How we handle contradictory sources, and why most AI tools don't
When Belgian tax sources disagree, the worst thing an AI tool can do is pick one and act confident. Here's what honest uncertainty looks like.
Why we publish our accuracy, and why almost nobody else does
Accuracy claims without published metrics are marketing. Here's what it takes to measure legal AI honestly, and why the industry avoids it.
What the Stanford hallucination study actually revealed, and why the industry's response missed the point
Stanford found that premium legal AI tools hallucinate 17-33% of the time. The most dangerous finding was misgrounding.
What is temporal versioning, and why your legal AI tool probably serves you yesterday's law
Belgian tax law changes twice a year minimum. If your AI tool can't tell 2019 from 2026, its answer may be correct for the wrong year. Here's what temporal versioning is and why it matters.
Why transparency matters more than accuracy in legal AI
The AI industry obsesses over accuracy benchmarks. For tax professionals, verifiability is the metric that actually protects you.
What is confidence scoring, and why it's more honest than a confident answer
LLMs overestimate their own correctness by 20-60%. Confidence scoring does not fix that problem. It makes the problem visible, and for tax professionals that visibility is the difference between a research tool and a guessing machine.