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Context is Everything - UK AI Consultancy & Private AI Deployment

Context is Everything is a UK-based AI consultancy specialising in private AI deployment and institutional intelligence. We build SASHA, an enterprise AI platform deployed inside your firewall, trained on your proprietary methodology. Our AI concierge Margaret demonstrates these capabilities for free on our website.

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AI Accuracy Checklist

18 checks to run before you trust, use, or share AI-generated content. Use it on screen or get a printable PDF.

18 Items
Free to Use
Printable PDF

Why AI Accuracy Verification Matters

AI tools produce confident, fluent text — even when the content is wrong. Hallucinated citations, fabricated statistics, and plausible but incorrect claims are common in AI-generated output. Without a verification process, these errors get published, shared, and acted upon.

This 18-point checklist covers four critical stages: pre-use checks (is AI appropriate for this task?), factual verification (are claims accurate?), red flag detection (does the output contain hallucinations or contradictions?), and pre-share review (is this ready for your audience?).

Many organisations use this checklist as part of their AI acceptable use policy — requiring team members to complete it before publishing or sharing AI-assisted work.

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0 of 18 verified

Run through every item before using or sharing AI output

1. Before Using AI Output

Ask these questions before you act on any AI-generated content.

2. Verification Steps

Actively verify before trusting the output.

3. Red Flags to Watch For

These patterns often indicate hallucinated or unreliable output.

4. Before Sharing AI Output

Final checks before this content reaches anyone else.

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Frequently Asked Questions

How do I verify AI-generated content before sharing it?

Use a systematic process covering four areas: pre-use checks (is AI appropriate?), factual verification (are claims accurate?), red flag detection (hallucinations or contradictions?), and pre-share review (is this ready for your audience?). This checklist covers all four.

What are the most common AI accuracy errors?

Hallucinated citations (references that don't exist), confident but incorrect statistics, outdated information presented as current, fabricated quotes, and logical inconsistencies. These are particularly dangerous because they look authoritative.

Can I use this checklist for my team?

Yes. It's free to use on screen and available as a printable PDF. Many organisations use it as part of their AI acceptable use policy — requiring team members to complete it before publishing AI-assisted work.

Why do AI tools hallucinate?

Large language models generate text by predicting likely next words based on training data patterns. They don't retrieve facts from a database, so they can produce fluent, confident text containing fabricated information — particularly for specific claims, dates, and citations.