Let AI Read Harness Drawings · Agent Exploration Prototype
Automotive harness drawings carry large volumes of non-standard, cross-platform, strongly-connected engineering information; going from drawing to production board diagram has long relied on manual reading, organizing, and drafting. We have built an "agent exploration pre-processing" prototype — it reads raw schematics directly, automatically identifies time candidates, geometric relations, label bounding boxes, and upstream/downstream connections, and outputs a structured Excel BOM. Understanding harness drawings is one of the key hard problems in industrial-drawing AI-ization.
Each project is annotated with its position in the product system, making it easy to see at a glance how systems support each other.



The harness industry has no shortage of CAD tools — what it lacks is a system that truly reads drawings, extracts BOMs, validates connections, and generates board diagrams.
Customer, legacy, and cross-platform drawings vary in expression, hard to process automatically.
Material info scattered across graphics, annotations, tables, and notes still needs manual organizing.
Relations among wire numbers, holes, terminals, and branch paths exceed simple OCR.
Production board diagrams still largely depend on designers' manual understanding, layout, and correction.
This is not efficiency optimization but a change in how work is done. Past: engineers read and draft. Future: AI understands drawings and auto-generates production results.
This is not a drawing-recognition problem but an engineering-semantics understanding problem. Harness drawings simultaneously contain graphics, text, materials, connections, process rules, and production requirements.
Many tools exist, but the key layer "non-standard drawing → AI understanding → production result" is missing.
| Type | Current Capability | Key Gap | Status |
|---|---|---|---|
| Int'l Harness SW | Design, BOM, mfg docs, assembly data | Strong in standardized design, weak at reverse-understanding non-standard drawings | Design-strong |
| Domestic CAD/CAPP | Drafting, process aid, BOM output, fixture board | Still highly dependent on engineer operation & judgment | Assist-strong |
| Engineering-Drawing AI | OCR, table recognition, dimension extraction, local understanding | Doesn't understand harness objects, connections, board craft | General-strong |
| Automation Vendors | Cutting, crimping, testing, assembly | Solve production actions, not upstream drawing understanding | Mfg-strong |
| What We Build | Drawing understanding, BOM, connectivity check, board generation | Fill the missing AI-understanding layer between drawing and production | Missing Layer |
Agent exploration pre-processing: auto-convert non-standard schematics into a structured Excel BOM — 9-step auto-exploration from data prep to entity comparison.
Accept customer non-standard schematics (CONTOUR/EXP/VT/RD/PD) without prior normalization.
Filter 1s/3s/5s/10s time candidates from CONTOUR info via a filter.
compute_stats calculates bbox medium-2/0/8/15/30 and more geometric params for later association.
upstream_validation + xlh_bbox verify geometric and directory-structure consistency.
default / adaptive / adaptive_light / adaptive_loose auto-run to fit different drawings.
Output wire no., spec, wire type, color, left/right functional parts / terminals / seals — full fields.
The agent executes step by step — data prep → pre-refine → time candidates → geometry → association validation → directory gen → multi-variant → algorithm selection → application → verification — turning non-standard schematics into an Excel BOM.
Product content has been published based on internal materials. The following areas are planned for further development:
Explore Xianma AI solutions in other domains