Field guides

In-depth guides on reliable AI for high-stakes work.

Practical, sourced writing on hallucination, reliability, and model risk, for the decisions where a confident, wrong answer is expensive. Honest about what the evidence supports and what it doesn't.

Credit & capital markets

Why AI hallucinates on financial decisions

The three mechanisms behind financial hallucination, why retrieval doesn’t fix it, what FINRA and the EU AI Act now ask for, and six controls that measurably reduce it.

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AI reliability

Does RAG eliminate hallucinations?

No. RAG reduces hallucination but leaves four gaps: retrieval misses, the model ignores or over-reads the passage, or cites a real source for an unsupported claim. What closes the gap is verification. With diagrams.

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AI reliability

Deterministic AI vs verifiable AI

“Deterministic AI” is 2026’s buzzword, but most of it is a rules layer over a probabilistic model. Why verifiability, not determinism, is what makes AI trustworthy on complex decisions, and how to judge a vendor’s claim.

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Legal

Verifiable AI for legal research

Fabricated citations are the defining AI risk in law. How verifiable AI checks every claim against the authorities it actually retrieved, flags what it only claimed to do, and runs locally so privileged matter stays private.

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Drug discovery

Reliable AI for drug discovery

A practical guide for R&D teams: how reliable, auditable AI controls hallucination on the decisions that cost years, labels its own confidence, and runs on your machine so your pipeline stays private.

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Manufacturing & operations

Reliable AI for operations

In operations, the costly answer is the plan that looks optimal and quietly breaks a constraint. How auditable AI verifies its own results, catches the too-good-to-be-true plan before it ships, and runs on your own machine.

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Cybersecurity

Reliable AI for cybersecurity

The two 2026 worries: the post-quantum migration and AI tools that fabricate findings. How auditable AI helps plan the migration and verifies every finding against the record of what it actually did, without being an encryption product.

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Healthcare

Reliable AI for healthcare

In clinical work the dangerous answer is the confident, fabricated one. How auditable AI works as decision support (not a diagnostic device), verifies its claims against the evidence, refuses what it cannot support, and runs on your machine so patient data stays private.

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AI reliability

How to verify AI output before you act on it

A practical method for checking an AI answer on a high-stakes decision: verify against the evidence, get a truly independent second opinion, demand an auditable trail, and re-ask adversarially.

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AI reliability

Is zero-hallucination AI real?

No AI is zero-hallucination, and claiming it is now a legal risk. What "controlled" actually means, the evidence, and how to verify any vendor’s claim yourself.

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Credit & capital markets

How to test an AI system for financial accuracy

A one-day protocol a risk function can run against any vendor, using your own documents, malformed questions, and three score columns, with our own results run through it.

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