VizSeek uses vector-based search to compare files beyond exact names, part numbers, or keywords. Technical data can be transformed into searchable representations that capture visual shape, geometry, text, metadata, and other meaningful features.

This helps teams search with an image, drawing, CAD file, sketch, screenshot, or text description and find related results even when the matching information lives across different file types.

Engineering information rarely lives in one place. A part may be connected to drawings, revisions, assemblies, suppliers, materials, quotes, inspection records, and ERP or PLM data. VizSeek uses graph-based relationships to help organize and understand how these records connect, making results more useful and context-aware.

Instead of only showing files that look similar, graph intelligence helps teams see where a part is used, which drawing belongs to which item, what supplier is associated with it, and how records connect across systems.

VizSeek can use agentic AI to support multi-step tasks that go beyond a single search query. An AI assistant can help interpret a user’s request, search across different sources, extract important fields, compare similar files, summarize results, and guide users toward the next action.

This makes VizSeek useful not only for finding information, but also for helping teams complete practical engineering and manufacturing workflows faster.