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

Dimensions on each drawing had to be manually checked against an abbreviation table to identify which ones mattered, then filtered by hand — not scalable at a volume of 200 drawings per day without expanding the team.
An on-premise pipeline uses ADEOS to extract dimension data from engineering drawings, automatically filtering target parameters and structuring them into ERP-ready Excel outputs.
| Impact Metric | Before | After |
|---|---|---|
Manual Effort | 60 mins | ~5 mins |
Processing Capacity | 50/day | 200/day |
Quality Control Effort | 100% | 30% |
Engineers cannot check every drawing manually as production grows. ADEOS flagged key data points in drawings and brought them up for review. Reviewing only the flagged drawings keeps work moving without adding staff.
Ready to see how our engineering-first AI solutions can streamline your operations and drive real impact?

Extract information once and reuse it across the entire bid workflow. Eliminated repeated manual reading, data entry, document preparation, and bid comparison.

Evaluation time/worksheet became 2 to 3 minutes, and 25+ worksheets/day processed across different boards and students.

Per-job turnaround targeted to drop from 3-4 days to under 3 hours, monthly capacity to scale from 12-20 to 75-80 panels, and duplicate item-master entries eliminated through automated de-duplication against Zoho ERP