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Reading a 60-page document end-to-end is sometimes essential — and often a waste. For triage, decision-making, or “I just need the point”, a structured AI summary is faster and frequently more reliable than scanning headings.
Three depths you should know
- TL;DR (3 lines): the elevator-pitch version. Tells you if the document is even worth your time.
- Standard (one page): key arguments, decisions, numbers, risks. The default for executives and review.
- Section-by-section: for due diligence, legal review, or anything where context per-section matters.
What to ask the summary to surface
Generic “summarise this” gives generic summaries. Better prompts ask for specific structure:
- “Top three takeaways.”
- “Key numbers with their context.”
- “Decisions or commitments made.”
- “Risks, dependencies and open questions.”
- “Anything that would surprise a reader who only read the executive summary.”
How extractive vs generative changes things
Extractive summaries pull verbatim sentences from the source. Highly faithful, sometimes choppy, never fabricates.
Generative summaries paraphrase and synthesise. More readable, but capable of subtle drift if the model hallucinates.
For legal, medical, financial: prefer extractive or hybrid. For everyday reading: generative is faster and easier.
Always verify the numbers
Even at 99% accuracy, summary tools occasionally swap a 12% for a 21%. If a number drives a decision, check it against the source. Treat AI summaries as a fast first pass, not as a substitute for reading the parts that matter.
Frequently asked questions
Are summaries accurate?
Modern models are highly accurate at capturing structure and overall arguments, but can still misquote specific numbers or names. Always verify decision-critical facts against the source.
Is my document used to train the model?
No. Files are processed over SSL, summarised, and deleted within 60 minutes. No content is retained or used for training.