Structured extraction with the Docen API and long documents

Strategies for extracting from documents that don't fit in a single pass.

The problem

long-document extraction sounds simple until you look at real documents. The failure cases are where most of the difficulty — and most of the value — lives.

What we did

We treated it as a measurement problem first. Before changing the model, we built a labeled set of the hardest examples we could find, so we could tell whether any change actually helped.

From there, the work was iterative: adjust the model, score it on the hard set, keep what moved the number, and throw out what didn't. No change ships without evidence.

• A benchmark built from real, difficult documents.
• Targeted training on the failure cases.
• Confidence signals so downstream systems know when to check.

Results

Want to see it on your own documents? Open the playground or reach out — we're happy to run a sample with you.