchmark: Why Harvey AI and CoCounsel Outperform Lawyers in Tests but Lag in Daily Practice
How Consumer DNA Tests Uncover Decades-Old Medical Malpractice Cases
How Louisiana v. Callais Forced Cleo Fields From Congress
The 2026 Cuba oil blockade is four distinct sanctions layers
Can Dollarama's Garlic Powder Recall Defeat a Class Action?
How the Elkhorn zebra case unfolded legally
EU AI Act Compliance for Law Firms: An 8-Step Action Plan Before the August 2, 2026 Deadline
Flock Safety's AI Surveillance Network Under Legal Siege
How Google Play Services Data Became Convertible Property
Harvey AI Accuracy and Hallucinations: Benchmark Data vs. Real-World Reliability
Harvey AI Legal Research Tool: Features, Capabilities, and Documented Limitations
Harvey AI for Law Firms: A Structured Taxonomy of Practice-Group Use Cases
Hawaii Truck Bed Age Law: Minimum Raised to 16 in 2026
How to Use Tubi on ChatGPT
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