Dense regulatory material creates a difficult engineering problem: the system must extract important details at scale without losing accuracy, traceability or the context on which decisions depend.
The challenge
Specialist regulatory workflows depend on turning long, varied source documents into structured information. Manual review is demanding, but poor automated extraction can introduce costly downstream errors.
What we engineered
An AI-assisted document-processing pipeline for extracting and structuring regulatory information. Evaluation of extraction quality formed part of the design, rather than being treated purely as a final manual check.
Why that matters
Useful document intelligence is not just a prompt that produces plausible text. It depends on reliable source handling, clear data structures, targeted testing and a way for experts to review exceptions.
What this work demonstrates
How AI engineering and evaluation can support demanding information-processing workflows, where data quality is central to the service itself.