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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.

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.

June 2026 · 6 min read

Engineering

Verifying AI in under 200ms without slowing production

The architecture behind inline verification: caching, parallel checks and how we keep the Nanchs Score fast at scale.

May 2026 · 7 min read

Playbook

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

The exact steps enterprise teams use to move from a blocked pilot to an approved, auditable rollout.

May 2026 · 5 min read

Product

Anatomy of the Nanchs Score

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

April 2026 · 6 min read

Industry

What trustworthy AI looks like in banking

Lessons from deploying verification across customer service, KYC and internal knowledge workflows at tier-1 banks.

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.

March 2026 · 7 min read