What information is used to train the AI

When preparing your designs, RhinoArtisan analyzes more than just geometry.

In addition to the geometric analysis, the AI also uses information such as:

Breakdown data (materials, gems, quantities, and costs)

Breakdown data plays a key role in training the AI.

At this stage, each design is analyzed from a detailed production perspective, including:

• Complete piece breakdown

• Production cost calculations

• Gemstone listings, including certified stones and melees

• Setting costs

• Other manufacturing-related data

This level of detail allows the AI to understand how a piece is built and produced, not just how it looks.

By using breakdown data, the system can identify meaningful similarities between designs based on structure, materials, and production characteristics — not only geometry.

Technical Report

The Technical Report adds valuable contextual information, especially in B2B production workflows.

It allows you to define client-specific concepts and production details, which are particularly useful for manufacturers.

This information can include:

• Client or brand references

• Purchase orders (PO)

• Style or collection identifiers

• CAD designer information

• Any other data currently used in RhinoArtisan Technical Reports

By including this information, the AI can help you find designs based on clients, production references, or internal criteria — not just visual characteristics.

Boutique

Boutique data represents the retail-focused information associated with each design.

This is the type of information typically used in physical stores or online shops, and it is specifically designed for in-store usage.

It can include:

• Product descriptions

• SKU references

• Retail prices

• Promotions and commercial conditions

• Delivery times

By incorporating boutique data, the AI can understand how a design is positioned and sold, making it especially useful for in-store search, sales assistance, and customer-facing experiences.

Notes and custom information

Any information added to the design notes is also taken into account.

This allows you to include custom details, internal comments, or specific criteria that may not fit into predefined fields.

Because of this, the possibilities are virtually unlimited and can be adapted to each workflow.

Summary

AI Semantic Search uses a combination of geometric analysis and design data to understand each piece in depth.

By combining breakdown data, technical reports, boutique information, and custom notes, RhinoArtisan can identify meaningful similarities between designs and make them searchable by intent, context, and usage — not just by appearance.

This approach makes AI Semantic Search especially powerful for design, manufacturing, and retail workflows.