For engineering, procurement, and operations leaders, this SME Media webinar tackles why physical innovation lags digital ideas and why upstream data stays siloed. CADDi's Patrick Harrigan and Sid Srivastava explain how a data layer, semantic layer, and workflow products in the CADDi AI Data Platform turn past engineering knowledge into faster quotes, smarter sourcing, and part consolidation.

Frequently asked questions

Do we need to consolidate our ERP and PLM systems first?

No. The CADDi AI Data Platform connects knowledge across existing systems, so teams can use information from multiple ERP and PLM environments without consolidating them first.

Is reuse realistic for engineer-to-order work, where parts aren't identical?

Yes. Patrick explains that 70% to 90% of a new project often overlaps with past work. Similarity scores help engineers evaluate potential matches and decide what to reuse, leaving more time for genuinely new requirements.

How does CADDi help engineering and procurement work together?

The CADDi AI Data Platform gives both teams access to the same knowledge and context behind past decisions. In the webinar, Sid explains how this shared foundation helps teams work faster, reduce conflict, and avoid decisions that lead to rework.

What is a semantic layer?

A semantic layer connects data with its meaning and context, including the reasoning behind past decisions. Patrick describes how knowledge captured as teams use the CADDi AI Data Platform feeds back into this layer, giving future quotes and decisions more context.

What types of data can the CADDi AI Data Platform connect?

In the webinar, Sid demonstrates engineering and procurement information, including drawings, specifications, inspection reports, and procedures. He also describes using recordings of design reviews, converted into transcripts, to capture knowledge beyond traditional documents.