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.
How to evaluate a legal AI tool: 10 questions that actually matter
Most firms start by asking 'how accurate is it?' That's question 10 on this list. Here are the nine questions you should ask first, and why they matter more for professional tax work.
Fine-tuning vs. RAG: two ways to make AI smart, and why it matters which one your tax tool chose
Fine-tuning memorizes yesterday's law. RAG looks up today's. For Belgian tax professionals, this architecture choice determines whether your AI tool is current or confidently outdated.
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.
I asked ChatGPT and Auryth the same Belgian tax questions. Here's what happened
Three tax questions, two AI tools, one clear lesson: for professional research, verifiability beats confidence.
AI hallucinations: why ChatGPT fabricates sources (and how to spot it)
Why language models invent legal citations, what makes Belgian tax especially vulnerable, and three defenses that actually work.