Document Intelligence Pipeline

This is an illustrative example build, not a delivered client project. It describes a problem we're equipped to solve and how we'd approach it.

Construction businesses sit on mountains of documents — drawings, contracts, variation orders, inspection reports — in wildly inconsistent formats. The information inside is valuable, but it's locked in PDFs and scans that no system can read, so teams re-key it by hand.

We build a pipeline that turns documents into structured data your existing systems can use:

We start with the one or two document types that cost you the most time and expand from there.

OCR handles the visual layer, extraction models pull the fields that matter, and a confidence threshold decides what's safe to auto-accept versus what a person should check. Everything is documented so your team can maintain and extend it.

Scope drives the timeline. A pipeline for a single, well-understood document type can ship in a few weeks; broader coverage across many formats runs longer. Data readiness is the biggest variable — clean, consistent source documents move faster than a decade of inconsistent scans.

We define the targets before building: extraction accuracy against a labelled sample, the proportion of documents processed without manual correction, and the hours returned to your team. You'll know what good looks like before we write a line of code.