Document workflows
An ai api examples pdf workflow helps turn scattered notes, reports, and reference files into clear, reusable deliverables. Start with a concrete prompt, then refine the output for the audience and format you need.
Prompt patterns
These prompt-to-result examples show how to move from an unstructured PDF to a reviewable output without starting from a blank page.
Summarize
1
Read this PDF and summarize the purpose, methodology, key findings, and limitations in four labeled sections. Cite the page number for each finding.
Extract
2
Extract every product name, date, amount, and stated condition from this PDF. Return one row per item and use null when a field is missing.
Verify
3
Answer these questions using only the attached PDF. Quote the supporting sentence, include its page number, and say Not found when the document gives no answer.
Replace the document type, fields, and audience in each prompt while keeping the evidence and missing-value rules.
Practical use cases
A research lead needs a fast first pass across a long study. The ai api examples page shows broader patterns, while this PDF workflow focuses on traceable findings.
Receive a sectioned brief with page references, open questions, and a clear distinction between evidence and interpretation.
ai api examplesAn operations manager has supplier manuals and policy PDFs spread across folders. Use the examples page for general task ideas, then apply field-by-field extraction here.
Create a consistent comparison table that exposes missing dates, conflicting requirements, and follow-up items.
ai api examplesA student wants to study a dense reading without losing the original context. The examples page introduces common AI tasks; the PDF prompt adds citations and uncertainty controls.
Turn a reading into a study guide with definitions, supporting passages, practice questions, and topics that need another look.
ai api examples
Visible improvement
Use the divider to compare the starting material with a structured presentation; always check the result against the source.
Output gallery
A useful result is specific about what it used, what it found, and what remains uncertain. Each example below pairs an output type with the input instruction that shaped it.
Brief
Table
Cited
Actions
Responsible handling
A generated PDF result is a draft for review, not an authoritative record. Keep the original file beside the output, preserve page references, and ask a qualified person to verify legal, medical, financial, safety, or contractual claims before they are shared or acted on. Avoid placing personal, confidential, or regulated information into a workflow unless your approved process permits it. Define the intended audience before prompting: an internal summary can be direct, while a public document needs clearer sourcing and uncertainty language. For repeat work, test the same prompt on representative files, record the fields you expect, and inspect how the system handles scans, tables, footnotes, and missing pages.
Common questions
Useful examples include summarizing a report, extracting fields into a table, answering questions with page citations, and creating an action list. The best workflow states the desired format and tells the system what to do when information is missing.
Yes, if the prompt explicitly requests page numbers or source passages and the document is processed with its page structure available. Check several citations manually, especially when the PDF is scanned, has complex layouts, or contains tables.
Name every field, define the output columns, specify the format, and provide a rule for missing values such as null or Not found. Add validation instructions for dates, amounts, duplicate entries, and conflicting information.
Usually they should be treated as drafts. Verify important claims against the source, review sensitive content, check formatting, and confirm that the final document meets the requirements of its audience and organization.