WEBINAR

Cut Harness Data Entry From Days to Minutes Using AI

How much engineering time is your team spending re-entering harness data from supplier PDFs, customer drawings, and legacy documents? Join Cadonix to see how Import AI extracts bill of materials (BOMs), cavity tables, and wiring data from PDF documents and converts them into structured, validated harness information in minutes. Register now!
August 06, 2026
3:00 PM UTC
1 hour

Now Available On-Demand!
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Multimodal AI PDF Extraction: From Wire Harness Drawings to Manufacturing-Constrained Designs

Harness engineering teams lose thousands of hours a year to a problem that shouldn't exist: retyping data that already exists, just trapped in static PDFs, customer drawings, and supplier documents. In this webinar, the Cadonix AI team introduces Import AI, a new capability that transforms static PDFs into structured, validated harness data, including BOMs, cavity tables, and wiring/signal data, in minutes instead of days.

Attendees will see how Import AI combines domain-aware AI with guided human-in-the-loop validation to eliminate manual transcription errors and recover engineering hours currently lost to data entry. The session will walk through how Import AI identifies and classifies tables with engineering context, not just pattern-matching, and how teams stay in control of every extraction before it enters their workflow.

If your team is still manually re-creating BOMs and connectivity tables from PDFs, this session will show you what that process looks like when it takes minutes, not days.

Speakers:

Steph Xu | AI/ML Research Fellow

Steph Xu | AI/ML Research Fellow

MBA and Master's in Electrical Engineering and Computer Science Candidate

Re:Build Manufacturing

Steph Xu (AI/ML Research Fellow, MBA and Master's in Electrical Engineering and Computer Science Candidate). Steph brings deep experience building large-scale distributed systems and cloud products, with a strong academic focus on AI, combining technical expertise with strategic insight to deliver high-impact innovations.

Karim ElSayed

Karim ElSayed

Applied Scientist II, Ph.D. Mechanical Engineering

Re:Build Manufacturing

Karim ElSayed (Applied Scientist II, Ph.D. Mechanical Engineering). Karim brings deep expertise in computer vision and reinforcement learning, building intelligent simulation tools and automation pipelines, and applies advanced AI at Cadonix to streamline ECAD design and manufacturing workflows.

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