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Summarize PDF

AI
Executive summary + section bullets.
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What you'll get: an executive summary plus per-section bullets, each cited to a source page. Best for reports, papers, and long memos. For another use, try AI · TL;DR Generator.

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Private & secure
AI tools process your PDF in memory, send only the extracted text to the model, and discard everything immediately. No file is persisted on our servers.
No watermarks
Clean output, no branding, no daily limits.
Pay only for what you use
Purchased credits never expire. Cancel anytime.

Why people use AI summarize

When a document is long enough that reading it cover-to-cover isn’t practical, a summary is the difference between “I read it” and “I meant to read it.” AI summarize generates a structured digest that surfaces the document’s actual claims, decisions, and findings — with page citations so you can jump back for verification.

Long-form report digest
Annual reports, market research, white papers — content where the executive summary is fine but you need a level deeper than the abstract. Summary lands at ~1/10th the length and keeps the section-by-section structure.
Meeting transcript distillation
Drop the auto-generated transcript from your call recording, get a recap with decisions, action items, and unresolved questions. Useful for catching attendees up; pairs with AI Action Items for the to-do extraction.
Contract / legal overview
Get the gist of a 40-page MSA before sending it to counsel. Summary won’t replace legal review, but it tells you which clauses to ask about. Liability caps, term length, payment terms, and termination triggers all surface.
Article / paper triage
Decide whether a research paper or industry article deserves your full read. Summary covers method + findings + caveats so you can route to a deep read, a skim, or a delete.
Email-thread / chat-export distillation
A 30-message email thread or 200-message Slack export becomes a 6-bullet recap of decisions made and parties involved. Especially useful for joining a project mid-stream.

How AI Summarize works

Three steps. Sign in to run, zero retention — files never persisted on our servers.

  1. STEP 1
    Drop your PDF + pick depth
    Upload a PDF up to 100 MB. Pick “summary” depth (default) or one of the variants — TL;DR, key points, study notes, ELI5, FAQ — each tuned for a different reading goal.
  2. STEP 2
    We extract + chunk + summarize
    Server-side text extraction (no rasterization), chunking when the PDF exceeds the model’s context window, then a map-reduce pass to keep section structure. The model used is selected by the routing layer for cost-vs-quality fit.
  3. STEP 3
    Get markdown back with page cites
    Output is markdown with section headings + page references. Download as .md or copy. The document and the summary land in /app/files for re-access without re-spending credits.

What makes pdfcraft ai different

  • Citations on every claim
    Every AI summary, answer, and translation links back to the page it came from. You can verify the source before relying on the output. Hallucination is bounded, not blind.
  • Pay only for what you use
    No subscription. Purchased credits never expire. Cancel anytime. Cost shown before you run — exact credit amount appears after upload.
  • Multi-provider routing, no vendor lock-in
    We balance multiple AI providers per call to optimise cost and quality. If one has an outage, the next call automatically tries another. You're not bound to a single vendor's pricing or downtime.
  • Zero retention by design
    Your PDF lives in memory only as long as the AI call needs it, then it's discarded — nothing is persisted to our servers. We don't fine-tune models on your data. Verifiable in your dashboard's audit log.
  • Honest about model limits
    When a doc exceeds the model's context window we surface that the output was truncated (we render result.wasTruncated in every AI tool's UI). When a number can't be verified from the source we flag it. No silent failures.

Frequently asked questions

How long is the output, and is it deterministic?
Length scales with input — for typical 10–40 page docs, the summary is ~500–1500 words. Output is NOT byte-identical across runs (LLM nondeterminism + temperature), but the structure and major points are stable. If you re-summarize the same PDF you’ll get the cached result for free (idempotent via internal idempotency key).
Does it cite specific pages?
Yes — claims that originate in a specific page or section are followed by a page-number reference. This is the key feature that distinguishes pdfcraft summary from a generic chatbot summary: every assertion is verifiable in the source.
What about confidential documents?
The PDF is sent to the AI provider for inference (no client-side LLM today). It’s NOT stored by the provider beyond the inference window (we use no-train endpoints where available). For maximum privacy on truly sensitive documents, redact first — Redact PDF is in-browser and sensitive content never reaches a server.
How is this different from AI TL;DR / Key Points?
Same backend op, different presentation. Summary is the default 1/10th-length structured digest. TL;DR is a 2–3 sentence elevator pitch. Key Points is bullet-list-only. ELI5 explains like you’re a layperson. Study Notes is exam-prep oriented. Pick the variant that matches how you’ll use the output.
What's the credit cost?
3 credits per summary by default. Cost is fixed per submission regardless of PDF size — no surprises. Credit balance + remaining quota is visible on /app/billing.
What if the summary is wrong?
It happens. LLMs occasionally fabricate (hallucinate) details, especially on technical content. Use the page citations to verify any claim before relying on it. For high-stakes work (legal, medical, financial), treat the summary as a navigation aid, not a substitute for reading the source.

Need a tighter version?

AI TL;DR returns a 2–3 sentence elevator-pitch version of the same content — useful for the executive forwarding the doc to a busy stakeholder.

Try AI TL;DR

Related PDF tools

Other tools in the AI category — built on the same private, in-browser pipeline.

Use cases for this tool

Step-by-step workflows that put this tool to work.

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