The Most Advanced PDF Annotation Interface Yet

In our previous post, we shared how we entirely rethought the annotation experience for audio transcription with tons of new tools and shortcuts to remove friction and improve precision so annotators can move faster (without sacrificing quality).

This week, we’ve done the same for one of the most common—and most challenging—data types in enterprise AI: large, complex PDF documents and image OCR.

PDFs and scanned images show up everywhere: contracts, financial filings, clinical reports, insurance claims, research papers, scanned forms, and regulatory submissions. They’re long, dense documents that mix text, tables, layouts, and structure in ways that are difficult for both humans and machines to interpret.

Traditional annotation interfaces tend to break down quickly at this scale and annotators spend more time navigating documents than actually labeling them.

So once again we started with feedback from real annotators and asked: What would the best possible UI look like for document AI at scale?

The result is the most advanced OCR + PDF labeling UI on the market, now available in Label Studio Enterprise.

Designed for navigating large, complex documents

When you’re working with a 200-page document, navigation is productivity. Performance was prioritized to make the interface feel immediate and load large documents quickly, even if they contain hundreds of pages.

There are several new view modes to find your way around documents:

• Side-by-side (two-page spread) for reviewing content in context
• Gallery view, showing a grid of page thumbnails for rapid scanning
• Continuous scrolling, with pages flowing naturally one after another
• Multi-document support to annotate two or more PDFs at the same time.

As you scan the document, you'll notice each thumbnail works as a live preview showing the page content, annotation boxes, and how many annotations have been applied to the page.

Because our users tend to spend lots of time with documents, we ensured full support for a keyboard-first workflow, with dedicated shortcuts for all the tools, navigation, labeling, search, zoom, rotation, and view modes.

This way up: page rotation

Annotators can rotate individual pages, with each page remembering its rotation independently. Extremely handy when encountering a scan upside-down halfway through the document!

Faster, more precise text annotations

The bounding box tool gets a major update that introduces live regions:

• Each time you draw a region, the text inside the box is automatically transcribed
• Resize regions and the extracted text updates in real time
• two or more annotation regions can overlap to capture multiple interpretations or layered labels. And you can hold down a modifier key to quickly select text beneath existing annotations.
• Regions can now span across multiple pages, eliminating awkward workarounds.
• ML model predictions are displayed as a dashed overlay boxes with 🤖 indicator and can be toggled on/off independently from manual annotations

This tight visual feedback loop makes it easy to refine selections with confidence.

In addition to drawing regions, annotators can pick from 3 selector modes that intelligently capture individual words, sentences, or whole paragraphs with a single click. And we made it possible to automatically extract and populate common document metadata such as title, author, and date.

Native support for tables

Tables are one of the hardest structures to parse annotate and yet one of the most important.

We’ve added automatic table structure detection, identifying rows and columns directly from the document. When a table is selected, annotators get a dedicated interface to:

• Refine detected rows and columns
• Add, delete, merge, or re-detect rows and columns on demand
• Label individual cells with entity types

Automatically extract and edit the text content of each cell.

Display annotations in context, as part of the document

This makes it dramatically easier to validate annotations visually and spot misalignments or extraction errors.

Document-wide search and bulk labeling

An improved document-wide search makes it easier to search across the entire document, preview all matching results, and label every match in a single action.

Built on the programmable UI engine

The whole UI includes user-configurable settings so power annotators can tune the experience to their workflow.

And just like our advanced audio transcription interface, the new PDF annotation experience is powered by the programmable UI engine in Label Studio Enterprise.

That engine allows teams to build fully custom annotation experiences using standard React components, while still benefiting from Label Studio’’s underlying data model, workflow orchestration, and permission system.

The result is a UI that’s:

• Purpose-built for large PDFs and scanned images
• Extensible to new document types
• Adaptable to evolving annotation needs

And most importantly, designed to scale with real enterprise workloads.

By removing friction from annotation workflows, we help teams create higher-quality datasets faster—and give humans the tools they need to do their best work.

If complex and multimodal data is critical to your AI models, our team can now help you build entirely custom, task-specific experiences to dramatically increase annotation speed and quality. Reach out to us to build a proof of concept for your use case and workflow.