80–90% reduction in manual effort per drawing, processing capacity scaled to 200 drawings per day, consistent two-sheet Excel output for every extraction

Manually identifying and filtering dimensions without abbreviation. Mapping data into ERP-ready formats was not possible with high volumes of 200 drawings per day without expanding team count to assist with the manual process.
Adeos deployed an on-premise pipeline combining vision language models with OCR to extract, filter, and structure dimension data from engineering drawings into ERP-ready Excel output
| Impact Metric | Before | After |
|---|---|---|
Manual effort per drawing | ~30–60 mins per drawing | ~5–10 mins |
Processing capacity | ~30–50 drawings/day | 200 drawings/day |
Quality control effort | 100% of drawings reviewed | ~10–20% (low-confidence only) |
Confidence scoring shifted QC from checking every record to reviewing only flagged outputs. Processing capacity scaled with drawing volume, not headcount.
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One extraction workflow distributed to 3 departments, reducing per-drawing review from days to hours across a 50–100 drawing project cycle.

Customer onboarding was cut from 5 days to 10 minutes, 100% audit trail coverage achieved, and annual audit costs eliminated across a 3-continent key management operation.

Authentication latency cut to under 1 second, tenant integration reduced from weeks to 15 minutes, and passwordless login active for 5,000+ users across 3 enterprises with zero bypass incidents.