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Notes on trustworthy AI

Research, engineering deep-dives and compliance playbooks from the team building the verification layer for enterprise AI.

Research

Why fluent AI answers are the most dangerous kind

The outputs most likely to slip past human reviewers are not the obviously broken ones — they are the confident, well-written answers that happen to be wrong. Here is how independent scoring changes the equation for regulated teams.

The Factlace Team · June 2026 · 8 min read

Compliance

Turning the EU AI Act into an engineering checklist

A practical mapping from regulatory obligations to the controls, logs and scores your AI systems need to produce.

The Factlace Team · June 2026 · 6 min read

Engineering

Designing inline verification for under 200ms

How we're thinking about the architecture — caching, parallel checks and the trade-offs involved in keeping the Factlace Score fast.

The Factlace Team · May 2026 · 7 min read

Playbook

A 30-day plan to get AI past your risk committee

A framework we recommend for moving from a stalled pilot to an approved, auditable rollout.

The Factlace Team · May 2026 · 5 min read

Product

Anatomy of the Factlace Score

What each of the four sub-scores measures, how they are weighted, and how to set thresholds for your risk appetite.

The Factlace Team · April 2026 · 6 min read

Industry

What trustworthy AI should look like in banking

Our take on how verification could fit customer service, KYC and internal knowledge workflows in a regulated bank.

The Factlace Team · April 2026 · 9 min read

Research

Measuring hallucination rates you can actually report

Moving beyond anecdotes to a repeatable, defensible methodology for quantifying AI reliability.

The Factlace Team · March 2026 · 7 min read