A hybrid extraction pipeline that pulls revision data from 4,700+ engineering drawings, replacing weeks of manual work.
Pulling revision data out of thousands of engineering drawings was manual, slow, and expensive. A single pass across the corpus took around four weeks and cost roughly £8,000 in engineering effort.
A three-tier hybrid pipeline that sends each page to the cheapest method that can handle it. Most pages clear with fast automated extraction. Harder pages route to an AI vision model. A small remainder is flagged for human review. A confidence score decides the routing, so cost stays low without losing accuracy.
A production system that reads revision data from 4,700+ engineering drawings without manual data entry. Confidence-based routing and per-site validation keep the output trustworthy, and anything the system is unsure about goes to a person rather than being guessed.
A full pass dropped from about four weeks to 45 minutes, at a cost of around £40 against the previous £8,000. The architecture pattern behind it was published on InfoQ and Towards Data Science.
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