computer-vision developer-tools ai-agents architectural-design

OCR for construction documents does not work, we fixed it

getanchorgrid.com

March 30, 2026

1 min read

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53/100

Summary

Free-tier door detection for architectural floor-plan PDFs typically completes in 2–4 minutes per job, with processing time increasing based on page count and drawing complexity. Pro and Enterprise plans utilize dedicated GPU infrastructure for faster detection.

Key Takeaways

Free-tier door detection processing time typically ranges from 2 to 4 minutes per job, depending on page count and drawing complexity.
Pro and Enterprise plans utilize dedicated GPU infrastructure for faster door detection processing.
The door detection endpoint requires a document_id and accepts JSON requests; it does not support direct file uploads.
Credits are charged based on the total page count of the submitted document, regardless of whether those pages contain doors.

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Coverage & discussions

Hacker News · getanchorgrid.com

OCR for construction documents does not work, we fixed it ↗

Community discussions

Hacker News discussion ↗

Historical count: 5 · 5 saved in sample · Historical sample

Analysis ready

Community Sentiment

Mixed

Positives

The development of a parsing engine that converts CAD files into structured JSON highlights a promising direction for improving data sharing in construction, potentially enhancing project accuracy.
Despite some misses, the OCR system's overall performance in identifying doors indicates progress in automating the extraction of critical information from construction documents.

Concerns

Concerns about the reliability of OCR in construction documents are significant, as past bugs have shown how easily critical data can be misinterpreted, leading to serious consequences.
The lack of machine learning in the critical path raises questions about the effectiveness and scalability of the proposed solution, especially given the precision required in CAD and GIS applications.
The article's focus on 'why' rather than 'how' may come off as marketing fluff, which detracts from the technical insights that developers seek in AI implementations.