A form reviewer looking at AI-extracted invoice or contract data has always had the same problem: the extracted values live in one place, and the proof they're correct — the actual scanned page — lives in another. Getting confident in an AI extraction meant constantly flipping between a PDF viewer and a form, matching numbers up by eye and hoping nothing shifted between tabs.
The File Renderer's Field Extraction mode closes that gap: it puts the document and the AI's extracted regions in the same view, so a reviewer can see exactly where every value came from and correct it on the spot.
1. Turning it on
Field Extraction lives on the Document Viewer component's properties panel. Toggle it on for any Document Viewer showing a PDF that's been through an OCR/extraction step, and the viewer switches from a plain document preview into a review surface: the PDF renders as before, but now with colored boxes overlaid on every region the extraction step detected.
2. Highlights track the document, not the screen
Each highlight is stored as a normalized region — a position and size expressed as a fraction of the page (0 to 1), not as fixed pixels. That's what lets a highlight stay locked to the exact word or line it belongs to no matter how far a reviewer zooms in, or what size window they're working in. The highlight is drawn as an overlay on top of the rendered page, scaled to match, so it never drifts out of alignment with the text underneath it.
3. Two ways to cross-reference a value
- Field → region. Click a field over in the form sidebar, and the document scrolls straight to the matching region and outlines it, so you can see the source instantly without hunting through pages.
- Region → field. Click a highlighted box directly on the page, and a floating card opens right over that spot showing the extracted value.
Either direction gets you to the same place: the value and its source, side by side, with no tab-switching.
4. Correcting a value in place
The floating card that opens on a region isn't read-only — it's an editable field. If the AI misread a handwritten total or a smudged digit, correct it right there and confirm, and the form's underlying value updates immediately. There's no separate "edit mode" to enter and no need to go find the field elsewhere in the form first.
5. Confidence is visible at a glance
Every highlight is color-coded by the extraction's own confidence score — high-confidence reads are shown in green, lower-confidence reads in red, so a reviewer's eye is naturally drawn to the values most worth double-checking instead of having to verify every field with equal effort. Line-item rows (like invoice line entries) get a dashed border to distinguish repeating structured data from single-value fields.
6. Provider-agnostic by design
The highlight coordinates are stored as an explicit data binding on the Document Viewer, independent of which OCR provider produced them. Whether the extraction ran through Textract, Azure Document Intelligence, or another provider behind the scenes, the review experience — highlights, click-to-locate, inline correction — works exactly the same way.
Best practices
- Turn on Field Extraction specifically for review-and-correct workflows — forms where a human needs to confirm AI-extracted values before they're trusted downstream.
- Use the confidence colors as your triage order — check the red highlights first; green ones are usually safe to skim.
- Correct values through the floating card, not by re-running extraction — your correction is saved immediately as the form's value of record.