AI Document Extraction and Review
Turn PDFs and images into structured fields, tables and entities while keeping the source page available for review and export.
Extract useful fields and tables from documents
Check each result against its source page
Export reviewed information for the next workflow
Video walkthrough · A document-review walkthrough using a fictional source page and illustrative extraction results. Open video · Read transcript
- Industry
- Financial services
- Focus
- Document processing
- Inputs
- PDFs, scanned pages and document images
- Teams
- Operations, finance and document-processing teams
The business situation
Where this fits
Teams repeatedly copy information from documents into spreadsheets or business systems. A structured result helps only when a reviewer can check where it came from and spot missing or uncertain information.
For document-heavy workflows where teams need structured information and an easy way to verify it.
- Staff rekey the same fields from PDFs.
- Tables require manual reconstruction.
- Reviewers cannot easily find the source of an extracted value.
The solution
How the solution helps
The document workspace presents extracted structure alongside the source. Reviewers can inspect fields, entities and tables, follow the relevant page region and export the information in a useful format. This supports document handling while keeping business approval with the responsible team.
Process the document
Upload a PDF or image and organise the resulting structure.
Review against the page
Inspect fields and tables with their source-page references.
Export the useful information
Choose JSON, CSV or Markdown for the next step in the process.
In practice
Review a document before handing off its data
Inspect a fictional document and the structured information beside it.
A PDF or image containing the fields and tables needed by the business process.
Open the document and result
View the source page alongside its structured summary.
OutputA result that can be checked in context.
Inspect the details
Select fields and tables, review source regions and note missing information.
OutputA clearer record of the usable data and open questions.
Choose an export
Export the structure in the format needed by the next team or system.
OutputA practical hand-off without repeated copying.
How it works
How the workflow comes together
Document processing
Turn an upload into page-level extraction results.
Evidence model
Retain the source-page and region references behind the result.
Review and export
Make the extracted structure easy to inspect and reuse.
- Amazon Bedrock
- Document and page-region extraction
- Amazon S3
- JSON, CSV and Markdown exports
Customer value
What this means for your team
Structured data with a visible source
Reviewers can inspect a value or table in context instead of trusting an isolated extraction result.
Less manual document handling
Help teams reduce rekeying, organise document results consistently and make hand-offs easier to check.
Review and control
Keep people in control
- Check important fields against the original page.
- Keep missing values visible rather than assuming an answer.
- Apply the relevant business approval process before acting on extracted information.
Get started
Start with your use case
Start with one recurring document family and the information staff currently extract by hand.
Useful starting information
- Representative document types
- The fields and tables the team needs
- A reviewer and downstream process owner
Success measures to track
- Review effort per document
- Field and table accuracy on representative samples
- Usefulness of the exported data
Fit with your existing systems
Agree the input formats, storage, review rules and export destination for the selected document workflow.
Your next conversation
Which documents create the most repetitive data-entry work for your team?
Tell us how your team works today. We’ll explore the information, integrations and review process that fit your use case.
Discuss this use case